From e9935624f77fd407f2c91a96f5c102f47de24ba9 Mon Sep 17 00:00:00 2001 From: firestar5683 <168790843+firestar5683@users.noreply.github.com> Date: Tue, 26 May 2026 20:10:16 -0500 Subject: [PATCH] smoosh smoosh --- scripts/model_compiler.py | 167 +- .../controls/lib/longitudinal_planner.py | 3 +- selfdrive/modeld/compile_modeld.py | 358 +++ selfdrive/modeld/get_model_metadata.py | 19 +- selfdrive/modeld/modeld.py | 24 +- selfdrive/modeld/modeld_v16.py | 447 +++ .../settings/starpilot/driving_model.py | 13 +- .../ui/mici/layouts/settings/driving_model.py | 13 +- starpilot/assets/download_functions.py | 2 +- starpilot/assets/model_manager.py | 159 +- starpilot/common/model_versions.py | 27 + starpilot/common/starpilot_variables.py | 3 +- starpilot/system/the_pond/the_pond.py | 12 +- starpilot/ui/qt/offroad/model_settings.cc | 9 +- uncompiledmodels/driving_off_policy.onnx | Bin 41191256 -> 41192485 bytes uncompiledmodels/driving_on_policy.onnx | Bin 33679041 -> 33680163 bytes uncompiledmodels/driving_vision.onnx | 2436 +++++++++-------- 17 files changed, 2406 insertions(+), 1286 deletions(-) create mode 100644 selfdrive/modeld/compile_modeld.py create mode 100644 selfdrive/modeld/modeld_v16.py create mode 100644 starpilot/common/model_versions.py diff --git a/scripts/model_compiler.py b/scripts/model_compiler.py index 817a5d840..3105b82ed 100644 --- a/scripts/model_compiler.py +++ b/scripts/model_compiler.py @@ -3,6 +3,7 @@ import argparse import codecs import os import pickle +import json import re import shutil import subprocess @@ -10,11 +11,18 @@ import sys from pathlib import Path - REPO_ROOT = Path(__file__).resolve().parents[1] +if str(REPO_ROOT) not in sys.path: + sys.path.insert(0, str(REPO_ROOT)) + +from openpilot.selfdrive.modeld.constants import ModelConstants +from openpilot.starpilot.common.model_versions import uses_combined_driving_artifacts + DEFAULT_INPUT_ROOT = Path("/data/openpilot/uncompiledmodels") DEFAULT_OUTPUT_ROOT = Path("/data/openpilot/compiledmodels") COMPILE_SCRIPT = REPO_ROOT / "tinygrad_repo/examples/openpilot/compile3.py" +COMBINED_COMPILE_SCRIPT = REPO_ROOT / "selfdrive/modeld/compile_modeld.py" +MODEL_VERSIONS_CACHE = Path("/data/models/.model_versions.json") DM_MODEL_KEY = "dm" DM_MODEL_NAME = "dmonitoring_model" DM_TARGET_ALIASES = {DM_MODEL_KEY, "dmonitoring", DM_MODEL_NAME} @@ -26,7 +34,33 @@ COMPONENT_ALIASES = { "driving_policy": ("driving_policy", "policy"), "driving_vision": ("driving_vision", "vision"), } -REQUIRED_COMPONENTS = {"driving_policy", "driving_vision"} +MEDMODEL_INPUT_SIZE = (512, 256) +DEFAULT_CAMERA_RESOLUTIONS = ( + (1928, 1208), + (1344, 760), +) + + +def build_compile_env(*, combined: bool = False) -> dict[str, str]: + env = os.environ.copy() + existing_pythonpath = env.get("PYTHONPATH", "") + env["PYTHONPATH"] = f"{REPO_ROOT}:{existing_pythonpath}" if existing_pythonpath else str(REPO_ROOT) + + numeric_defaults = { + "DEBUG": "0", + "FLOAT16": "1", + "IMAGE": "2", + "JIT_BATCH_SIZE": "0", + "NOLOCALS": "1", + } + for key, default in numeric_defaults.items(): + value = env.get(key) + try: + int(str(value), 0) + except (TypeError, ValueError): + env[key] = default + + return env def parse_args() -> argparse.Namespace: @@ -37,6 +71,7 @@ def parse_args() -> argparse.Namespace: parser.add_argument("--dm", action="store_true", help="Compile the driver monitoring model into dmonitoring_model_tinygrad.pkl.") parser.add_argument("--input-dir", type=Path, default=DEFAULT_INPUT_ROOT, help="Directory containing staged ONNX files. Flat root files like driving_policy.onnx are preferred.") parser.add_argument("--output-dir", type=Path, default=DEFAULT_OUTPUT_ROOT, help="Directory for compiled tinygrad pkls and metadata.") + parser.add_argument("--version", help="Model version. v16+ uses the combined driving_tinygrad artifact path. If omitted, split-policy staged models default to the combined build.") parser.add_argument("--list", action="store_true", help="List detected staged models and exit.") parser.add_argument("--force", action="store_true", help="Legacy no-op. Compiled outputs are always cleared before a build.") @@ -66,14 +101,6 @@ def detect_component(path: Path) -> str | None: return None -def normalize_model_files(model_files: dict[str, Path]) -> dict[str, Path]: - normalized = dict(model_files) - on_policy_path = normalized.pop("driving_on_policy", None) - if on_policy_path is not None and "driving_policy" not in normalized and "driving_off_policy" in normalized: - normalized["driving_policy"] = on_policy_path - return normalized - - def find_staged_dm(input_root: Path) -> Path | None: if not input_root.is_dir(): return None @@ -107,7 +134,6 @@ def find_staged_models(input_root: Path) -> dict[str, dict[str, Path]]: component = detect_component(onnx_file) if component: model_files[component] = onnx_file - model_files = normalize_model_files(model_files) if model_files: found[child.name] = model_files @@ -137,7 +163,7 @@ def find_staged_models(input_root: Path) -> dict[str, dict[str, Path]]: flat_root_files[component] = onnx_file if flat_root_files: - found["_root"] = normalize_model_files(flat_root_files) + found["_root"] = flat_root_files return found @@ -156,7 +182,7 @@ def resolve_model_files(input_root: Path, model_key: str) -> dict[str, Path]: component = detect_component(onnx_file) if component: prefixed_files[component] = onnx_file - return normalize_model_files(prefixed_files) + return prefixed_files def get_metadata_value_by_name(model, name: str): @@ -190,17 +216,94 @@ def write_metadata(onnx_path: Path, output_path: Path) -> None: def compile_component(onnx_path: Path, output_path: Path) -> None: - env = os.environ.copy() - existing_pythonpath = env.get("PYTHONPATH", "") - env["PYTHONPATH"] = f"{REPO_ROOT}:{existing_pythonpath}" if existing_pythonpath else str(REPO_ROOT) subprocess.run( [sys.executable, str(COMPILE_SCRIPT), str(onnx_path), str(output_path)], cwd=REPO_ROOT, - env=env, + env=build_compile_env(combined=False), check=True, ) +def compile_combined_model(component_paths: dict[str, Path], output_path: Path) -> None: + vision_path = component_paths["driving_vision"] + off_policy_path = component_paths["driving_off_policy"] + on_policy_path = component_paths.get("driving_on_policy") or component_paths.get("driving_policy") + if on_policy_path is None: + raise ValueError("Combined compile requires driving_on_policy.onnx (or driving_policy.onnx) alongside driving_off_policy.onnx") + + frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ + camera_resolutions = [f"{width}x{height}" for width, height in DEFAULT_CAMERA_RESOLUTIONS] + subprocess.run( + [ + sys.executable, + str(COMBINED_COMPILE_SCRIPT), + "--model-size", + f"{MEDMODEL_INPUT_SIZE[0]}x{MEDMODEL_INPUT_SIZE[1]}", + "--camera-resolutions", + *camera_resolutions, + "--vision-onnx", + str(vision_path), + "--off-policy-onnx", + str(off_policy_path), + "--on-policy-onnx", + str(on_policy_path), + "--output", + str(output_path), + "--frame-skip", + str(frame_skip), + ], + cwd=REPO_ROOT, + env=build_compile_env(combined=True), + check=True, + ) + + +def infer_model_version(model_key: str, explicit_version: str | None) -> str: + if explicit_version: + return explicit_version.strip() + + if MODEL_VERSIONS_CACHE.is_file(): + try: + version_map = json.loads(MODEL_VERSIONS_CACHE.read_text()) + version = version_map.get(model_key) + if isinstance(version, str) and version.strip(): + return version.strip() + except Exception: + pass + + return "" + + +def should_use_combined_artifacts(model_version: str, model_files: dict[str, Path]) -> bool: + if uses_combined_driving_artifacts(model_version): + return True + if model_version.strip(): + return False + + has_vision = "driving_vision" in model_files + has_off_policy = "driving_off_policy" in model_files + has_on_policy = "driving_on_policy" in model_files or "driving_policy" in model_files + return has_vision and has_off_policy and has_on_policy + + +def resolve_split_component_inputs(model_files: dict[str, Path]) -> dict[str, Path]: + resolved: dict[str, Path] = {} + + vision_path = model_files.get("driving_vision") + if vision_path is not None: + resolved["driving_vision"] = vision_path + + policy_path = model_files.get("driving_policy") or model_files.get("driving_on_policy") + if policy_path is not None: + resolved["driving_policy"] = policy_path + + off_policy_path = model_files.get("driving_off_policy") + if off_policy_path is not None: + resolved["driving_off_policy"] = off_policy_path + + return resolved + + def clear_existing_outputs(output_dir: Path) -> list[Path]: removed = [] for existing in sorted(output_dir.iterdir()): @@ -277,18 +380,38 @@ def main() -> int: f"or optionally {args.input_dir / model_key}/*.onnx" ) - missing = sorted(REQUIRED_COMPONENTS - set(files)) - if missing: - raise SystemExit(f"Missing required ONNX files for {model_key}: {', '.join(missing)}") + model_version = infer_model_version(model_key, args.version) + use_combined_artifacts = should_use_combined_artifacts(model_version, files) args.output_dir.mkdir(parents=True, exist_ok=True) - print(f"Compiling {model_key} from {args.input_dir} -> {args.output_dir}") + mode_label = "combined" if use_combined_artifacts else "split" + version_label = model_version or ("auto-combined" if use_combined_artifacts else "legacy-default") + print(f"Compiling {model_key} ({version_label}, {mode_label}) from {args.input_dir} -> {args.output_dir}") removed = clear_existing_outputs(args.output_dir) if removed: print(f" cleared {len(removed)} existing output entries") - for component, onnx_path in sorted(files.items()): + if use_combined_artifacts: + required_components = {"driving_vision", "driving_off_policy"} + if not (files.get("driving_on_policy") or files.get("driving_policy")): + required_components.add("driving_on_policy") + missing = sorted(component for component in required_components if component not in files) + if missing: + raise SystemExit(f"Missing required ONNX files for combined compile of {model_key}: {', '.join(missing)}") + + output_pkl = args.output_dir / f"{model_key}_driving_tinygrad.pkl" + compile_combined_model(files, output_pkl) + print(f" saved {output_pkl.name}") + print("Done.") + return 0 + + split_components = resolve_split_component_inputs(files) + missing = sorted(component for component in ("driving_policy", "driving_vision") if component not in split_components) + if missing: + raise SystemExit(f"Missing required ONNX files for {model_key}: {', '.join(missing)}") + + for component, onnx_path in sorted(split_components.items()): output_pkl = args.output_dir / f"{model_key}_{component}_tinygrad.pkl" output_metadata = args.output_dir / f"{model_key}_{component}_metadata.pkl" diff --git a/selfdrive/controls/lib/longitudinal_planner.py b/selfdrive/controls/lib/longitudinal_planner.py index 3172ed434..424f09f99 100755 --- a/selfdrive/controls/lib/longitudinal_planner.py +++ b/selfdrive/controls/lib/longitudinal_planner.py @@ -8,6 +8,7 @@ from openpilot.common.constants import CV from openpilot.common.filter_simple import FirstOrderFilter from openpilot.common.realtime import DT_MDL from openpilot.selfdrive.modeld.constants import ModelConstants +from openpilot.starpilot.common.model_versions import is_tinygrad_model_version from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalMpc from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import desired_follow_distance @@ -434,7 +435,7 @@ class LongitudinalPlanner: @property def mlsim(self): - return self.generation in ("v8", "v10", "v11", "v12", "v13", "v14", "v15") + return is_tinygrad_model_version(self.generation) def get_mpc_mode(self) -> str: if not self.mlsim: diff --git a/selfdrive/modeld/compile_modeld.py b/selfdrive/modeld/compile_modeld.py new file mode 100644 index 000000000..cb7b51268 --- /dev/null +++ b/selfdrive/modeld/compile_modeld.py @@ -0,0 +1,358 @@ +#!/usr/bin/env python3 +import argparse +import atexit +import os +import pickle +import time +from collections import defaultdict, namedtuple +from functools import partial + +import numpy as np + + +def _patch_tinygrad_fetch_fw(): + import hashlib + import pathlib + + import zstandard + from tinygrad import helpers + + original_fetch_fw = getattr(helpers, "fetch_fw", None) + if original_fetch_fw is None: + return + + def fetch_fw(path, name, sha256): + firmware_path = pathlib.Path(f"/lib/firmware/{path}/{name}.zst") + if firmware_path.is_file(): + blob = zstandard.ZstdDecompressor().stream_reader(firmware_path.read_bytes()).read() + if hashlib.sha256(blob).hexdigest() == sha256: + return blob + return original_fetch_fw(path, name, sha256) + + helpers.fetch_fw = fetch_fw + + +_patch_tinygrad_fetch_fw() + +from tinygrad.device import Device +from tinygrad.engine.jit import TinyJit +from tinygrad.helpers import Context +from tinygrad.tensor import Tensor + + +NV12Frame = namedtuple("NV12Frame", ["width", "height", "stride", "y_height", "uv_height", "size"]) +WARP_INPUTS = ["img_q", "big_img_q", "tfm", "big_tfm"] +POLICY_INPUTS = ["feat_q", "desire_q", "desire", "traffic_convention", "action_t"] + +WARP_DEV = os.getenv("WARP_DEV") + + +def make_random_images(keys, shape, device=None): + return {key: Tensor.randint(shape, low=0, high=256, dtype="uint8", device=device).realize() for key in keys} + + +def warp_perspective_tinygrad(src_flat, matrix_inverse, dst_shape, src_shape, stride_pad, border_fill_val=None): + width_dst, height_dst = dst_shape + height_src, width_src = src_shape + + x = Tensor.arange(width_dst, device=WARP_DEV).reshape(1, width_dst).expand(height_dst, width_dst).reshape(-1) + y = Tensor.arange(height_dst, device=WARP_DEV).reshape(height_dst, 1).expand(height_dst, width_dst).reshape(-1) + + # Inline 3x3 matmul as elementwise to avoid reduce ops and enable fusion with gather. + src_x = matrix_inverse[0, 0] * x + matrix_inverse[0, 1] * y + matrix_inverse[0, 2] + src_y = matrix_inverse[1, 0] * x + matrix_inverse[1, 1] * y + matrix_inverse[1, 2] + src_w = matrix_inverse[2, 0] * x + matrix_inverse[2, 1] * y + matrix_inverse[2, 2] + + src_x = src_x / src_w + src_y = src_y / src_w + + x_round = Tensor.round(src_x) + y_round = Tensor.round(src_y) + x_nn_clipped = x_round.clip(0, width_src - 1).cast("int") + y_nn_clipped = y_round.clip(0, height_src - 1).cast("int") + idx = y_nn_clipped * (width_src + stride_pad) + x_nn_clipped + sampled = src_flat[idx] + + if border_fill_val is None: + return sampled + + in_bounds = ((x_round >= 0) & (x_round <= width_src - 1) & + (y_round >= 0) & (y_round <= height_src - 1)).cast(sampled.dtype) + return sampled * in_bounds + Tensor(border_fill_val, dtype=sampled.dtype) * (1 - in_bounds) + + +def frames_to_tensor(frames): + height = (frames.shape[0] * 2) // 3 + width = frames.shape[1] + return Tensor.cat( + frames[0:height:2, 0::2], + frames[1:height:2, 0::2], + frames[0:height:2, 1::2], + frames[1:height:2, 1::2], + frames[height:height + height // 4].reshape((height // 2, width // 2)), + frames[height + height // 4:height + height // 2].reshape((height // 2, width // 2)), + dim=0, + ).reshape((6, height // 2, width // 2)) + + +def make_frame_prepare(nv12: NV12Frame, model_w, model_h): + cam_w, cam_h, stride, y_height, uv_height, _ = nv12 + uv_offset = stride * y_height + stride_pad = stride - cam_w + + def frame_prepare_tinygrad(input_frame, matrix_inverse): + # UV_SCALE @ M_inv @ UV_SCALE_INV simplifies to elementwise scaling. + matrix_inverse_uv = matrix_inverse * Tensor([[1.0, 1.0, 0.5], [1.0, 1.0, 0.5], [2.0, 2.0, 1.0]], device=WARP_DEV) + # Deinterleave NV12 UV plane (UVUV... -> separate U, V). + uv = input_frame[uv_offset:uv_offset + uv_height * stride].reshape(uv_height, stride) + with Context(SPLIT_REDUCEOP=0): + y = warp_perspective_tinygrad( + input_frame[:cam_h * stride], + matrix_inverse, + (model_w, model_h), + (cam_h, cam_w), + stride_pad, + ).realize() + u = warp_perspective_tinygrad( + uv[:cam_h // 2, :cam_w:2].flatten(), + matrix_inverse_uv, + (model_w // 2, model_h // 2), + (cam_h // 2, cam_w // 2), + 0, + ).realize() + v = warp_perspective_tinygrad( + uv[:cam_h // 2, 1:cam_w:2].flatten(), + matrix_inverse_uv, + (model_w // 2, model_h // 2), + (cam_h // 2, cam_w // 2), + 0, + ).realize() + yuv = y.cat(u).cat(v).reshape((model_h * 3 // 2, model_w)) + return frames_to_tensor(yuv) + + return frame_prepare_tinygrad + + +def make_input_queues(vision_input_shapes, policy_input_shapes, frame_skip, device): + img = vision_input_shapes["img"] + n_frames = img[1] // 6 + img_buf_shape = (frame_skip * (n_frames - 1) + 1, 6, img[2], img[3]) + + features_buffer = policy_input_shapes["features_buffer"] + desire_pulse = policy_input_shapes["desire_pulse"] + traffic_convention = policy_input_shapes["traffic_convention"] + + npy = { + "desire": np.zeros(desire_pulse[2], dtype=np.float32), + "traffic_convention": np.zeros(traffic_convention, dtype=np.float32), + "tfm": np.zeros((3, 3), dtype=np.float32), + "big_tfm": np.zeros((3, 3), dtype=np.float32), + } + if "action_t" in policy_input_shapes: + npy["action_t"] = np.zeros(policy_input_shapes["action_t"], dtype=np.float32) + + input_queues = { + "img_q": Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(), + "big_img_q": Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(), + "feat_q": Tensor( + np.zeros((frame_skip * (features_buffer[1] - 1) + 1, features_buffer[0], features_buffer[2]), dtype=np.float32), + device=device, + ).contiguous().realize(), + "desire_q": Tensor( + np.zeros((frame_skip * desire_pulse[1], desire_pulse[0], desire_pulse[2]), dtype=np.float32), + device=device, + ).contiguous().realize(), + **{key: Tensor(value, device="NPY").realize() for key, value in npy.items()}, + } + return input_queues, npy + + +def shift_and_sample(buf, new_val, sample_fn): + buf.assign(buf[1:].cat(new_val, dim=0).contiguous()) + return sample_fn(buf) + + +def sample_skip(buf, frame_skip): + return buf[::frame_skip].contiguous().flatten(0, 1).unsqueeze(0) + + +def sample_desire(buf, frame_skip): + return buf.reshape(-1, frame_skip, *buf.shape[1:]).max(1).flatten(0, 1).unsqueeze(0) + + +def make_warp(nv12, model_w, model_h, frame_skip): + frame_prepare = make_frame_prepare(nv12, model_w, model_h) + sample_skip_fn = partial(sample_skip, frame_skip=frame_skip) + + def warp_enqueue(img_q, big_img_q, tfm, big_tfm, frame, big_frame): + tfm = tfm.to(WARP_DEV) + big_tfm = big_tfm.to(WARP_DEV) + Tensor.realize(tfm, big_tfm) + + warped_frame = frame_prepare(frame, tfm).unsqueeze(0).to(Device.DEFAULT) + warped_big_frame = frame_prepare(big_frame, big_tfm).unsqueeze(0).to(Device.DEFAULT) + img = shift_and_sample(img_q, warped_frame, sample_skip_fn) + big_img = shift_and_sample(big_img_q, warped_big_frame, sample_skip_fn) + return img, big_img + + return warp_enqueue + + +def make_run_policy(vision_runner, off_policy_runner, on_policy_runner, vision_features_slice, frame_skip): + sample_desire_fn = partial(sample_desire, frame_skip=frame_skip) + sample_skip_fn = partial(sample_skip, frame_skip=frame_skip) + + def run_policy(img, big_img, feat_q, desire_q, desire, traffic_convention, action_t): + desire = desire.to(Device.DEFAULT) + traffic_convention = traffic_convention.to(Device.DEFAULT) + action_t = action_t.to(Device.DEFAULT) + Tensor.realize(desire, traffic_convention, action_t) + + desire_buf = shift_and_sample(desire_q, desire.reshape(1, 1, -1), sample_desire_fn) + vision_out = next(iter(vision_runner({"img": img, "big_img": big_img}).values())).cast("float32") + + new_feat = vision_out[:, vision_features_slice].reshape(1, -1).unsqueeze(0) + feat_buf = shift_and_sample(feat_q, new_feat, sample_skip_fn) + + inputs = { + "features_buffer": feat_buf, + "desire_pulse": desire_buf, + "traffic_convention": traffic_convention, + "action_t": action_t, + } + on_policy_out = next(iter(on_policy_runner(inputs).values())).cast("float32") + off_policy_out = next(iter(off_policy_runner(inputs).values())).cast("float32") + return vision_out, on_policy_out, off_policy_out + + return run_policy + + +def compile_jit(jit, make_random_inputs, input_keys, frame_skip, vision_metadata, policy_metadata): + vision_input_shapes = vision_metadata["input_shapes"] + policy_input_shapes = policy_metadata["input_shapes"] + + seed = 42 + validation_rtol = 5e-3 if Device.DEFAULT == "QCOM" else 0.0 + validation_atol = 5e-3 if Device.DEFAULT == "QCOM" else 0.0 + + def arrays_match(lhs, rhs): + if lhs.shape != rhs.shape: + return False + if np.issubdtype(lhs.dtype, np.floating) or np.issubdtype(rhs.dtype, np.floating): + return np.allclose(lhs, rhs, rtol=validation_rtol, atol=validation_atol, equal_nan=True) + return np.array_equal(lhs, rhs) + + def random_inputs_run(fn, current_seed, test_val=None, test_buffers=None, expect_match=True): + input_queues, npy = make_input_queues(vision_input_shapes, policy_input_shapes, frame_skip, Device.DEFAULT) + np.random.seed(current_seed) + Tensor.manual_seed(current_seed) + + testing = test_val is not None or test_buffers is not None + n_runs = 1 if testing else 3 + + for idx in range(n_runs): + for value in npy.values(): + value[:] = np.random.randn(*value.shape).astype(value.dtype) + Device.default.synchronize() + random_inputs = make_random_inputs() + start = time.perf_counter() + outs = fn(**{key: input_queues[key] for key in input_keys}, **random_inputs) + mid = time.perf_counter() + Device.default.synchronize() + end = time.perf_counter() + print(f" [{idx + 1}/{n_runs}] enqueue {(mid - start) * 1e3:6.2f} ms -- total {(end - start) * 1e3:6.2f} ms") + + if idx == 0: + val = [np.copy(value.numpy()) for value in outs] + buffers = [np.copy(value.numpy().copy()) for value in input_queues.values()] + + if Device.DEFAULT != "QCOM": + if test_val is not None: + match = all(arrays_match(lhs, rhs) for lhs, rhs in zip(val, test_val, strict=True)) + assert match == expect_match, f"outputs {'differ from' if expect_match else 'match'} baseline (seed={current_seed})" + if test_buffers is not None: + match = all(arrays_match(lhs, rhs) for lhs, rhs in zip(buffers, test_buffers, strict=True)) + assert match == expect_match, f"buffers {'differ from' if expect_match else 'match'} baseline (seed={current_seed})" + return val, buffers + + print("capture + replay") + test_val, test_buffers = random_inputs_run(jit, seed) + print("pickle round trip") + jit = pickle.loads(pickle.dumps(jit)) + random_inputs_run(jit, seed, test_val, test_buffers, expect_match=True) + random_inputs_run(jit, seed + 1, test_val, test_buffers, expect_match=False) + return jit + + +def _parse_size(size): + width, height = size.lower().split("x") + return int(width), int(height) + + +def read_file_chunked_to_shm(path): + from openpilot.common.file_chunker import read_file_chunked + from openpilot.system.hardware.hw import Paths + + shm_path = os.path.join(Paths.shm_path(), os.path.basename(path)) + atexit.register(lambda: os.path.exists(shm_path) and os.remove(shm_path)) + with open(shm_path, "wb") as f: + f.write(read_file_chunked(path)) + return shm_path + + +if __name__ == "__main__": + from tinygrad.nn.onnx import OnnxRunner + from openpilot.selfdrive.modeld.get_model_metadata import make_metadata_dict + from openpilot.system.camerad.cameras.nv12_info import get_nv12_info + + parser = argparse.ArgumentParser() + parser.add_argument("--model-size", type=_parse_size, required=True, help="model input WxH") + parser.add_argument("--camera-resolutions", type=_parse_size, nargs="+", required=True, help="camera resolutions WxH (one or more)") + parser.add_argument("--vision-onnx", required=True) + parser.add_argument("--off-policy-onnx", required=True) + parser.add_argument("--on-policy-onnx", required=True) + parser.add_argument("--output", required=True) + parser.add_argument("--frame-skip", type=int, required=True) + args = parser.parse_args() + + out = defaultdict(dict) + vision_path = read_file_chunked_to_shm(args.vision_onnx) + off_policy_path = read_file_chunked_to_shm(args.off_policy_onnx) + on_policy_path = read_file_chunked_to_shm(args.on_policy_onnx) + model_w, model_h = args.model_size + + vision_runner = OnnxRunner(vision_path) + off_policy_runner = OnnxRunner(off_policy_path) + on_policy_runner = OnnxRunner(on_policy_path) + vision_metadata = make_metadata_dict(vision_path) + off_policy_metadata = make_metadata_dict(off_policy_path) + on_policy_metadata = make_metadata_dict(on_policy_path) + assert off_policy_metadata["input_shapes"] == on_policy_metadata["input_shapes"] + + run_policy_jit = TinyJit( + make_run_policy( + vision_runner, + off_policy_runner, + on_policy_runner, + vision_metadata["output_slices"]["hidden_state"], + args.frame_skip, + ), + prune=True, + ) + + out["metadata"]["vision"] = vision_metadata + out["metadata"]["off_policy"] = off_policy_metadata + out["metadata"]["on_policy"] = on_policy_metadata + + make_random_model_inputs = partial(make_random_images, keys=["img", "big_img"], shape=vision_metadata["input_shapes"]["img"]) + out["run_policy"] = compile_jit(run_policy_jit, make_random_model_inputs, POLICY_INPUTS, args.frame_skip, vision_metadata, on_policy_metadata) + + for cam_w, cam_h in args.camera_resolutions: + nv12 = NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h)) + make_random_warp_inputs = partial(make_random_images, keys=["frame", "big_frame"], shape=nv12.size, device=WARP_DEV) + warp_enqueue = TinyJit(make_warp(nv12, model_w, model_h, args.frame_skip), prune=True) + out[(cam_w, cam_h)] = compile_jit(warp_enqueue, make_random_warp_inputs, WARP_INPUTS, args.frame_skip, vision_metadata, on_policy_metadata) + + with open(args.output, "wb") as f: + pickle.dump(out, f) + print(f"Saved JITs to {args.output} ({os.path.getsize(args.output) / 1e6:.2f} MB)") diff --git a/selfdrive/modeld/get_model_metadata.py b/selfdrive/modeld/get_model_metadata.py index 2001d23d7..40a8c0c45 100755 --- a/selfdrive/modeld/get_model_metadata.py +++ b/selfdrive/modeld/get_model_metadata.py @@ -1,11 +1,12 @@ #!/usr/bin/env python3 -import sys -import pathlib -import onnx import codecs import pickle +import pathlib +import sys from typing import Any +import onnx + def get_name_and_shape(value_info:onnx.ValueInfoProto) -> tuple[str, tuple[int,...]]: shape = tuple([int(dim.dim_value) for dim in value_info.type.tensor_type.shape.dim]) name = value_info.name @@ -17,19 +18,23 @@ def get_metadata_value_by_name(model:onnx.ModelProto, name:str) -> str | Any: return prop.value return None -if __name__ == "__main__": - model_path = pathlib.Path(sys.argv[1]) + +def make_metadata_dict(model_path: str | pathlib.Path) -> dict[str, Any]: model = onnx.load(str(model_path)) output_slices = get_metadata_value_by_name(model, 'output_slices') assert output_slices is not None, 'output_slices not found in metadata' - metadata = { + return { 'model_checkpoint': get_metadata_value_by_name(model, 'model_checkpoint'), 'output_slices': pickle.loads(codecs.decode(output_slices.encode(), "base64")), 'input_shapes': dict([get_name_and_shape(x) for x in model.graph.input]), - 'output_shapes': dict([get_name_and_shape(x) for x in model.graph.output]) + 'output_shapes': dict([get_name_and_shape(x) for x in model.graph.output]), } +if __name__ == "__main__": + model_path = pathlib.Path(sys.argv[1]) + metadata = make_metadata_dict(model_path) + metadata_path = model_path.parent / (model_path.stem + '_metadata.pkl') with open(metadata_path, 'wb') as f: pickle.dump(metadata, f) diff --git a/selfdrive/modeld/modeld.py b/selfdrive/modeld/modeld.py index 08164e86d..ed3b101ff 100755 --- a/selfdrive/modeld/modeld.py +++ b/selfdrive/modeld/modeld.py @@ -28,6 +28,11 @@ from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_pose_ from openpilot.selfdrive.modeld.constants import ModelConstants, Plan from openpilot.selfdrive.modeld.models.commonmodel_pyx import DrivingModelFrame, CLContext from openpilot.selfdrive.modeld.runners.tinygrad_helpers import qcom_tensor_from_opencl_address +from openpilot.starpilot.common.model_versions import ( + is_tinygrad_model_version, + uses_combined_driving_artifacts, + uses_split_off_policy_artifacts, +) from openpilot.starpilot.common.starpilot_variables import get_starpilot_toggles, MODELS_PATH, params_memory @@ -309,7 +314,7 @@ class ModelState: self.is_v14 = (self.policy_generation == "v14") self.is_v15 = (self.policy_generation == "v15") self.is_v9 = (self.policy_generation == "v9") - self.mlsim = (self.policy_generation in ("v8", "v10", "v11", "v12", "v13", "v14", "v15")) + self.mlsim = is_tinygrad_model_version(self.policy_generation) self.policy_has_plan = 'plan' in self.policy_output_slices self.frames = {name: DrivingModelFrame(context, ModelConstants.TEMPORAL_SKIP) for name in self.vision_input_names} @@ -334,7 +339,7 @@ class ModelState: self.off_policy_output: np.ndarray | None = None off_policy_metadata = None - if self.policy_generation in ("v12", "v13", "v14", "v15") or OFF_POLICY_METADATA_PATH.is_file() or OFF_POLICY_PKL_PATH.is_file(): + if uses_split_off_policy_artifacts(self.policy_generation) or OFF_POLICY_METADATA_PATH.is_file() or OFF_POLICY_PKL_PATH.is_file(): resolved_off_policy_meta = ensure_artifact(OFF_POLICY_METADATA_PATH, "driving_off_policy_metadata.pkl", optional=True) if resolved_off_policy_meta is not None: with open(resolved_off_policy_meta, 'rb') as f: @@ -453,14 +458,14 @@ class ModelState: self.full_prev_desired_curv[0,-1,:] = policy_outputs_dict['desired_curvature'][0, :] if self.prev_desired_curv_key is not None: - # v9/v10/v11/v12/v13/v14/v15 models expect zeros for prev_desired_curv(s); others use history - if self.is_v9 or self.is_v10 or self.is_v11 or self.is_v12 or self.is_v13 or self.is_v14 or self.is_v15: + # Tinygrad-era policy models expect zeros for prev_desired_curv(s); older ones use history. + if is_tinygrad_model_version(self.policy_generation): self.numpy_inputs[self.prev_desired_curv_key][:] = 0 * self.full_prev_desired_curv[0, self.temporal_idxs] else: self.numpy_inputs[self.prev_desired_curv_key][:] = self.full_prev_desired_curv[0, self.temporal_idxs] if self.off_policy_enabled and self.off_policy_prev_desired_curv_key is not None: - if self.is_v9 or self.is_v12 or self.is_v13 or self.is_v14 or self.is_v15: + if self.is_v9 or uses_split_off_policy_artifacts(self.policy_generation) or uses_combined_driving_artifacts(self.policy_generation): self.off_policy_numpy_inputs[self.off_policy_prev_desired_curv_key][:] = 0 * self.full_prev_desired_curv[0, self.temporal_idxs] else: self.off_policy_numpy_inputs[self.off_policy_prev_desired_curv_key][:] = self.full_prev_desired_curv[0, self.temporal_idxs] @@ -486,6 +491,13 @@ class ModelState: def main(demo=False): + params = Params() + selected_version = _resolve_mirrored_param(params, "ModelVersion", "DrivingModelVersion") + if uses_combined_driving_artifacts(selected_version): + from openpilot.selfdrive.modeld.modeld_v16 import main as combined_main + + return combined_main(demo=demo) + cloudlog.warning("modeld init") sentry.set_tag("daemon", PROCESS_NAME) @@ -527,8 +539,6 @@ def main(demo=False): sm = SubMaster(["deviceState", "carState", "roadCameraState", "liveCalibration", "driverMonitoringState", "carControl", "liveDelay", "starpilotPlan"]) publish_state = PublishState() - params = Params() - # setup filter to track dropped frames frame_dropped_filter = FirstOrderFilter(0., 10., 1. / ModelConstants.MODEL_FREQ) frame_id = 0 diff --git a/selfdrive/modeld/modeld_v16.py b/selfdrive/modeld/modeld_v16.py new file mode 100644 index 000000000..20177f65b --- /dev/null +++ b/selfdrive/modeld/modeld_v16.py @@ -0,0 +1,447 @@ +#!/usr/bin/env python3 +from __future__ import annotations + +import os +import pickle +import time +from pathlib import Path + +from openpilot.system.hardware import TICI + +os.environ["DEV"] = "QCOM" if TICI else "LLVM" + +import cereal.messaging as messaging +import numpy as np +from cereal import car, log +from msgq.visionipc import VisionBuf, VisionIpcClient, VisionStreamType +from opendbc.car.car_helpers import get_demo_car_params +from setproctitle import setproctitle +from tinygrad.device import Device +from tinygrad.tensor import Tensor + +from openpilot.common.file_chunker import read_file_chunked +from openpilot.common.filter_simple import FirstOrderFilter +from openpilot.common.params import Params +from openpilot.common.realtime import DT_MDL, config_realtime_process +from openpilot.common.swaglog import cloudlog +from openpilot.common.transformations.camera import DEVICE_CAMERAS +from openpilot.common.transformations.model import get_warp_matrix +from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper +from openpilot.selfdrive.controls.lib.drive_helpers import smooth_value +from openpilot.selfdrive.modeld.compile_modeld import POLICY_INPUTS, WARP_INPUTS, make_input_queues +from openpilot.selfdrive.modeld.constants import ModelConstants +from openpilot.selfdrive.modeld.fill_model_msg import PublishState, fill_model_msg, fill_pose_msg +from openpilot.selfdrive.modeld.parse_model_outputs import Parser +from openpilot.starpilot.assets.model_manager import ModelManager +from openpilot.starpilot.common.model_versions import uses_combined_driving_artifacts +from openpilot.starpilot.common.starpilot_variables import MODELS_PATH, get_starpilot_toggles, params_memory +from openpilot.system import sentry +from openpilot.system.camerad.cameras.nv12_info import get_nv12_info + + +PROCESS_NAME = "selfdrive.modeld.modeld" +SEND_RAW_PRED = os.getenv("SEND_RAW_PRED") + +BUILTIN_MODEL_KEY = "sc2" +BUILTIN_MODEL_ALIASES = {BUILTIN_MODEL_KEY, "sc"} + +LAT_SMOOTH_SECONDS = 0.0 +LONG_SMOOTH_SECONDS = 0.3 +MIN_LAT_CONTROL_SPEED = 0.3 + + +def _get_param_str(params: Params, key: str, default: str = "") -> str: + try: + value = params.get(key) + except Exception: + return default + if value is None: + return default + if isinstance(value, bytes): + try: + return value.decode("utf-8") + except Exception: + return default + if isinstance(value, (dict, list)): + return default + return str(value) + + +def _get_default_param_str(params: Params, key: str) -> str: + try: + value = params.get_default_value(key) + except Exception: + return "" + if value is None: + return "" + if isinstance(value, bytes): + try: + return value.decode("utf-8") + except Exception: + return "" + return str(value) + + +def _resolve_mirrored_param(params: Params, primary_key: str, secondary_key: str) -> str: + primary_val = _get_param_str(params, primary_key).strip() + secondary_val = _get_param_str(params, secondary_key).strip() + if primary_val == secondary_val: + return secondary_val or primary_val + + primary_default = _get_default_param_str(params, primary_key).strip() + secondary_default = _get_default_param_str(params, secondary_key).strip() + primary_non_default = bool(primary_val) and primary_val != primary_default + secondary_non_default = bool(secondary_val) and secondary_val != secondary_default + + if secondary_non_default: + return secondary_val + if primary_non_default: + return primary_val + return secondary_val or primary_val + + +def _canonical_model_id(model_id: str) -> str: + key = (model_id or "").strip().lower() + return BUILTIN_MODEL_KEY if key in BUILTIN_MODEL_ALIASES else key + + +def _combined_model_path(model_id: str, use_builtin_model: bool) -> Path: + if use_builtin_model: + return Path(__file__).parent / "models" / "driving_tinygrad.pkl" + return MODELS_PATH / f"{model_id}_driving_tinygrad.pkl" + + +def get_action_from_model(model_output: dict[str, np.ndarray], prev_action: log.ModelDataV2.Action, v_ego: float) -> log.ModelDataV2.Action: + desired_curv_unscaled, desired_accel = model_output["action"][0] + desired_curvature = float(desired_curv_unscaled) / max(1.0, v_ego) ** 2 + should_stop = (v_ego < 0.3 and desired_accel < 0.1) + + desired_accel = smooth_value(float(desired_accel), prev_action.desiredAcceleration, LONG_SMOOTH_SECONDS) + if v_ego > MIN_LAT_CONTROL_SPEED: + desired_curvature = smooth_value(desired_curvature, prev_action.desiredCurvature, LAT_SMOOTH_SECONDS) + else: + desired_curvature = prev_action.desiredCurvature + + return log.ModelDataV2.Action( + desiredCurvature=float(desired_curvature), + desiredAcceleration=float(desired_accel), + shouldStop=bool(should_stop), + ) + + +class FrameMeta: + frame_id: int = 0 + timestamp_sof: int = 0 + timestamp_eof: int = 0 + + def __init__(self, vipc=None): + if vipc is not None: + self.frame_id, self.timestamp_sof, self.timestamp_eof = vipc.frame_id, vipc.timestamp_sof, vipc.timestamp_eof + + +class ModelState: + prev_desire: np.ndarray + + def __init__(self, cam_w: int, cam_h: int): + params = Params() + model_id_raw = _resolve_mirrored_param(params, "Model", "DrivingModel") or BUILTIN_MODEL_KEY + self.model_id = _canonical_model_id(model_id_raw) + self.model_version = _resolve_mirrored_param(params, "ModelVersion", "DrivingModelVersion") + if not uses_combined_driving_artifacts(self.model_version): + raise ValueError(f"Combined runtime requested for non-combined version {self.model_version!r}") + + use_builtin_model = self.model_id == BUILTIN_MODEL_KEY + model_path = _combined_model_path(self.model_id, use_builtin_model) + if not model_path.is_file(): + if use_builtin_model: + raise FileNotFoundError( + f"Missing builtin combined model artifact: {model_path}. " + "Rebuild/deploy the combined builtin model before selecting this version." + ) + + cloudlog.error(f"Missing combined model artifact {model_path}, downloading {self.model_id}...") + ModelManager(params, params_memory).download_model(self.model_id) + if not model_path.is_file(): + raise FileNotFoundError(model_path) + + jits = pickle.loads(read_file_chunked(model_path)) + + vision_metadata = jits["metadata"]["vision"] + off_policy_metadata = jits["metadata"]["off_policy"] + on_policy_metadata = jits["metadata"]["on_policy"] + + self.vision_input_shapes = vision_metadata["input_shapes"] + self.vision_input_names = list(self.vision_input_shapes.keys()) + self.vision_output_slices = vision_metadata["output_slices"] + self.off_policy_output_slices = off_policy_metadata["output_slices"] + self.policy_input_shapes = on_policy_metadata["input_shapes"] + self.policy_output_slices = on_policy_metadata["output_slices"] + self.desire_key = next(key for key in self.policy_input_shapes if key.startswith("desire")) + + self.frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ + self.dev = Device.DEFAULT + self.input_queues, self.npy = make_input_queues(self.vision_input_shapes, self.policy_input_shapes, self.frame_skip, device=self.dev) + self.full_frames: dict[str, Tensor] = {} + self._blob_cache: dict[tuple[str, int], Tensor] = {} + self.parser = Parser() + self.frame_buf_params = {key: get_nv12_info(cam_w, cam_h) for key in ("img", "big_img")} + self.prev_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32) + + camera_jit = jits[(cam_w, cam_h)] + self.split_warp_layout = "run_policy" in jits and not isinstance(camera_jit, dict) + if self.split_warp_layout: + self.run_policy = jits["run_policy"] + self.warp_enqueue = camera_jit + else: + self.run_policy = camera_jit["run_policy"] + self.warp_enqueue = camera_jit["warp_enqueue"] + + def slice_outputs(self, model_outputs: np.ndarray, output_slices: dict[str, slice]) -> dict[str, np.ndarray]: + return {key: model_outputs[np.newaxis, value] for key, value in output_slices.items()} + + def run(self, bufs: dict[str, VisionBuf], transforms: dict[str, np.ndarray], inputs: dict[str, np.ndarray], prepare_only: bool) -> dict[str, np.ndarray] | None: + for key in bufs.keys(): + ptr = np.frombuffer(bufs[key].data, dtype=np.uint8).ctypes.data + yuv_size = self.frame_buf_params[key][3] + cache_key = (key, ptr) + if cache_key not in self._blob_cache: + self._blob_cache[cache_key] = Tensor.from_blob(ptr, (yuv_size,), dtype="uint8", device=self.dev) + self.full_frames[key] = self._blob_cache[cache_key] + + inputs[self.desire_key][0] = 0 + self.npy["desire"][:] = np.where(inputs[self.desire_key] - self.prev_desire > 0.99, inputs[self.desire_key], 0) + self.prev_desire[:] = inputs[self.desire_key] + self.npy["traffic_convention"][:] = inputs["traffic_convention"] + if "action_t" in self.npy: + self.npy["action_t"][:] = inputs["action_t"] + self.npy["tfm"][:, :] = transforms["img"][:, :] + self.npy["big_tfm"][:, :] = transforms["big_img"][:, :] + + if self.split_warp_layout: + img, big_img = self.warp_enqueue( + **{key: self.input_queues[key] for key in WARP_INPUTS}, + frame=self.full_frames["img"], + big_frame=self.full_frames["big_img"], + ) + if prepare_only: + return None + policy_inputs = {key: self.input_queues[key] for key in POLICY_INPUTS if key in self.input_queues} + vision_output, policy_output, off_policy_output = self.run_policy(**policy_inputs, img=img, big_img=big_img) + else: + if prepare_only: + self.warp_enqueue(**self.input_queues, frame=self.full_frames["img"], big_frame=self.full_frames["big_img"]) + return None + vision_output, policy_output, off_policy_output = self.run_policy( + **self.input_queues, + frame=self.full_frames["img"], + big_frame=self.full_frames["big_img"], + ) + + vision_output = vision_output.numpy().flatten() + policy_output = policy_output.numpy().flatten() + off_policy_output = off_policy_output.numpy().flatten() + + vision_outputs_dict = self.parser.parse_vision_outputs(self.slice_outputs(vision_output, self.vision_output_slices)) + off_policy_outputs_dict = self.parser.parse_policy_outputs(self.slice_outputs(off_policy_output, self.off_policy_output_slices)) + policy_outputs_dict = self.parser.parse_policy_outputs(self.slice_outputs(policy_output, self.policy_output_slices)) + combined_outputs_dict = {**vision_outputs_dict, **off_policy_outputs_dict, **policy_outputs_dict} + + if SEND_RAW_PRED: + combined_outputs_dict["raw_pred"] = np.concatenate([vision_output.copy(), policy_output.copy(), off_policy_output.copy()]) + return combined_outputs_dict + + +def main(demo=False): + cloudlog.warning("modeld init") + + sentry.set_tag("daemon", PROCESS_NAME) + cloudlog.bind(daemon=PROCESS_NAME) + setproctitle(PROCESS_NAME) + config_realtime_process(7, 54) + + while True: + available_streams = VisionIpcClient.available_streams("camerad", block=False) + if available_streams: + use_extra_client = VisionStreamType.VISION_STREAM_WIDE_ROAD in available_streams and VisionStreamType.VISION_STREAM_ROAD in available_streams + main_wide_camera = VisionStreamType.VISION_STREAM_ROAD not in available_streams + break + time.sleep(0.1) + + vipc_client_main_stream = VisionStreamType.VISION_STREAM_WIDE_ROAD if main_wide_camera else VisionStreamType.VISION_STREAM_ROAD + vipc_client_main = VisionIpcClient("camerad", vipc_client_main_stream, True) + vipc_client_extra = VisionIpcClient("camerad", VisionStreamType.VISION_STREAM_WIDE_ROAD, False) + cloudlog.warning(f"vision stream set up, main_wide_camera: {main_wide_camera}, use_extra_client: {use_extra_client}") + + while not vipc_client_main.connect(False): + time.sleep(0.1) + while use_extra_client and not vipc_client_extra.connect(False): + time.sleep(0.1) + + cloudlog.warning(f"connected main cam with buffer size: {vipc_client_main.buffer_len} ({vipc_client_main.width} x {vipc_client_main.height})") + if use_extra_client: + cloudlog.warning(f"connected extra cam with buffer size: {vipc_client_extra.buffer_len} ({vipc_client_extra.width} x {vipc_client_extra.height})") + + start_time = time.monotonic() + cloudlog.warning("loading combined model") + model = ModelState(vipc_client_main.width, vipc_client_main.height) + cloudlog.warning(f"combined model loaded in {time.monotonic() - start_time:.1f}s, modeld starting") + + pm = messaging.PubMaster(["modelV2", "drivingModelData", "cameraOdometry", "starpilotModelV2"]) + sm = messaging.SubMaster(["deviceState", "carState", "roadCameraState", "liveCalibration", "driverMonitoringState", "carControl", "liveDelay", "starpilotPlan"]) + + publish_state = PublishState() + params = Params() + + frame_dropped_filter = FirstOrderFilter(0.0, 10.0, 1.0 / ModelConstants.MODEL_RUN_FREQ) + last_vipc_frame_id = 0 + run_count = 0 + + model_transform_main = np.zeros((3, 3), dtype=np.float32) + model_transform_extra = np.zeros((3, 3), dtype=np.float32) + live_calib_seen = False + buf_main, buf_extra = None, None + meta_main = FrameMeta() + meta_extra = FrameMeta() + + if demo: + CP = get_demo_car_params() + else: + CP = messaging.log_from_bytes(params.get("CarParams", block=True), car.CarParams) + cloudlog.info("modeld got CarParams: %s", CP.brand) + + long_delay = CP.longitudinalActuatorDelay + LONG_SMOOTH_SECONDS + prev_action = log.ModelDataV2.Action() + desire_helper = DesireHelper() + starpilot_toggles = get_starpilot_toggles(sm) + + while True: + while meta_main.timestamp_sof < meta_extra.timestamp_sof + 25000000: + buf_main = vipc_client_main.recv() + meta_main = FrameMeta(vipc_client_main) + if buf_main is None: + break + + if buf_main is None: + cloudlog.debug("vipc_client_main no frame") + continue + + if use_extra_client: + while True: + buf_extra = vipc_client_extra.recv() + meta_extra = FrameMeta(vipc_client_extra) + if buf_extra is None or meta_main.timestamp_sof < meta_extra.timestamp_sof + 25000000: + break + + if buf_extra is None: + cloudlog.debug("vipc_client_extra no frame") + continue + + if abs(meta_main.timestamp_sof - meta_extra.timestamp_sof) > 10000000: + cloudlog.error( + f"frames out of sync! main: {meta_main.frame_id} ({meta_main.timestamp_sof / 1e9:.5f}), " + f"extra: {meta_extra.frame_id} ({meta_extra.timestamp_sof / 1e9:.5f})" + ) + else: + buf_extra = buf_main + meta_extra = meta_main + + sm.update(0) + desire = desire_helper.desire + is_rhd = sm["driverMonitoringState"].isRHD + frame_id = sm["roadCameraState"].frameId + v_ego = max(sm["carState"].vEgo, 0.0) + lat_delay = sm["liveDelay"].lateralDelay + LAT_SMOOTH_SECONDS + + if sm.updated["liveCalibration"] and sm.seen["roadCameraState"] and sm.seen["deviceState"]: + device_from_calib_euler = np.array(sm["liveCalibration"].rpyCalib, dtype=np.float32) + dc = DEVICE_CAMERAS[(str(sm["deviceState"].deviceType), str(sm["roadCameraState"].sensor))] + model_transform_main = get_warp_matrix( + device_from_calib_euler, + dc.ecam.intrinsics if main_wide_camera else dc.fcam.intrinsics, + False, + ).astype(np.float32) + model_transform_extra = get_warp_matrix(device_from_calib_euler, dc.ecam.intrinsics, True).astype(np.float32) + live_calib_seen = True + + traffic_convention = np.zeros(2, dtype=np.float32) + traffic_convention[int(is_rhd)] = 1 + + vec_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32) + if 0 <= desire < ModelConstants.DESIRE_LEN: + vec_desire[desire] = 1 + + vipc_dropped_frames = max(0, meta_main.frame_id - last_vipc_frame_id - 1) + frames_dropped = frame_dropped_filter.update(min(vipc_dropped_frames, 10)) + if run_count < 10: + frame_dropped_filter.x = 0.0 + frames_dropped = 0.0 + run_count += 1 + + frame_drop_ratio = frames_dropped / (1 + frames_dropped) + prepare_only = vipc_dropped_frames > 0 + if prepare_only: + cloudlog.error(f"skipping model eval. Dropped {vipc_dropped_frames} frames") + + bufs = {name: buf_extra if "big" in name else buf_main for name in model.vision_input_names} + transforms = {name: model_transform_extra if "big" in name else model_transform_main for name in model.vision_input_names} + + frame_delay = DT_MDL + action_delay = DT_MDL / 2 + lat_action_t = lat_delay + frame_delay + action_delay + long_action_t = long_delay + frame_delay + action_delay + + inputs: dict[str, np.ndarray] = { + model.desire_key: vec_desire, + "traffic_convention": traffic_convention, + } + if "action_t" in model.npy: + inputs["action_t"] = np.array([lat_action_t, long_action_t], dtype=np.float32) + + start = time.perf_counter() + model_output = model.run(bufs, transforms, inputs, prepare_only) + end = time.perf_counter() + model_execution_time = end - start + + if model_output is not None: + modelv2_send = messaging.new_message("modelV2") + starpilot_modelv2_send = messaging.new_message("starpilotModelV2") + drivingdata_send = messaging.new_message("drivingModelData") + posenet_send = messaging.new_message("cameraOdometry") + + action = get_action_from_model(model_output, prev_action, v_ego) + prev_action = action + fill_model_msg( + drivingdata_send, + modelv2_send, + model_output, + action, + publish_state, + meta_main.frame_id, + meta_extra.frame_id, + frame_id, + frame_drop_ratio, + meta_main.timestamp_eof, + model_execution_time, + live_calib_seen, + ) + + desire_state = modelv2_send.modelV2.meta.desireState + l_lane_change_prob = desire_state[log.Desire.laneChangeLeft] + r_lane_change_prob = desire_state[log.Desire.laneChangeRight] + lane_change_prob = l_lane_change_prob + r_lane_change_prob + desire_helper.update(sm["carState"], sm["carControl"].latActive, lane_change_prob, sm["starpilotPlan"], starpilot_toggles) + modelv2_send.modelV2.meta.laneChangeState = desire_helper.lane_change_state + modelv2_send.modelV2.meta.laneChangeDirection = desire_helper.lane_change_direction + starpilot_modelv2_send.starpilotModelV2.turnDirection = desire_helper.turn_direction + drivingdata_send.drivingModelData.meta.laneChangeState = desire_helper.lane_change_state + drivingdata_send.drivingModelData.meta.laneChangeDirection = desire_helper.lane_change_direction + + fill_pose_msg(posenet_send, model_output, meta_main.frame_id, vipc_dropped_frames, meta_main.timestamp_eof, live_calib_seen) + pm.send("modelV2", modelv2_send) + pm.send("starpilotModelV2", starpilot_modelv2_send) + pm.send("drivingModelData", drivingdata_send) + pm.send("cameraOdometry", posenet_send) + + last_vipc_frame_id = meta_main.frame_id + if sm.updated["starpilotPlan"]: + starpilot_toggles = get_starpilot_toggles(sm) diff --git a/selfdrive/ui/layouts/settings/starpilot/driving_model.py b/selfdrive/ui/layouts/settings/starpilot/driving_model.py index 60e0e4cc6..76cbdcf5c 100644 --- a/selfdrive/ui/layouts/settings/starpilot/driving_model.py +++ b/selfdrive/ui/layouts/settings/starpilot/driving_model.py @@ -17,11 +17,15 @@ from openpilot.starpilot.assets.model_manager import ( MODEL_DOWNLOAD_ALL_PARAM, MODEL_DOWNLOAD_PARAM, ModelManager, - TINYGRAD_VERSIONS, canonical_model_key, is_builtin_model_key, model_key_aliases, ) +from openpilot.starpilot.common.model_versions import ( + is_tinygrad_model_version, + uses_combined_driving_artifacts, + uses_split_off_policy_artifacts, +) from openpilot.starpilot.common.starpilot_variables import MODELS_PATH, update_starpilot_toggles from openpilot.system.ui.lib.application import FontWeight, MouseEvent, MousePos, gui_app from openpilot.system.ui.lib.multilang import tr @@ -674,7 +678,7 @@ class StarPilotDrivingModelLayout(_SettingsPage): if f"{model_key}.thneed" in files: return True - if version in TINYGRAD_VERSIONS: + if is_tinygrad_model_version(version): required_files = set(self._required_files_for_version(model_key, version)) return required_files.issubset(files) @@ -684,6 +688,9 @@ class StarPilotDrivingModelLayout(_SettingsPage): return any(file.startswith(f"{model_key}.") or file.startswith(f"{model_key}_") for file in files) def _required_files_for_version(self, key: str, version: str) -> list[str]: + if uses_combined_driving_artifacts(version): + return [f"{key}_driving_tinygrad.pkl"] + files = [ f"{key}_driving_policy_tinygrad.pkl", f"{key}_driving_vision_tinygrad.pkl", @@ -691,7 +698,7 @@ class StarPilotDrivingModelLayout(_SettingsPage): f"{key}_driving_vision_metadata.pkl", ] - if version in {"v12", "v13", "v14", "v15"}: + if uses_split_off_policy_artifacts(version): files.extend( [ f"{key}_driving_off_policy_tinygrad.pkl", diff --git a/selfdrive/ui/mici/layouts/settings/driving_model.py b/selfdrive/ui/mici/layouts/settings/driving_model.py index 1cd018a9a..bbad92b8f 100644 --- a/selfdrive/ui/mici/layouts/settings/driving_model.py +++ b/selfdrive/ui/mici/layouts/settings/driving_model.py @@ -11,7 +11,11 @@ from openpilot.starpilot.assets.model_manager import ( CANCEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, ModelManager, - TINYGRAD_VERSIONS, +) +from openpilot.starpilot.common.model_versions import ( + is_tinygrad_model_version, + uses_combined_driving_artifacts, + uses_split_off_policy_artifacts, ) from openpilot.starpilot.common.starpilot_variables import MODELS_PATH from openpilot.selfdrive.ui.mici.widgets.button import BigButton @@ -715,9 +719,12 @@ class DrivingModelBigButton(BigButton): return False def _required_files_for_version(self, key: str, version: str) -> list[str]: - if version not in TINYGRAD_VERSIONS: + if not is_tinygrad_model_version(version): return [] + if uses_combined_driving_artifacts(version): + return [f"{key}_driving_tinygrad.pkl"] + files = [ f"{key}_driving_policy_tinygrad.pkl", f"{key}_driving_vision_tinygrad.pkl", @@ -725,7 +732,7 @@ class DrivingModelBigButton(BigButton): f"{key}_driving_vision_metadata.pkl", ] - if version in {"v12", "v13", "v14", "v15"}: + if uses_split_off_policy_artifacts(version): files.extend([ f"{key}_driving_off_policy_tinygrad.pkl", f"{key}_driving_off_policy_metadata.pkl", diff --git a/starpilot/assets/download_functions.py b/starpilot/assets/download_functions.py index 47f9dd1e6..1776a7bcc 100644 --- a/starpilot/assets/download_functions.py +++ b/starpilot/assets/download_functions.py @@ -83,7 +83,7 @@ def download_file(cancel_param, destination, progress_param, url, download_param def get_remote_file_size(url, suppress_errors=False): try: - response = requests.head(url, headers={"Accept-Encoding": "identity"}, timeout=10) + response = requests.head(url, headers={"Accept-Encoding": "identity"}, timeout=10, allow_redirects=True) response.raise_for_status() return int(response.headers.get("Content-Length", 0)) except Exception as error: diff --git a/starpilot/assets/model_manager.py b/starpilot/assets/model_manager.py index a784b7ae3..e2fc3944b 100644 --- a/starpilot/assets/model_manager.py +++ b/starpilot/assets/model_manager.py @@ -14,12 +14,18 @@ from openpilot.starpilot.assets.download_functions import ( handle_request_error, verify_download, ) +from openpilot.starpilot.common.model_versions import ( + is_tinygrad_model_version, + uses_combined_driving_artifacts, + uses_split_off_policy_artifacts, +) from openpilot.starpilot.common.starpilot_utilities import delete_file from openpilot.starpilot.common.starpilot_variables import MODELS_PATH MANIFEST_CANDIDATES = ("v21",) -TINYGRAD_VERSIONS = {"v8", "v9", "v10", "v11", "v12", "v13", "v14", "v15"} +TINYGRAD_VERSIONS = {f"v{i}" for i in range(8, 33)} DEFAULT_MODEL_KEY = "sc2" +ARTIFACT_URLS_CACHE = ".model_artifact_urls.json" MODEL_KEY_CANONICAL_MAP = { "sc": DEFAULT_MODEL_KEY, } @@ -130,6 +136,13 @@ class ModelManager: self.model_series = [entry for entry in self._param_text("AvailableModelSeries").split(",") if entry] self.available_model_names = [entry for entry in self._param_text("AvailableModelNames").split(",") if entry] + @staticmethod + def _manifest_paths(manifest_version: str) -> tuple[str, ...]: + return ( + f"Versions/model_names_{manifest_version}.json", + f"model_names_{manifest_version}.json", + ) + def _set_model_param_keys(self, model_key: str | None = None, model_name: str | None = None, model_version: str | None = None): if model_key is not None and model_key != "": canonical_key = self._canonical_model_key(model_key) @@ -182,9 +195,12 @@ class ModelManager: return DEFAULT_MODEL_KEY def _required_files(self, model_key: str, model_version: str) -> list[str]: - if model_version not in TINYGRAD_VERSIONS: + if not is_tinygrad_model_version(model_version): return [] + if uses_combined_driving_artifacts(model_version): + return [f"{model_key}_driving_tinygrad.pkl"] + filenames = [ f"{model_key}_driving_policy_tinygrad.pkl", f"{model_key}_driving_vision_tinygrad.pkl", @@ -192,7 +208,7 @@ class ModelManager: f"{model_key}_driving_vision_metadata.pkl", ] - if model_version in {"v12", "v13", "v14", "v15"}: + if uses_split_off_policy_artifacts(model_version): filenames += [ f"{model_key}_driving_off_policy_tinygrad.pkl", f"{model_key}_driving_off_policy_metadata.pkl", @@ -200,6 +216,72 @@ class ModelManager: return filenames + @staticmethod + def _artifact_urls_cache_path() -> Path: + return MODELS_PATH / ARTIFACT_URLS_CACHE + + def _load_artifact_url_map(self) -> dict[str, dict[str, str]]: + try: + cache_path = self._artifact_urls_cache_path() + if not cache_path.is_file(): + return {} + + payload = json.loads(cache_path.read_text()) + if not isinstance(payload, dict): + return {} + + normalized: dict[str, dict[str, str]] = {} + for model_key, urls in payload.items(): + if not isinstance(urls, dict): + continue + normalized[str(model_key)] = { + str(filename): str(url) + for filename, url in urls.items() + if filename and url + } + return normalized + except Exception as error: + print(f"Failed to load artifact URL cache: {error}") + return {} + + def _build_artifact_url_map(self, model_info: list[dict]) -> dict[str, dict[str, str]]: + artifact_url_map: dict[str, dict[str, str]] = {} + + for model in model_info: + model_key = self._canonical_model_key(str(model.get("id") or "").strip()) + model_version = str(model.get("version") or "").strip() + required_files = self._required_files(model_key, model_version) + if not model_key or not required_files: + continue + + urls: dict[str, str] = {} + + explicit_urls = model.get("artifact_urls") or model.get("download_urls") + if isinstance(explicit_urls, dict): + for filename, url in explicit_urls.items(): + if filename and url: + urls[str(filename).strip()] = str(url).strip() + + base_url = str(model.get("artifact_base_url") or model.get("download_base_url") or "").strip() + if base_url: + base_url = base_url.rstrip("/") + for filename in required_files: + urls.setdefault(filename, f"{base_url}/{filename}") + + direct_url = str(model.get("artifact_url") or model.get("download_url") or "").strip() + if direct_url: + if len(required_files) == 1: + urls.setdefault(required_files[0], direct_url) + else: + matched_filename = next((filename for filename in required_files if Path(filename).name == Path(direct_url).name), None) + if matched_filename is not None: + urls.setdefault(matched_filename, direct_url) + + if urls: + artifact_url_map[model_key] = urls + + return artifact_url_map + def _is_model_downloaded(self, model_key: str, model_version: str) -> bool: if is_builtin_model_key(model_key): return True @@ -296,16 +378,17 @@ class ModelManager: def _get_manifest(self, repo_url: str) -> tuple[str | None, list[dict]]: for manifest_version in MANIFEST_CANDIDATES: - model_info = self._fetch_manifest(f"{repo_url}/Versions/model_names_{manifest_version}.json") - if not model_info: - continue + for manifest_path in self._manifest_paths(manifest_version): + model_info = self._fetch_manifest(f"{repo_url}/{manifest_path}") + if not model_info: + continue - # Desktop/dev build is tinygrad-only. - filtered = [model for model in model_info if model.get("version") in TINYGRAD_VERSIONS] - if not filtered: - continue + # Desktop/dev build is tinygrad-only. + filtered = [model for model in model_info if is_tinygrad_model_version(model.get("version"))] + if not filtered: + continue - return manifest_version, filtered + return manifest_version, filtered return None, [] @@ -366,6 +449,9 @@ class ModelManager: versions_file = MODELS_PATH / ".model_versions.json" versions_file.parent.mkdir(parents=True, exist_ok=True) versions_file.write_text(json.dumps(version_map)) + + artifact_urls_file = self._artifact_urls_cache_path() + artifact_urls_file.write_text(json.dumps(self._build_artifact_url_map(model_info))) except Exception as error: print(f"Failed to write model versions cache: {error}") @@ -411,6 +497,8 @@ class ModelManager: self._load_catalog_from_params() version_map = self._model_version_map() model_version = version_map.get(model_to_download) + model_artifact_urls = self._load_artifact_url_map() + artifact_urls = model_artifact_urls.get(self._canonical_model_key(model_to_download)) or model_artifact_urls.get(model_to_download) or {} required_files = self._required_files(model_to_download, model_version or "") if not required_files: handle_error(None, f"Unsupported model format for {model_to_download}", "Model download failed", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, self.params_memory) @@ -419,25 +507,40 @@ class ModelManager: for filename in required_files: file_path = MODELS_PATH / filename + candidate_urls: list[tuple[str, bool]] = [] + + custom_url = artifact_urls.get(filename, "").strip() + if custom_url: + candidate_urls.append((custom_url, True)) + file_url = f"{repo_url}/Models/{filename}" - - download_file(CANCEL_DOWNLOAD_PARAM, file_path, DOWNLOAD_PROGRESS_PARAM, file_url, MODEL_DOWNLOAD_PARAM, self.params_memory) - if self.params_memory.get_bool(CANCEL_DOWNLOAD_PARAM): - handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, self.params_memory) - self.downloading_model = False - return - - if verify_download(file_path, file_url): - continue + candidate_urls.append((file_url, False)) fallback_url = f"{GITLAB_URL}/Models/{filename}" - download_file(CANCEL_DOWNLOAD_PARAM, file_path, DOWNLOAD_PROGRESS_PARAM, fallback_url, MODEL_DOWNLOAD_PARAM, self.params_memory) - if self.params_memory.get_bool(CANCEL_DOWNLOAD_PARAM): - handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, self.params_memory) - self.downloading_model = False - return + if fallback_url != file_url: + candidate_urls.append((fallback_url, False)) - if not verify_download(file_path, fallback_url): + download_succeeded = False + for candidate_url, allow_unknown_size in candidate_urls: + download_file( + CANCEL_DOWNLOAD_PARAM, + file_path, + DOWNLOAD_PROGRESS_PARAM, + candidate_url, + MODEL_DOWNLOAD_PARAM, + self.params_memory, + allow_unknown_size=allow_unknown_size, + ) + if self.params_memory.get_bool(CANCEL_DOWNLOAD_PARAM): + handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, self.params_memory) + self.downloading_model = False + return + + if verify_download(file_path, candidate_url, allow_unknown_size=allow_unknown_size): + download_succeeded = True + break + + if not download_succeeded: handle_error(file_path, "Verification failed...", f"Verification failed for {filename}", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, self.params_memory) self.downloading_model = False return @@ -489,6 +592,10 @@ class ModelManager: if model_versions_file.is_file(): delete_file(model_versions_file, print_error=False) + artifact_urls_file = self._artifact_urls_cache_path() + if artifact_urls_file.is_file(): + delete_file(artifact_urls_file, print_error=False) + self.params.put_bool("TinygradUpdateAvailable", False) self.params_memory.remove(UPDATE_TINYGRAD_PARAM) self.params_memory.remove(CANCEL_DOWNLOAD_PARAM) diff --git a/starpilot/common/model_versions.py b/starpilot/common/model_versions.py new file mode 100644 index 000000000..042fbccba --- /dev/null +++ b/starpilot/common/model_versions.py @@ -0,0 +1,27 @@ +from __future__ import annotations + + +def parse_model_version(version: str | None) -> int | None: + text = str(version or "").strip().lower() + if not text.startswith("v"): + return None + + raw_number = text[1:] + if not raw_number.isdigit(): + return None + return int(raw_number) + + +def is_tinygrad_model_version(version: str | None) -> bool: + parsed = parse_model_version(version) + return parsed is not None and parsed >= 8 + + +def uses_split_off_policy_artifacts(version: str | None) -> bool: + parsed = parse_model_version(version) + return parsed is not None and 12 <= parsed < 16 + + +def uses_combined_driving_artifacts(version: str | None) -> bool: + parsed = parse_model_version(version) + return parsed is not None and parsed >= 16 diff --git a/starpilot/common/starpilot_variables.py b/starpilot/common/starpilot_variables.py index cab125023..21133cf33 100644 --- a/starpilot/common/starpilot_variables.py +++ b/starpilot/common/starpilot_variables.py @@ -26,6 +26,7 @@ from openpilot.common.constants import CV from openpilot.common.params import Params from openpilot.selfdrive.controls.lib.latcontrol_torque import KP from openpilot.selfdrive.modeld.constants import ModelConstants +from openpilot.starpilot.common.model_versions import is_tinygrad_model_version from openpilot.starpilot.common.accel_profile import ( ACCELERATION_PROFILES, CUSTOM_ACCEL_PROFILE_PARAM_KEYS, @@ -1074,7 +1075,7 @@ class StarPilotVariables: if isinstance(toggle.model_version, bytes): toggle.model_version = toggle.model_version.decode("utf-8", "ignore") toggle.classic_model = toggle.model_version in {"v1", "v2", "v3", "v4"} - toggle.tinygrad_model = toggle.model_version in {"v8", "v9", "v10", "v11", "v12", "v13", "v14", "v15"} + toggle.tinygrad_model = is_tinygrad_model_version(toggle.model_version) toggle.tomb_raider = toggle.model == "space-lab" toggle.model_ui = self.get_value("ModelUI") diff --git a/starpilot/system/the_pond/the_pond.py b/starpilot/system/the_pond/the_pond.py index e4e2564ff..cd2cbd2ff 100644 --- a/starpilot/system/the_pond/the_pond.py +++ b/starpilot/system/the_pond/the_pond.py @@ -60,6 +60,11 @@ from openpilot.starpilot.common.maps_catalog import ( schedule_label, schedule_param_value, ) +from openpilot.starpilot.common.model_versions import ( + is_tinygrad_model_version, + uses_combined_driving_artifacts, + uses_split_off_policy_artifacts, +) from openpilot.starpilot.common.experimental_state import sync_persist_experimental_state from openpilot.starpilot.common.starpilot_utilities import delete_file, get_lock_status, run_cmd from openpilot.starpilot.common.starpilot_variables import ACTIVE_THEME_PATH, ERROR_LOGS_PATH, EXCLUDED_KEYS, LEGACY_STARPILOT_PARAM_RENAMES, MAPS_PATH, MODELS_PATH, RESOURCES_REPO, SCREEN_RECORDINGS_PATH, STOCK_THEME_PATH, THEME_SAVE_PATH,\ @@ -4330,14 +4335,17 @@ def setup(app): if f"{model_key}.thneed" in on_disk_files: return True - if model_version in ("v8", "v9", "v10", "v11", "v12", "v13", "v14", "v15"): + if is_tinygrad_model_version(model_version): + if uses_combined_driving_artifacts(model_version): + return f"{model_key}_driving_tinygrad.pkl" in on_disk_files + required_files = { f"{model_key}_driving_policy_tinygrad.pkl", f"{model_key}_driving_vision_tinygrad.pkl", f"{model_key}_driving_policy_metadata.pkl", f"{model_key}_driving_vision_metadata.pkl", } - if model_version in ("v12", "v13", "v14", "v15"): + if uses_split_off_policy_artifacts(model_version): required_files |= { f"{model_key}_driving_off_policy_tinygrad.pkl", f"{model_key}_driving_off_policy_metadata.pkl", diff --git a/starpilot/ui/qt/offroad/model_settings.cc b/starpilot/ui/qt/offroad/model_settings.cc index d70cd2acd..13eabe06b 100644 --- a/starpilot/ui/qt/offroad/model_settings.cc +++ b/starpilot/ui/qt/offroad/model_settings.cc @@ -615,6 +615,7 @@ bool StarPilotModelPanel::isModelInstalled(const QString &key) const { } bool has_thneed = false; + bool has_combined_tg = false; bool has_policy_meta = false; bool has_policy_tg = false; bool has_vision_meta = false; @@ -635,7 +636,9 @@ bool StarPilotModelPanel::isModelInstalled(const QString &key) const { if (ext == "thneed") { has_thneed = true; } else if (ext == "pkl") { - if (base.contains("_driving_policy_metadata")) { + if (base.contains("_driving_tinygrad")) { + has_combined_tg = true; + } else if (base.contains("_driving_policy_metadata")) { has_policy_meta = true; } else if (base.contains("_driving_policy_tinygrad")) { has_policy_tg = true; @@ -655,6 +658,10 @@ bool StarPilotModelPanel::isModelInstalled(const QString &key) const { return true; } + if (has_combined_tg) { + return true; + } + if (has_policy_meta && has_policy_tg && has_vision_meta && has_vision_tg) { if (has_off_policy_meta || has_off_policy_tg) { return has_off_policy_meta && has_off_policy_tg; diff --git a/uncompiledmodels/driving_off_policy.onnx b/uncompiledmodels/driving_off_policy.onnx index 54c34a0ede7b9e918737d29241b17d440163be7f..9473720d5ef41441ebeeb5df85cb8b780164d448 100644 GIT binary patch delta 13991 zcmb{2dwfsz1IO{l=bZB$`))J$xz5lqx82M=H54L7gvKtiX3~aDDyq3;t~0(k68nZw znGFY@LKwoa-*f!&dPcsVbH3+%&-eTJd@lv*`Q?_(%`cZx z#qHGW{Bm~ZD!+q5>~Umhz9LIs7-Flah6FZt-Rqek^emWwZ`hkyYGK*?jFHI7a7KhCJXL= z1n_3oW<1w4Vz`_3)7YIO0gL#+cUrQ_b<-jHdUT3cvncZ$HR|_j#hRsq@?F zf8Ub#)sfV@r!wBt*xr3sF>mdj>t)xH6NZei>t!MgpP79t8`pYQDbAg8{4~$Qm>Shn z5xe-HI^q}j+;bSGW7~+!M!$zhqwK5`SRd?yG zW*MjF;au!1JQvybo(mpbkIc3r-I$#js)!?nx7zT}TaCmmYAt%uEpnDT=oYO%`0rax zGInJhbQ5d!8A-xd%+Zg#i#uLm^ZAZ{R=ShFVX5cbO9Y*Q@P5 zW8b<>Hj%DhSgHDoUy8et9BvCQKK9gdcDI*fheU@3JB4?OQYmwHvQpoO*|OC9HpOp7 z#;&(Cakl6wwqIXWwO9u>S6nh~=1np)aFH>*V2~z0F52U~;_fj(uW?ee60?nrqmiaZ zFESRMG{0}%*nGCXg?;B=w6gE>S55ERV_bQAiTJpbgp|0KoEe_DbacOQe!lwADSlou zLKVZ@#P*^qdr7e_%GgWlE4MCcue9=Z_gkBe4!&dK&Xqfo6>Qy0B%9y5*eX>Yk**1& z=xUi&ysM>-7A10IxUU#xX5<1n#9t(s8To}i%wO@5^BW30GhDsPvGP!;80q>r9_o#j z<_*YCcZAZ_BIyl+ADlj^&22C z^A)}-iXC!eUvb9jR`TVI0b-UaJ}I1RGw+^k|M~hJuZ%4(_YV?V-NdG%d+&VUy${e! zFA;V0eWR6oR^eCV?&0Eno1Q#cy<;)=&z=6;1`1brAIi<6M1lDYC~0Nn5938cn>bu_ zFzd}6%-`$XKjaJ3#CtZ~f1G0OfU;%pIpP}&8(1$>oqRZ#6h5329`tY)omuxuVBJqo8Bnb&r_x@5tA)X{<2k$co?&Pi?E{EU(eX-7oeYCrP$@6kHi8i zYXEs8SD0A@C}X{4;x6GZvkX`v&*X_@^RuZeUm(m+rz>R0QA>M|JZWL?+49x1BE`b7 zFTQAg?|04Ep|@u2W6OlE^Nrpqn6XP=vod4fwe==NTX$ykNl_Z;SPB$9shk;yur$#3 zE)kwG#!d0Jus+x;KlN7Tnwc~=NiQE|vYCVNL%#2(m zOEytnH#0I%hP6_xEDpxBRm?9AX2{K*l(kl;^__B059Md8TgjKD`YA3h4!(<39?Ih2 zx;*ltvfTXK?yd3@FQA>Mwp0u?0U1u%qeX2ZlQQ2W(a-J&B-LSNQ{qpyc>O3=Z*B1F$X?3cZ zk=b&Tk7{mq=ez%EGS^p~WoE}4q^*u>YKmViTQ^eQFtg7*Ik<^xev02I*R@h7n1287 zkXPEO((2^AOP1`Sp0&D_0@Tw*3JbGVmaLJe9x=ZG z&f^_Mst<7<-}$C$Z64n^QMEFUZv{JI;T(z0?>3`)y)xz|zj4dZ`e5n3vVSdN@YmGX^ z#3ZeZ_m<~3sIyHB71=Urn`&i#e|xuTWqy|jEbM);JYJyUqhga^W@N8BW@+d3Pg&Uc zRN3jAYGry)ml2oMT^7~{`((J)wqXYIswJ zjkK#@C`5@onb%0OGQC#|)2vMIF|D>F zMQPTi_q2G;;`E*~RC|cid(f+zh3VZR=hi0@A;C@bm^u7VaG+Mw8F(!jA7v+v)n=Ms z$>1BQu2c9pyY>ctj`W(Lb-dq?5%@*SU~yCTGqfN*b$GDNc`O;9pg5zUoBVN>wnh`< zi@ren;hrxV7H-y@w|}8g_=~Fz(s#aATN8TGfXn|ipzyn$h4QOK+89+hiw30L`xV`t zySV)gjOSYXJR?31KhJ1tZ>Ar}(t@1lQ?Q1SO+V1SR*S#$t8!_M=BTxa->5hv6RX|N7#z4!yX*0|fq8i8#)kL*WZS)B8M|DtLR1XE9`ltbFh#H~BC=dmqU=)HvQ4q6}STq1Vj|QSR^a6@UgHQq*j9x@T&`T&0C842c7#fa}Q3@J? zUPdF)E9h198XAR0qu0?J=uMQ0#-Ooi92$?_LK9FLnusQ$$!H3iil(7-G#zE28E7VQ zpjl`(nuByS7rl+fDWT0=xg*1`WAhMj-q4eIQky_51l|ipp)nn`VswvPNOsE zXLJ^wL%*Q&=mPo`{e~{0-_alF61t53L|4#NbPZicH_*)~okPWRL=>VDjo64ADM3mS zcVZ_V#FKcDQpB5-CS^!jQjU}-6-Y(mLn@KVqzb7@s*&o%m((DBq$a6FYLiEZKdD3N zl6oY7)F%x{L(+&eCV?b~1d|X_c=%2Dr!dl#G$YMP3(}IbBCW}zqz!qDJWj$%ThflS zCr^+kNe9xAbRtiY&ZG-@nsg=INCfFldXQ&GPtuD#OL~(&q%V1nM3R1_KZzpIB!8A)CtuaeiuC^DM7PTnAI zl2kH=j3wj9c=8sRK+?!WGKowkQ^-^@jii(5B!kQ#Gl_%DBD2XHqLaDgZ8DF%L*|nO zB$GJFyJR6*L>80x$P%)YEFeNrlW)kkthY{ZR}ASH=Au@evCNxVoY;!R4EGNddi zN6M25q$2Sll}Ke$g;XWgNOj^%Y7jqClhh)$$s@#{)FE|AJrY3blLn+AX+#>6KoUfP zNeC%C{3iTU7->qHk>;cYX-Qg<*5pyrhCD_dC*hZgmo(v)hWH5P= Z3?VO(M3O{?l3`>xNme%FUOkdVTNp+vv_(%%un$?et$gfYq#F#-RFHy=lwpNV^jJG z=hLYtoR_*;tzLA(S-)ntM;Vj8WQOt{O{FdLpXT)qyBn`$tF+IhlA6A;NQ=-NuIU?p zYJXU7tLYoXTCBc8VWnzmy6n#O7z%J zzk_I?pIY)h3z6>IYF8Vk%IunXCQ3?j+?5kaiq;R4thBvGEyI4nC9C`y&0%;H0;o~(yq5ouW?ach6g?SKU&yM?Lvp6 zHC{pW!0N@Z1)8hh+8WpP*x*O&+oHYL?F-S_uWO@w`PQ^XOx}s@&`Nt3D(qMD9b5db zJJ!pvGk7qTWWG{O8m`qDxJrKJP`b_#=^tCoW#|gA!R#~5Ep({JHPEjD+o+un3zJx( z=`qXt*JI{o=s&gxyRFS1drM)-hJs7(?5D?;bM(FFN6W!fn>1z8$MUnrVm&m}H%@Tq zd2P&$QG!>Hr}a&w#hf!OCjYU;Xh|bjnWj&^q!==T{7ugt&wMY#{gjZ$7m=oopO-Dy zHpX=EY1-V>rw`GW+Uu?2C&s)T?rSVL94~b?jye)A*%(HJ*3oXSaC!PA7|w;+YV$He zBvy=d7)C}ktiIf<>t3PX@Ak${5<6vDB(Gj1R}e&j#@gCxwBNYbS*PK$363tRZlw>XGs3>1J%)Ea%+Ni-fa*Fx+fowGB5$3(lE$M|94M_l4$^ z?m6@OGCN?!^31;hYioZn-!(n>_79!)HqlWD6BD9h!#f(2PsdB%#-xx0$-(Flogi89 zU5(8`-^M2_siW`7~9N)o3ZyqhT5e$=&fQS5@O$u(brcGHI?i0 z4Xs!|k(;vPd_#M-UTA0*zuTG36dJmjw|QCY+F3Cl`6}*_{ib^)qn3N5SAP~mcixWv zEJxy-ov3{9^-bpEx+MB7w4>vi;kBHZ8TSsE|(QB%WYZ@zvK>tn_CnXg%W z@|xAssq%R2_vVf1Hup+kn{}+%e1ok|xk2?JZ8uacva4Rbu-&6Ok4a?9ESp1mSdR}& zVeNEk?+HrPS!CWntFI70@X4_b;(orH9UZ-2+x2zW3u6o2?}aZovxqZbym!!Vowu_`XKc z0-=%FyqAYGOK9jhb%Cecgr~NaRtSyH0mJZzq)G@ zbK?6VrIr>P5qEf#Dbh9zx66-tlXs*umfZ+v!hj^nf-|936o_$Mj);T=8LMjs9_}Lu3kI9zYpokaR%BzJo$4_|!XL*s(&}{yun=H8TbK3ZK z3C)_z%e`c=J%1bb_K`mjnzfim2FPN2egWq_z3U} z9Tdsx@X4XF;TeAiuw>pdOg?JCj$XkBOptRd+yOW8LDS^#ExQqR^u$@RMLW9Hhq8q` zx_x%lE*Q{>UgqzPmHmv1V-qABm0suD@ZpQ(1(sbl%j2C_%4?qWVxP_9cUQ~bTfW=d zZIb_gyM2J_86^9ty8=C(RNClm_}(3|@p*Rp+x#+@7mB`QmmWCqaR=p zx_P>NEer1Uyyv%qv##NBXXS}PXF@hl`&oF_qN{?l&f(X~E!wwJ`2Blwu>~hX5x2Ke zL^t{{dqs4k&va1)H+u6c{2PrG(O39gTPR|?eGY%8twOKG1^##`<~uqnqPsoos)+9P z0|ONccYE7{|7}OUK3z<20^xaTV_Y1M9f{rvvf=ysDXT0y4A@D&W2izq(o^3NqLW}@ zsAAbkppI26KM7V%R-WS|C{9o;Ithj*Di)puwBZa+Q7nCJpU0Dy;J$tOTRUtye{H4m z`ja0?Ok#KW`E;dHVgH!l8~U;8y&<*yreb{bUfW(iX1&rvVarT!Q{H}JRP`HdEQ7me zE6FljWg1yo|CoR!Y^ht}qK0v)V!?PWqnWJ2m1%6Hiuhf*f61!shAmz)d z4^nX5^VnULR^^lSyP_BaXW?DUe6HjQEV43RbdjGF3NMoF#{|cc#*s7bwMKYR`5EGy4rpvi+GBQ?kicUl=1Hj*bizicb(}|E&Rr|QGJ@}CRRU* z^hLIME4)44(NA6CqHAl6YnUL}s$W!nspFr!>B0r)x?DAvzri!qRgG(!K!e#oc(Tae~y0hqlsju?ZY@+URX!CQgZpm>%BAU$4?f zo^4d`*_xgYZKpdfNtxz5X!c`wkeAxtM;D|f`skV)_9QtkZ(yy)`RVG?Q>)lVXD?fJ zqZK^KPj~Fef2XnHBiAlE%8Ih4>QFY6p0cIvD0|9*s!P?Q94RNtnR21(Qw^wwlq=PU za-$kkO{k`nJJpQxpggJOR12yl^#aw3YE5}jZK$@?i&Q(RJ=KBorhKT5lrPnZ>P-1j z{!{?fh3ZPZM0KNHrn*x-sGd|H)r)$CdX?%;y+-w+`ckh`{iy!b0BRsLh#E`OJaxDv|nt`VW;vB~!Dh52-oSTq=e7h?+;u zrxs8PsYTRcDwSG7Ev1%G%P9l3f?7$XQ7V;At)f;_8PpnTEwzp^QtPQqY6JB#wUOFH zWl`DGW@-zymD)yar*fzr)J|#_wVT>QX;dz?m)b{h>J#cyYCrWEl}8<*@~MN=A*z7- zoH|T>K^0O*s3Pi1s+c-T9izUYj#FP#-%uq~DRqJ>qfS!aQm3fzsMFLL>U-)3>MV7R zI#2ybU7#*fKT$tZm#AN;%hVO>SL!$FD)l>cjk-?Vpl(vPsB-Ey^#}DQb%*+ks-XU+ z?oyT1J?cL7fcl4exX`r=TS5T|$Up%)U5bc2Q5HL@B(NBS_3c82DAk)f_9)i=m5Nd59kPdK_}1| z_yKYFcC}wlR*rK1yjIO z5C^7#=^!2?fVaU6@D6wv%mlN*d*FSL2tEM+0ZAYk%myEVIbbeG0Uv>RU_Mv?7J@}! zF-QeVz*4XbEC&X#0;~jSKn3Yw6<7^2z#6a?tOG`{9%OkdV7<>T=!4Xgdz68bK zC^!bb0>{DE;2Tf^O2G+G22O%+!71<^I1SE#@4*k?EI0?wgCD^Ka1s0jeg>DoFW@q` z0)7R*fvezma1C4sH^5DB3zUP~;1BR8xC8zI72t1h7gU0K;68W&{s9jeZGRGd!GHv0 zpa31P0@k1oumO5t3+#YBZ~%2dJ>UqOfHQCb^+5yB5V(RyzzsA8O+ZuN4w?ZE;0c<8 z7N8|~0ki_Gffr~4+JYBBJJ23<0N%g{bOgSj6X*>5fIkQTru(HUzIq9C122Q_paScmsrjH^EzABp3xo xgD?;d#()Sg7K{UtAPS5J(O?3Y2quBaAO^&ODPSsy1Jl5C5HB61?N71~`7d>~Oo#vg diff --git a/uncompiledmodels/driving_on_policy.onnx b/uncompiledmodels/driving_on_policy.onnx index 49a41d95eabd5707f9915dec0c2f0d226756094e..464613c71c55b3ce50b622622729a9cb94a25259 100644 GIT binary patch delta 12389 zcmb`Nd3+658^=FqW)gCR#2PIksI`bBcB-XXloCo+5sA{+_oen&Dq;z7F(`?(wn)U_ zSVJr&2(gDQXe~u)EUm40f4>|0ilvg7{PF$flVqOr%$YfNo@ZumLQ<&v;*+87)82MI zcs$hI78U1pOo#*aX_}`JE$qc|=U08bE7}t#%@p&D?Mm`%{x{WV>$K}N|GR5k&9>?_ z|2u31+3srMls%}Br`Tv;SiQj0bkV}s?o+>vy?kjudwdNK{1#VXqVUzvFH;7IWyb2< zTUBw@5p^H~QFU7=Vaga+b+MYkkY|&|%KV{s=A$kcHwL!L z%3!%%@j79uA`FX~pDVYvBWfYjvF;n{%ZCss;$tO7`AM@hmIh_`f^+dQaGty5H zXB=B?d3meB*rNENH*FES^i5mTUh&^sgc*s^$DGA_J)*bp6tnd6F5yc#<4uCUB9_ zFQtnnHl<~po6(GA^`e(VEiu!WcDAkQ=taiDOXhRy#`f#&E#y9W$4c(hho*D8j?HJw z7TkG2*8!b-+Vr62UKOXW&ZY+z@X9H%miju2-DyjEX@*v1&|USLr>i@Ek%Q+{G_=Hock$2HAOHCdL$B~}v&X@_@FMh|aUy|=&k5NBs#BN1Xc zJX{+7Vy%<-F>U2-&CtqoTvWX}3RF7BMN#aPTib|hR!2E1A9oZpRI$xbTqDyL*OxEv z!OEC?@=zDC(^Z!cz5@j}wHM@~@0>lf4p!-An_pT3$;Q{ms`=nJ-0{FQlub?^#RP z+g`GeJw^_>E(Tbb`{Fz1v!|=pevWEgMSt83U4Z*PRw{M6aVtB-pV0mGnyUP4VSvqY_H3T(O!WyOTsDhTQml3aN97mGm0jlV-E)k|`|Mm-}3@E}f!G(Wt!EsJka%r*zp@kq-|a}Xol_A6EjWQ`+=`Q`w9XNsll zqt9B(9(Bo5_QdNJvQL(m?1^m`S`vI+apQ)%dltb_I2$nViY8TV>UJjo&9X)KbTrzU8;e2lZ5GwK^xt z>`m0`R!2#ZOi(>_<9{Mcc2-wgs9DjnXfO4Q`2kqT8w^&nxRUQ1 zrCO`xTPLViD)~-%DMFo>$x3dUme1zQJANM@$1T5q9W9&Qd#-AWa^EeKYKKM@^Y6gB%drB-B7KR_;BfePffJY zBOH=#6wPFbU+kipEb(XEH7g~)WI@ejiSJreGgac($pxh}+)ZcpJwkv;mdO<~DI&M?&W96 zoDo{X*L@d(FJij6PIa?6_wU@J^H&3G@97H{Ywzk6?|9{rS7&HDH8C#j{n^Fz?-=lP ztJ3<7wOWwADn@(ZozGrbah~R_2|X?HUWOtaFMC$VTZ^qXhoEB>PuhKDy{o&)Ve== zi5D+RZ_+$e<@>blLtnLhgKe5Ww%505#TCD*_9KM~h929d0Vm)LvVrWt1=v6i;0khr zT)+*ugWMnw$P4m;{Gb5v037oz@HQv}3WFlR6BGqrpcp6)N`QAjNl*%u24z55P!7Bc z%7Y4^BJc*4fDiBmexNd_0;+;)pgO1lYJyszHh2%z0q=tkKwVG|d4IU zfAJ7-{1O34OFc1s^gTXgo2p9^6f#F~T7zsv!5HK2y0b{{9 z@GTe*Lcs(O1}1_@U^18j!ogH94Mc$Hzz$}BnP3*s!E7)G%mv?pd0;+>1W{lCSO^w@ z#b60o3cd%+z;dtxtOTn-G*}H{KrC1T;=o#9fOTL!*Z?Hh2sVMuU<=p^wt;xC9qa%J zU?_rQJd06YZ$ zfJfjlcrxkOHZc`Y3Z+sSe)szueN-lOVJ?^7R8b*XyPhg5y)BkE(S0o9OdM14XvrkYTnQcbC5 zlt0y+YC(NQwWL~6pHr==FQ_)umsDG-9o3!+pgK^2R1npX`ikmAb*8?if~hW4SE?J; zo$5jLqS;EP-+-8oEkxmq()I8)M#o9HI^DjeM^m} zLa7N<7&VcaL`|lqP~p^6Y8n+mO{eVC3~DAdi_)pt)EsIq^&K^jnomViQPcuzA+?BF zOf8|7Qr}a{sO8iOY9+Obil$amF;pzIhKi%sQUjNZfXzp1GSghMJ0TG z^%M0o^$T^DI!B$Sex-h+E>IV#OVnlRcj^jtmAXd#L0zYAP=8XX)J^IZb(^|F{YCvv f-KFkP_o)ZeL+T&u5%rjQB5?Urw&U`r+$i%u$6*p# delta 10057 zcmbuEc~}-zABL}UW&nLb5^>8duu`-Vms~TqTyjNC&9YDob4gRvG%NbR4A)S5m2pRK z!3|1>Jf(=BqT*7LW$v0wmZ`Z^=9b^{@FwOL>KVU3?%RuNe&@_NGw(cSJhNcW*rHiG z#}=JZ#{2a4u|-{TRtD`Ba;tD(XjEP<#Xl8GxL1~)E@s*rPurfv)t;8bxT=`6mZpBHv++$UxSmTaJtRQB) z0~XyHV-KIN{ar>xWMsmSRzf}+zuhe9PIXmEIIn~(VqdL1vA~&yxNkIWb9;85+DEHx zD{vV3h50iS6YSEp=N34@JBn{la;g2qGn;gKKWo3*v}QpQW#_d-s-4?B+Y~=}u5Qjh zu5O6?(~ccDCC^B0+0`!8Zl-bHQjD{U{L9xa-g%l{u~=)D>E2mq4EQ~Wh4$g_a4E9$ zZrtL3+_(^To8FDYMSFbj^QMS#XPu}Zj@>bxZSVEHJsozn$TkNoFz#2&`JlAs5Y5uV zcCQhyXpSJ=ZWV>e9Lk$a#vPNfqq~XSwkzg@=}ru*llK4xXN0(~$9B1M67lxyBLlQtZi_pvs>hXEJ4J7!GG7-ScqR;(H!Gy7V50W9*?RyS+t< zl{-pQ5OG%ST;X}hgEL~RU_UX$9dqOZE1-x7u}UqIO+C4kZAYmLFA-}6WTMfjyEm$0 zbxbj0Jd#{KSDEJ@prtrtcii@oDSpiR$!@WxrW*whvxP`!0PC-7ORLFI$|6T-5D^j01H#W4Ne z#9HNBTEv-RMc&2#_%0X!LIn{nmZ*-8i1&0#{o?&y-h(2B4|;o`tAv$V-YB7xDv8!Q zO~p=?^pu#dRk~PRd0LFpDqW(gG}Ifr$Wc9>;}uzxcSUC3<%%?IBL?E)rM3~#TBWh- zQYW#>OYHXC=Cr%r<_^aD`H!n>eKD8!h=_qb>(#bIR~hOKO7lr*vPno^)uD$-bk>>J zp*lngtai$?iq6PicK(qxeSNP6y1ejS(X)=LxmBaS2(=Cm6#mw(#2_ClF5C!J^9P8Q z-eR?97S_LKVdV}sUT64wlIo%g87`K1i5yRZW%p>1KW)FHThp%ZYM3_&)iX-WbJmHx zSya6cE1vYSn)fqrtxTRo%^xDqc>9IroH`gM7CJkN-{QZATEB*?k!Pq6%@9e>IuU8g zJCS!L!E9+ za^I}%ry`R@O~-4C`ua2RfQyR?S|c88bx}zhh4%6yulcKow+pxS0<&1n{YDJa%XqbO zpU?~W#p>cw?OrSXq}gk-YW1rat~u6s{?O}H-V9XpZip=Xg@G-W_(%sWM7CNPAZKXB zv0DAGoS;>iteOVNceP3nSrdYdaw@K}oTgQuruJ2nW3@_`sZw=hlvZhuYWu9zT|VYD zmwL;`cy+w3{M=#UXR6Cxx5V?Kqk2>?|T#?V2hNIc$`s?%6H%Qa#z~^s@|9{s&})W(YrdOt))=u5|}I`n+bZV^s2GxkW$O#Td0(7)}~& zQQ5x6EUonWQk4ueCTW!>tCz|cn#rz^?4N1%nx-y<7Srul8!m8^eV}i30i*)t$ zbYsqa(|(+~GRxTSJnj7!8UJ6}*R_JfjOy`ehPRrZYNS0##9vfDDg(RCdiz51hQE4k zy)j+49*gYHn+@H>Ec2D28S$#|cbdJClP0e)oytkh#YwEtY*MHR1i}(~ZvZ{$UY>nNm9FTNn-0%pEpKEM)?Gu(8v1ayuv9WDU~oer_4(>MEc6+M~P z_C9a+pQsko&FBC9A!2|SuMW>JU0&iZ&nD23Tbn>uOqLm9r7SW>-riNqQbXpOp{AIc zw?%oe;L`m4G_gQ6NH)hCVrE|X)w`GHZ-)7;#iy3OeekKJj;p>Ek!hB*dWjn4)v^@x zq@jD-%c^Rc`H&Q+^1iEVz4cuse?qrR9ep1qBZ0!vu@B-d|e-{FUfeZKoKTrhtgNHy- z5CDpSKu{c%03|^wP#Qc8%7C(<94HSefJZ{IH&|FgAh;!R0U6fC&5#o z8VCi|K@Ct7)B;a~+Mo`o3+jRTpaFOWGz8CrMxZfh0-Azm;5pD7v;ZwZEATvM4cdUV zpdDxrI)E_H5p)8b!3&@Z=nA@l7eROM5_lQ(0Iz^oK{)6MdVvVg8@vW0K_Bos=nMLR z{$K!j0}KR%z?)z&7y^cZx4kB8B76F!6(2Crh(}o9#~)omB(MN1 z1dG68kPMc9rC=FY4px8^kP1EppMjNN6|g}X_#CVT3VZ>+1Z%)rkPg;?46q(#f-JBB zYy_J?HrNcdfUO`0Yy;cD4zLq^1-=HmKrZ+O>;~V0@4z1LJ=hEOf&JhBI0z1b!{7)w z3Vr~`z;SQ_oCH6DQ{X4?GdK-?0cXHja1Q(m&Vvi!BDe&81HXemz-90!xB{+%Yv4M# z0saCvC)VB|CId=R24zxSlsDx=6`~4LF3Okkql!@e)I(HJDu60R1yaSS5>!d56jhpf zm?}e+rOHv|sS4C1R1g(RRiqxJ9-|(oDp8fG5UL7Qm3o4Dl6s1&Muk$Lu!Bst5H7^(qxk^`v@H5mayLH7b(oL%mM*rTS6*sR7g* z)Ie$w^(Hl#8bS@F-lB$4!>PBa5!6WP9cmQyF7+PuJ{3iMK>de`redhk)Q8j<>LV(a z8cU6%##0lhiPR+OV=9iCOiiJtQlC(6Y8o}2il;1U1~rqKMa`z>P;;qyR01`hN~Dsg z1=K=n5w(~~rj}4ksb$o1Y6X=-rBa_#pHVBRRg_JoQJ+(*DMfujeMzmM)>7%zIx2%& zPi0bB)COuJwTa56Hd9-utyB)RjoMD_pmtJUQD0NLs9fqBYB%*Q^&Pc``kvZL?W6Wn z2dIP8A?h%7ggQ$7KpmrwQzxjC)Q{9D>L==F>NNEWb%r`iouhuG&Qlkti_|6RH|lrl g59%`YCv}CoN?oI_Q#Yu;sG9=uC)XqXvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem node_Conv_283"Conv* @@ -231,27 +231,28 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_4, %repeat_2, %repeat_3, %repeat, %repeat_1, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.conv', 'vision_model.vision._en.stages.0.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.conv', 'vision_model.vision._en.stages.0.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem 8vision_model.vision._en.stages.0.blocks.0.mlp.fc1.weight 6vision_model.vision._en.stages.0.blocks.0.mlp.fc1.biasconv2d_5 node_conv2d_5"Conv* @@ -263,47 +264,47 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.0.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.0.blocks.0.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_5: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_5 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.fc1', 'conv2d_5']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.fc1', 'conv2d_5']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_5gelu_3 node_gelu_3"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.0.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.0.blocks.0.mlp.act: timm.layers.activations.GELUTanh/gelu_3: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node~%gelu_3 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_5,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.act', 'gelu_3']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.act', 'gelu_3']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_3 8vision_model.vision._en.stages.0.blocks.0.mlp.fc2.weight 6vision_model.vision._en.stages.0.blocks.0.mlp.fc2.biasconv2d_6 node_conv2d_6"Conv* @@ -315,64 +316,64 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.0.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.0.blocks.0.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_6: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_6 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.fc2', 'conv2d_6']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.fc2', 'conv2d_6']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_6 ;vision_model.vision._en.stages.0.blocks.0.layer_scale.gammamulnode_mul"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.0.blocks.0.layer_scale: timm.models.fastvit.LayerScale2d/mul: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_1, %p_vision_model_vision__en_stages_0_blocks_0_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.layer_scale', 'mul']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.layer_scale', 'mul']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_3 muladdnode_add"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.0: timm.models.fastvit.RepMixerBlock/add: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodem%add : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_3, %mul), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'add']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'add']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add Ivision_model.vision._en.stages.0.blocks.1.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.0.blocks.1.token_mixer.reparam_conv.biasconv2d_7 node_conv2d_7"Conv* @@ -384,24 +385,24 @@ Gvision_model.vision._en.stages.0.blocks.1.token_mixer.reparam_conv.biasconv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.0.blocks.1.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.0.blocks.1.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_7: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_7 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add, %p_vision_model_vision__en_stages_0_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_0_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 64), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.token_mixer', 'vision_model.vision._en.stages.0.blocks.1.token_mixer.reparam_conv', 'conv2d_7']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.token_mixer', 'vision_model.vision._en.stages.0.blocks.1.token_mixer.reparam_conv', 'conv2d_7']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_7 >vision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 node_Conv_285"Conv* @@ -414,27 +415,28 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_1 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_8, %repeat_6, %repeat_7, %repeat_4, %repeat_5, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.conv', 'vision_model.vision._en.stages.0.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_1']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.conv', 'vision_model.vision._en.stages.0.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_1']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_3 8vision_model.vision._en.stages.0.blocks.1.mlp.fc1.weight 6vision_model.vision._en.stages.0.blocks.1.mlp.fc1.biasconv2d_9 node_conv2d_9"Conv* @@ -446,47 +448,47 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.0.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.0.blocks.1.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_9: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_9 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_3, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.fc1', 'conv2d_9']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.fc1', 'conv2d_9']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_9gelu_4 node_gelu_4"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.0.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.0.blocks.1.mlp.act: timm.layers.activations.GELUTanh/gelu_4: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node~%gelu_4 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_9,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.act', 'gelu_4']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.act', 'gelu_4']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_4 8vision_model.vision._en.stages.0.blocks.1.mlp.fc2.weight 6vision_model.vision._en.stages.0.blocks.1.mlp.fc2.bias conv2d_10node_conv2d_10"Conv* @@ -498,66 +500,66 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.0.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.0.blocks.1.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_10: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_10 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_2, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.fc2', 'conv2d_10']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.fc2', 'conv2d_10']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_10 ;vision_model.vision._en.stages.0.blocks.1.layer_scale.gammamul_1 node_mul_1"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.0.blocks.1.layer_scale: timm.models.fastvit.LayerScale2d/mul_1: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_1 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_3, %p_vision_model_vision__en_stages_0_blocks_1_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.layer_scale', 'mul_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.layer_scale', 'mul_1']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_7 mul_1add_1 node_add_1"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.0: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.0.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.0.blocks.1: timm.models.fastvit.RepMixerBlock/add_1: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodeq%add_1 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_7, %mul_1), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'add_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'add_1']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_1 Fvision_model.vision._en.stages.1.downsample.proj.0.reparam_conv.weight Dvision_model.vision._en.stages.1.downsample.proj.0.reparam_conv.bias conv2d_11node_conv2d_11"Conv* @@ -569,24 +571,24 @@ Dvision_model.vision._en.stages.1.downsample.proj.0.reparam_conv.bias conv2d_11 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.downsample: timm.models.fastvit.PatchEmbed/vision_model.vision._en.stages.1.downsample.proj: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.downsample.proj.0: timm.models.fastvit.ReparamLargeKernelConv/vision_model.vision._en.stages.1.downsample.proj.0.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_11: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.ReparamLargeKernelConv', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_11 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_1, %p_vision_model_vision__en_stages_1_downsample_proj_0_reparam_conv_weight, %p_vision_model_vision__en_stages_1_downsample_proj_0_reparam_conv_bias, [2, 2], [3, 3], [1, 1], 64), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.0', 'vision_model.vision._en.stages.1.downsample.proj.0.reparam_conv', 'conv2d_11']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.0', 'vision_model.vision._en.stages.1.downsample.proj.0.reparam_conv', 'conv2d_11']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward out = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_11 Fvision_model.vision._en.stages.1.downsample.proj.1.reparam_conv.weight Dvision_model.vision._en.stages.1.downsample.proj.1.reparam_conv.bias conv2d_12node_conv2d_12"Conv* @@ -598,47 +600,47 @@ Dvision_model.vision._en.stages.1.downsample.proj.1.reparam_conv.bias conv2d_12 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.downsample: timm.models.fastvit.PatchEmbed/vision_model.vision._en.stages.1.downsample.proj: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.downsample.proj.1: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.stages.1.downsample.proj.1.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_12: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_12 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%conv2d_11, %p_vision_model_vision__en_stages_1_downsample_proj_1_reparam_conv_weight, %p_vision_model_vision__en_stages_1_downsample_proj_1_reparam_conv_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.1', 'vision_model.vision._en.stages.1.downsample.proj.1.reparam_conv', 'conv2d_12']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.1', 'vision_model.vision._en.stages.1.downsample.proj.1.reparam_conv', 'conv2d_12']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_12gelu_5 node_gelu_5"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.downsample: timm.models.fastvit.PatchEmbed/vision_model.vision._en.stages.1.downsample.proj: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.downsample.proj.1: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.stages.1.downsample.proj.1.act: timm.layers.activations.GELUTanh/gelu_5: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_5 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_12,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.1', 'vision_model.vision._en.stages.1.downsample.proj.1.act', 'gelu_5']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.1', 'vision_model.vision._en.stages.1.downsample.proj.1.act', 'gelu_5']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_5 Ivision_model.vision._en.stages.1.blocks.0.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.1.blocks.0.token_mixer.reparam_conv.bias conv2d_13node_conv2d_13"Conv* @@ -650,24 +652,24 @@ Gvision_model.vision._en.stages.1.blocks.0.token_mixer.reparam_conv.bias conv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.1.blocks.0.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.1.blocks.0.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_13: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_13 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_5, %p_vision_model_vision__en_stages_1_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_1_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 128), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.token_mixer', 'vision_model.vision._en.stages.1.blocks.0.token_mixer.reparam_conv', 'conv2d_13']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.token_mixer', 'vision_model.vision._en.stages.1.blocks.0.token_mixer.reparam_conv', 'conv2d_13']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_13 >vision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 node_Conv_287"Conv* @@ -680,27 +682,28 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_2 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_14, %repeat_10, %repeat_11, %repeat_8, %repeat_9, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.conv', 'vision_model.vision._en.stages.1.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_2']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.conv', 'vision_model.vision._en.stages.1.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_2']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_6 8vision_model.vision._en.stages.1.blocks.0.mlp.fc1.weight 6vision_model.vision._en.stages.1.blocks.0.mlp.fc1.bias conv2d_15node_conv2d_15"Conv* @@ -712,47 +715,47 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.1.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.1.blocks.0.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_15: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_15 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_6, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.fc1', 'conv2d_15']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.fc1', 'conv2d_15']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_15gelu_6 node_gelu_6"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.1.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.1.blocks.0.mlp.act: timm.layers.activations.GELUTanh/gelu_6: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_6 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_15,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.act', 'gelu_6']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.act', 'gelu_6']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_6 8vision_model.vision._en.stages.1.blocks.0.mlp.fc2.weight 6vision_model.vision._en.stages.1.blocks.0.mlp.fc2.bias conv2d_16node_conv2d_16"Conv* @@ -764,66 +767,66 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.1.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.1.blocks.0.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_16: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_16 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_4, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.fc2', 'conv2d_16']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.fc2', 'conv2d_16']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_16 ;vision_model.vision._en.stages.1.blocks.0.layer_scale.gammamul_2 node_mul_2"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.1.blocks.0.layer_scale: timm.models.fastvit.LayerScale2d/mul_2: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_2 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_5, %p_vision_model_vision__en_stages_1_blocks_0_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.layer_scale', 'mul_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.layer_scale', 'mul_2']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_13 mul_2add_2 node_add_2"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.0: timm.models.fastvit.RepMixerBlock/add_2: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_2 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_13, %mul_2), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'add_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'add_2']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_2 Ivision_model.vision._en.stages.1.blocks.1.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.1.blocks.1.token_mixer.reparam_conv.bias conv2d_17node_conv2d_17"Conv* @@ -835,24 +838,24 @@ Gvision_model.vision._en.stages.1.blocks.1.token_mixer.reparam_conv.bias conv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.1.blocks.1.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.1.blocks.1.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_17: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_17 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_2, %p_vision_model_vision__en_stages_1_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_1_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 128), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.token_mixer', 'vision_model.vision._en.stages.1.blocks.1.token_mixer.reparam_conv', 'conv2d_17']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.token_mixer', 'vision_model.vision._en.stages.1.blocks.1.token_mixer.reparam_conv', 'conv2d_17']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_17 >vision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 node_Conv_289"Conv* @@ -865,27 +868,28 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_3 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_18, %repeat_14, %repeat_15, %repeat_12, %repeat_13, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.conv', 'vision_model.vision._en.stages.1.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_3']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.conv', 'vision_model.vision._en.stages.1.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_3']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_9 8vision_model.vision._en.stages.1.blocks.1.mlp.fc1.weight 6vision_model.vision._en.stages.1.blocks.1.mlp.fc1.bias conv2d_19node_conv2d_19"Conv* @@ -897,47 +901,47 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.1.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.1.blocks.1.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_19: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_19 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_9, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.fc1', 'conv2d_19']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.fc1', 'conv2d_19']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_19gelu_7 node_gelu_7"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.1.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.1.blocks.1.mlp.act: timm.layers.activations.GELUTanh/gelu_7: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_7 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_19,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.act', 'gelu_7']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.act', 'gelu_7']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_7 8vision_model.vision._en.stages.1.blocks.1.mlp.fc2.weight 6vision_model.vision._en.stages.1.blocks.1.mlp.fc2.bias conv2d_20node_conv2d_20"Conv* @@ -949,66 +953,66 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.1.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.1.blocks.1.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_20: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_20 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_6, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.fc2', 'conv2d_20']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.fc2', 'conv2d_20']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_20 ;vision_model.vision._en.stages.1.blocks.1.layer_scale.gammamul_3 node_mul_3"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.1.blocks.1.layer_scale: timm.models.fastvit.LayerScale2d/mul_3: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_3 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_7, %p_vision_model_vision__en_stages_1_blocks_1_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.layer_scale', 'mul_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.layer_scale', 'mul_3']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_17 mul_3add_3 node_add_3"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.1: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.1.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.1.blocks.1: timm.models.fastvit.RepMixerBlock/add_3: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_3 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_17, %mul_3), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'add_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'add_3']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_3 Fvision_model.vision._en.stages.2.downsample.proj.0.reparam_conv.weight Dvision_model.vision._en.stages.2.downsample.proj.0.reparam_conv.bias conv2d_21node_conv2d_21"Conv* @@ -1020,24 +1024,24 @@ Dvision_model.vision._en.stages.2.downsample.proj.0.reparam_conv.bias conv2d_21 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.downsample: timm.models.fastvit.PatchEmbed/vision_model.vision._en.stages.2.downsample.proj: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.downsample.proj.0: timm.models.fastvit.ReparamLargeKernelConv/vision_model.vision._en.stages.2.downsample.proj.0.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_21: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.ReparamLargeKernelConv', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_21 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_3, %p_vision_model_vision__en_stages_2_downsample_proj_0_reparam_conv_weight, %p_vision_model_vision__en_stages_2_downsample_proj_0_reparam_conv_bias, [2, 2], [3, 3], [1, 1], 128), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.0', 'vision_model.vision._en.stages.2.downsample.proj.0.reparam_conv', 'conv2d_21']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.0', 'vision_model.vision._en.stages.2.downsample.proj.0.reparam_conv', 'conv2d_21']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward out = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_21 Fvision_model.vision._en.stages.2.downsample.proj.1.reparam_conv.weight Dvision_model.vision._en.stages.2.downsample.proj.1.reparam_conv.bias conv2d_22node_conv2d_22"Conv* @@ -1049,47 +1053,47 @@ Dvision_model.vision._en.stages.2.downsample.proj.1.reparam_conv.bias conv2d_22 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.downsample: timm.models.fastvit.PatchEmbed/vision_model.vision._en.stages.2.downsample.proj: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.downsample.proj.1: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.stages.2.downsample.proj.1.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_22: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_22 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%conv2d_21, %p_vision_model_vision__en_stages_2_downsample_proj_1_reparam_conv_weight, %p_vision_model_vision__en_stages_2_downsample_proj_1_reparam_conv_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.1', 'vision_model.vision._en.stages.2.downsample.proj.1.reparam_conv', 'conv2d_22']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.1', 'vision_model.vision._en.stages.2.downsample.proj.1.reparam_conv', 'conv2d_22']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_22gelu_8 node_gelu_8"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.downsample: timm.models.fastvit.PatchEmbed/vision_model.vision._en.stages.2.downsample.proj: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.downsample.proj.1: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.stages.2.downsample.proj.1.act: timm.layers.activations.GELUTanh/gelu_8: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_8 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_22,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.1', 'vision_model.vision._en.stages.2.downsample.proj.1.act', 'gelu_8']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.1', 'vision_model.vision._en.stages.2.downsample.proj.1.act', 'gelu_8']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_8 Ivision_model.vision._en.stages.2.blocks.0.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.2.blocks.0.token_mixer.reparam_conv.bias conv2d_23node_conv2d_23"Conv* @@ -1101,24 +1105,24 @@ Gvision_model.vision._en.stages.2.blocks.0.token_mixer.reparam_conv.bias conv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.0.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.2.blocks.0.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_23: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_23 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_8, %p_vision_model_vision__en_stages_2_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.token_mixer', 'vision_model.vision._en.stages.2.blocks.0.token_mixer.reparam_conv', 'conv2d_23']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.token_mixer', 'vision_model.vision._en.stages.2.blocks.0.token_mixer.reparam_conv', 'conv2d_23']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_23 >vision_model.vision._en.stages.2.blocks.0.mlp.conv.conv.weight Cvision_model.vision._en.stages.2.blocks.0.mlp.conv.conv.weight_bias @@ -1132,27 +1136,28 @@ getitem_12 node_Conv_291"Conv* !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_4 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_24, %repeat_18, %repeat_19, %repeat_16, %repeat_17, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.conv', 'vision_model.vision._en.stages.2.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_4']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.conv', 'vision_model.vision._en.stages.2.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_4']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_12 8vision_model.vision._en.stages.2.blocks.0.mlp.fc1.weight @@ -1165,47 +1170,47 @@ getitem_12 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.0.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_25: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_25 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_12, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.fc1', 'conv2d_25']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.fc1', 'conv2d_25']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_25gelu_9 node_gelu_9"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.0.mlp.act: timm.layers.activations.GELUTanh/gelu_9: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_9 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_25,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.act', 'gelu_9']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.act', 'gelu_9']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_9 8vision_model.vision._en.stages.2.blocks.0.mlp.fc2.weight 6vision_model.vision._en.stages.2.blocks.0.mlp.fc2.bias conv2d_26node_conv2d_26"Conv* @@ -1217,66 +1222,66 @@ getitem_12 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.0.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_26: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_26 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_8, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.fc2', 'conv2d_26']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.fc2', 'conv2d_26']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_26 ;vision_model.vision._en.stages.2.blocks.0.layer_scale.gammamul_4 node_mul_4"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.0.layer_scale: timm.models.fastvit.LayerScale2d/mul_4: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_4 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_9, %p_vision_model_vision__en_stages_2_blocks_0_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.layer_scale', 'mul_4']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.layer_scale', 'mul_4']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_23 mul_4add_4 node_add_4"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.0: timm.models.fastvit.RepMixerBlock/add_4: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_4 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_23, %mul_4), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'add_4']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'add_4']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_4 Ivision_model.vision._en.stages.2.blocks.1.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.2.blocks.1.token_mixer.reparam_conv.bias conv2d_27node_conv2d_27"Conv* @@ -1288,24 +1293,24 @@ Gvision_model.vision._en.stages.2.blocks.1.token_mixer.reparam_conv.bias conv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.1.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.2.blocks.1.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_27: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_27 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_4, %p_vision_model_vision__en_stages_2_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.token_mixer', 'vision_model.vision._en.stages.2.blocks.1.token_mixer.reparam_conv', 'conv2d_27']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.token_mixer', 'vision_model.vision._en.stages.2.blocks.1.token_mixer.reparam_conv', 'conv2d_27']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_27 >vision_model.vision._en.stages.2.blocks.1.mlp.conv.conv.weight Cvision_model.vision._en.stages.2.blocks.1.mlp.conv.conv.weight_bias @@ -1319,27 +1324,28 @@ getitem_15 node_Conv_293"Conv* !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_5 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_28, %repeat_22, %repeat_23, %repeat_20, %repeat_21, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.conv', 'vision_model.vision._en.stages.2.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_5']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.conv', 'vision_model.vision._en.stages.2.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_5']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_15 8vision_model.vision._en.stages.2.blocks.1.mlp.fc1.weight @@ -1352,47 +1358,47 @@ getitem_15 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.1.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_29: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_29 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_15, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.fc1', 'conv2d_29']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.fc1', 'conv2d_29']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_29gelu_10 node_gelu_10"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.1.mlp.act: timm.layers.activations.GELUTanh/gelu_10: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_10 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_29,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.act', 'gelu_10']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.act', 'gelu_10']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_10 8vision_model.vision._en.stages.2.blocks.1.mlp.fc2.weight 6vision_model.vision._en.stages.2.blocks.1.mlp.fc2.bias conv2d_30node_conv2d_30"Conv* @@ -1404,66 +1410,66 @@ getitem_15 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.1.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_30: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_30 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_10, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.fc2', 'conv2d_30']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.fc2', 'conv2d_30']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_30 ;vision_model.vision._en.stages.2.blocks.1.layer_scale.gammamul_5 node_mul_5"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.1.layer_scale: timm.models.fastvit.LayerScale2d/mul_5: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_5 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_11, %p_vision_model_vision__en_stages_2_blocks_1_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.layer_scale', 'mul_5']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.layer_scale', 'mul_5']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_27 mul_5add_5 node_add_5"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.1: timm.models.fastvit.RepMixerBlock/add_5: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_5 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_27, %mul_5), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'add_5']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'add_5']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_5 Ivision_model.vision._en.stages.2.blocks.2.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.2.blocks.2.token_mixer.reparam_conv.bias conv2d_31node_conv2d_31"Conv* @@ -1475,24 +1481,24 @@ Gvision_model.vision._en.stages.2.blocks.2.token_mixer.reparam_conv.bias conv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.2: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.2.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.2.blocks.2.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_31: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_31 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_5, %p_vision_model_vision__en_stages_2_blocks_2_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_2_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.token_mixer', 'vision_model.vision._en.stages.2.blocks.2.token_mixer.reparam_conv', 'conv2d_31']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.token_mixer', 'vision_model.vision._en.stages.2.blocks.2.token_mixer.reparam_conv', 'conv2d_31']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_31 >vision_model.vision._en.stages.2.blocks.2.mlp.conv.conv.weight Cvision_model.vision._en.stages.2.blocks.2.mlp.conv.conv.weight_bias @@ -1506,27 +1512,28 @@ getitem_18 node_Conv_295"Conv* !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_6 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_32, %repeat_26, %repeat_27, %repeat_24, %repeat_25, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.conv', 'vision_model.vision._en.stages.2.blocks.2.mlp.conv.bn', '_native_batch_norm_legit_no_training_6']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.conv', 'vision_model.vision._en.stages.2.blocks.2.mlp.conv.bn', '_native_batch_norm_legit_no_training_6']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_18 8vision_model.vision._en.stages.2.blocks.2.mlp.fc1.weight @@ -1539,47 +1546,47 @@ getitem_18 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.2: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.2.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.2.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_33: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_33 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_18, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.fc1', 'conv2d_33']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.fc1', 'conv2d_33']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_33gelu_11 node_gelu_11"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.2: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.2.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.2.mlp.act: timm.layers.activations.GELUTanh/gelu_11: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_11 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_33,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.act', 'gelu_11']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.act', 'gelu_11']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_11 8vision_model.vision._en.stages.2.blocks.2.mlp.fc2.weight 6vision_model.vision._en.stages.2.blocks.2.mlp.fc2.bias conv2d_34node_conv2d_34"Conv* @@ -1591,66 +1598,66 @@ getitem_18 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.2: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.2.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.2.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_34: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_34 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_12, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.fc2', 'conv2d_34']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.fc2', 'conv2d_34']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_34 ;vision_model.vision._en.stages.2.blocks.2.layer_scale.gammamul_6 node_mul_6"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.2: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.2.layer_scale: timm.models.fastvit.LayerScale2d/mul_6: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_6 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_13, %p_vision_model_vision__en_stages_2_blocks_2_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.layer_scale', 'mul_6']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.layer_scale', 'mul_6']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_31 mul_6add_6 node_add_6"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.2: timm.models.fastvit.RepMixerBlock/add_6: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_6 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_31, %mul_6), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'add_6']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'add_6']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_6 Ivision_model.vision._en.stages.2.blocks.3.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.2.blocks.3.token_mixer.reparam_conv.bias conv2d_35node_conv2d_35"Conv* @@ -1662,24 +1669,24 @@ Gvision_model.vision._en.stages.2.blocks.3.token_mixer.reparam_conv.bias conv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.3: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.3.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.2.blocks.3.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_35: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_35 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_6, %p_vision_model_vision__en_stages_2_blocks_3_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_3_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.token_mixer', 'vision_model.vision._en.stages.2.blocks.3.token_mixer.reparam_conv', 'conv2d_35']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.token_mixer', 'vision_model.vision._en.stages.2.blocks.3.token_mixer.reparam_conv', 'conv2d_35']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_35 >vision_model.vision._en.stages.2.blocks.3.mlp.conv.conv.weight Cvision_model.vision._en.stages.2.blocks.3.mlp.conv.conv.weight_bias @@ -1693,27 +1700,28 @@ getitem_21 node_Conv_297"Conv* !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_7 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_36, %repeat_30, %repeat_31, %repeat_28, %repeat_29, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.conv', 'vision_model.vision._en.stages.2.blocks.3.mlp.conv.bn', '_native_batch_norm_legit_no_training_7']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.conv', 'vision_model.vision._en.stages.2.blocks.3.mlp.conv.bn', '_native_batch_norm_legit_no_training_7']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_21 8vision_model.vision._en.stages.2.blocks.3.mlp.fc1.weight @@ -1726,47 +1734,47 @@ getitem_21 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.3: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.3.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.3.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_37: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_37 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_21, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.fc1', 'conv2d_37']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.fc1', 'conv2d_37']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_37gelu_12 node_gelu_12"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.3: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.3.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.3.mlp.act: timm.layers.activations.GELUTanh/gelu_12: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_12 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_37,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.act', 'gelu_12']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.act', 'gelu_12']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_12 8vision_model.vision._en.stages.2.blocks.3.mlp.fc2.weight 6vision_model.vision._en.stages.2.blocks.3.mlp.fc2.bias conv2d_38node_conv2d_38"Conv* @@ -1778,66 +1786,66 @@ getitem_21 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.3: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.3.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.3.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_38: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_38 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_14, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.fc2', 'conv2d_38']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.fc2', 'conv2d_38']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_38 ;vision_model.vision._en.stages.2.blocks.3.layer_scale.gammamul_7 node_mul_7"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.3: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.3.layer_scale: timm.models.fastvit.LayerScale2d/mul_7: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_7 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_15, %p_vision_model_vision__en_stages_2_blocks_3_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.layer_scale', 'mul_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.layer_scale', 'mul_7']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_35 mul_7add_7 node_add_7"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.3: timm.models.fastvit.RepMixerBlock/add_7: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_7 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_35, %mul_7), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'add_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'add_7']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_7 Ivision_model.vision._en.stages.2.blocks.4.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.2.blocks.4.token_mixer.reparam_conv.bias conv2d_39node_conv2d_39"Conv* @@ -1849,24 +1857,24 @@ Gvision_model.vision._en.stages.2.blocks.4.token_mixer.reparam_conv.bias conv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.4: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.4.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.2.blocks.4.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_39: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_39 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_7, %p_vision_model_vision__en_stages_2_blocks_4_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_4_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.token_mixer', 'vision_model.vision._en.stages.2.blocks.4.token_mixer.reparam_conv', 'conv2d_39']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.token_mixer', 'vision_model.vision._en.stages.2.blocks.4.token_mixer.reparam_conv', 'conv2d_39']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_39 >vision_model.vision._en.stages.2.blocks.4.mlp.conv.conv.weight Cvision_model.vision._en.stages.2.blocks.4.mlp.conv.conv.weight_bias @@ -1880,27 +1888,28 @@ getitem_24 node_Conv_299"Conv* !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_8 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_40, %repeat_34, %repeat_35, %repeat_32, %repeat_33, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.conv', 'vision_model.vision._en.stages.2.blocks.4.mlp.conv.bn', '_native_batch_norm_legit_no_training_8']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.conv', 'vision_model.vision._en.stages.2.blocks.4.mlp.conv.bn', '_native_batch_norm_legit_no_training_8']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_24 8vision_model.vision._en.stages.2.blocks.4.mlp.fc1.weight @@ -1913,47 +1922,47 @@ getitem_24 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.4: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.4.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.4.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_41: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_41 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_24, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.fc1', 'conv2d_41']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.fc1', 'conv2d_41']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_41gelu_13 node_gelu_13"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.4: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.4.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.4.mlp.act: timm.layers.activations.GELUTanh/gelu_13: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_13 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_41,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.act', 'gelu_13']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.act', 'gelu_13']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_13 8vision_model.vision._en.stages.2.blocks.4.mlp.fc2.weight 6vision_model.vision._en.stages.2.blocks.4.mlp.fc2.bias conv2d_42node_conv2d_42"Conv* @@ -1965,66 +1974,66 @@ getitem_24 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.4: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.4.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.4.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_42: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_42 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_16, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.fc2', 'conv2d_42']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.fc2', 'conv2d_42']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_42 ;vision_model.vision._en.stages.2.blocks.4.layer_scale.gammamul_8 node_mul_8"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.4: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.4.layer_scale: timm.models.fastvit.LayerScale2d/mul_8: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_8 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_17, %p_vision_model_vision__en_stages_2_blocks_4_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.layer_scale', 'mul_8']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.layer_scale', 'mul_8']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_39 mul_8add_8 node_add_8"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.4: timm.models.fastvit.RepMixerBlock/add_8: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_8 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_39, %mul_8), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'add_8']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'add_8']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_8 Ivision_model.vision._en.stages.2.blocks.5.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.2.blocks.5.token_mixer.reparam_conv.bias conv2d_43node_conv2d_43"Conv* @@ -2036,24 +2045,24 @@ Gvision_model.vision._en.stages.2.blocks.5.token_mixer.reparam_conv.bias conv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.5: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.5.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.2.blocks.5.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_43: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_43 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_8, %p_vision_model_vision__en_stages_2_blocks_5_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_5_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.token_mixer', 'vision_model.vision._en.stages.2.blocks.5.token_mixer.reparam_conv', 'conv2d_43']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.token_mixer', 'vision_model.vision._en.stages.2.blocks.5.token_mixer.reparam_conv', 'conv2d_43']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_43 >vision_model.vision._en.stages.2.blocks.5.mlp.conv.conv.weight Cvision_model.vision._en.stages.2.blocks.5.mlp.conv.conv.weight_bias @@ -2067,27 +2076,28 @@ getitem_27 node_Conv_301"Conv* !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_9 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_44, %repeat_38, %repeat_39, %repeat_36, %repeat_37, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.conv', 'vision_model.vision._en.stages.2.blocks.5.mlp.conv.bn', '_native_batch_norm_legit_no_training_9']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.conv', 'vision_model.vision._en.stages.2.blocks.5.mlp.conv.bn', '_native_batch_norm_legit_no_training_9']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_27 8vision_model.vision._en.stages.2.blocks.5.mlp.fc1.weight @@ -2100,47 +2110,47 @@ getitem_27 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.5: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.5.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.5.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_45: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_45 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_27, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.fc1', 'conv2d_45']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.fc1', 'conv2d_45']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_45gelu_14 node_gelu_14"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.5: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.5.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.5.mlp.act: timm.layers.activations.GELUTanh/gelu_14: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_14 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_45,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.act', 'gelu_14']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.act', 'gelu_14']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_14 8vision_model.vision._en.stages.2.blocks.5.mlp.fc2.weight 6vision_model.vision._en.stages.2.blocks.5.mlp.fc2.bias conv2d_46node_conv2d_46"Conv* @@ -2152,66 +2162,66 @@ getitem_27 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.5: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.5.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.2.blocks.5.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_46: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_46 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_18, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.fc2', 'conv2d_46']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.fc2', 'conv2d_46']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_46 ;vision_model.vision._en.stages.2.blocks.5.layer_scale.gammamul_9 node_mul_9"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.5: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.2.blocks.5.layer_scale: timm.models.fastvit.LayerScale2d/mul_9: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_9 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_19, %p_vision_model_vision__en_stages_2_blocks_5_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.layer_scale', 'mul_9']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.layer_scale', 'mul_9']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_43 mul_9add_9 node_add_9"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.2: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.2.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.2.blocks.5: timm.models.fastvit.RepMixerBlock/add_9: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_noder%add_9 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_43, %mul_9), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'add_9']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'add_9']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_9 Fvision_model.vision._en.stages.3.downsample.proj.0.reparam_conv.weight Dvision_model.vision._en.stages.3.downsample.proj.0.reparam_conv.bias conv2d_47node_conv2d_47"Conv* @@ -2223,24 +2233,24 @@ Dvision_model.vision._en.stages.3.downsample.proj.0.reparam_conv.bias conv2d_47 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.downsample: timm.models.fastvit.PatchEmbed/vision_model.vision._en.stages.3.downsample.proj: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.downsample.proj.0: timm.models.fastvit.ReparamLargeKernelConv/vision_model.vision._en.stages.3.downsample.proj.0.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_47: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.ReparamLargeKernelConv', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_47 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_9, %p_vision_model_vision__en_stages_3_downsample_proj_0_reparam_conv_weight, %p_vision_model_vision__en_stages_3_downsample_proj_0_reparam_conv_bias, [2, 2], [3, 3], [1, 1], 256), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.0', 'vision_model.vision._en.stages.3.downsample.proj.0.reparam_conv', 'conv2d_47']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.0', 'vision_model.vision._en.stages.3.downsample.proj.0.reparam_conv', 'conv2d_47']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 376, in forward out = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_47 Fvision_model.vision._en.stages.3.downsample.proj.1.reparam_conv.weight Dvision_model.vision._en.stages.3.downsample.proj.1.reparam_conv.bias conv2d_48node_conv2d_48"Conv* @@ -2252,47 +2262,47 @@ Dvision_model.vision._en.stages.3.downsample.proj.1.reparam_conv.bias conv2d_48 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.downsample: timm.models.fastvit.PatchEmbed/vision_model.vision._en.stages.3.downsample.proj: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.downsample.proj.1: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.stages.3.downsample.proj.1.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_48: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_48 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%conv2d_47, %p_vision_model_vision__en_stages_3_downsample_proj_1_reparam_conv_weight, %p_vision_model_vision__en_stages_3_downsample_proj_1_reparam_conv_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.1', 'vision_model.vision._en.stages.3.downsample.proj.1.reparam_conv', 'conv2d_48']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.1', 'vision_model.vision._en.stages.3.downsample.proj.1.reparam_conv', 'conv2d_48']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_48gelu_15 node_gelu_15"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.downsample: timm.models.fastvit.PatchEmbed/vision_model.vision._en.stages.3.downsample.proj: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.downsample.proj.1: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.stages.3.downsample.proj.1.act: timm.layers.activations.GELUTanh/gelu_15: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_15 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_48,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.1', 'vision_model.vision._en.stages.3.downsample.proj.1.act', 'gelu_15']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.1', 'vision_model.vision._en.stages.3.downsample.proj.1.act', 'gelu_15']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1162, in forward x = self.downsample(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 628, in forward x = self.proj(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_15 Ivision_model.vision._en.stages.3.blocks.0.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.3.blocks.0.token_mixer.reparam_conv.bias conv2d_49node_conv2d_49"Conv* @@ -2304,24 +2314,24 @@ Gvision_model.vision._en.stages.3.blocks.0.token_mixer.reparam_conv.bias conv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.3.blocks.0.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.3.blocks.0.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_49: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_49 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_15, %p_vision_model_vision__en_stages_3_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_3_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 512), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.token_mixer', 'vision_model.vision._en.stages.3.blocks.0.token_mixer.reparam_conv', 'conv2d_49']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.token_mixer', 'vision_model.vision._en.stages.3.blocks.0.token_mixer.reparam_conv', 'conv2d_49']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_49 >vision_model.vision._en.stages.3.blocks.0.mlp.conv.conv.weight Cvision_model.vision._en.stages.3.blocks.0.mlp.conv.conv.weight_bias @@ -2335,27 +2345,28 @@ getitem_30 node_Conv_303"Conv* !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_10 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_50, %repeat_42, %repeat_43, %repeat_40, %repeat_41, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.conv', 'vision_model.vision._en.stages.3.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_10']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.conv', 'vision_model.vision._en.stages.3.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_10']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_30 8vision_model.vision._en.stages.3.blocks.0.mlp.fc1.weight @@ -2368,47 +2379,47 @@ getitem_30 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.3.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.3.blocks.0.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_51: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_51 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_30, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.fc1', 'conv2d_51']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.fc1', 'conv2d_51']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_51gelu_16 node_gelu_16"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.3.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.3.blocks.0.mlp.act: timm.layers.activations.GELUTanh/gelu_16: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_16 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_51,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.act', 'gelu_16']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.act', 'gelu_16']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_16 8vision_model.vision._en.stages.3.blocks.0.mlp.fc2.weight 6vision_model.vision._en.stages.3.blocks.0.mlp.fc2.bias conv2d_52node_conv2d_52"Conv* @@ -2420,64 +2431,64 @@ getitem_30 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.3.blocks.0.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.3.blocks.0.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_52: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_52 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_20, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.fc2', 'conv2d_52']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.fc2', 'conv2d_52']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_52 ;vision_model.vision._en.stages.3.blocks.0.layer_scale.gammamul_10 node_mul_10"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.0: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.3.blocks.0.layer_scale: timm.models.fastvit.LayerScale2d/mul_10: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_10 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_21, %p_vision_model_vision__en_stages_3_blocks_0_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.layer_scale', 'mul_10']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.layer_scale', 'mul_10']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_49 mul_10add_10 node_add_10"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.0: timm.models.fastvit.RepMixerBlock/add_10: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodet%add_10 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_49, %mul_10), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'add_10']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'add_10']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_10 Ivision_model.vision._en.stages.3.blocks.1.token_mixer.reparam_conv.weight Gvision_model.vision._en.stages.3.blocks.1.token_mixer.reparam_conv.bias conv2d_53node_conv2d_53"Conv* @@ -2489,24 +2500,24 @@ Gvision_model.vision._en.stages.3.blocks.1.token_mixer.reparam_conv.bias conv2d namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.3.blocks.1.token_mixer: timm.models.fastvit.RepMixer/vision_model.vision._en.stages.3.blocks.1.token_mixer.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_53: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_53 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_10, %p_vision_model_vision__en_stages_3_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_3_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 512), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.token_mixer', 'vision_model.vision._en.stages.3.blocks.1.token_mixer.reparam_conv', 'conv2d_53']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.token_mixer', 'vision_model.vision._en.stages.3.blocks.1.token_mixer.reparam_conv', 'conv2d_53']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1001, in forward x = self.token_mixer(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 717, in forward x = self.reparam_conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_53 >vision_model.vision._en.stages.3.blocks.1.mlp.conv.conv.weight Cvision_model.vision._en.stages.3.blocks.1.mlp.conv.conv.weight_bias @@ -2520,27 +2531,28 @@ getitem_33 node_Conv_305"Conv* !pkg.onnxscript.rewriter.rule_name1FuseBatchNormIntoConv, RemoveOptionalBiasFromConvJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'xx.training.path.allnorm.AllNormAct2d', 'aten._native_batch_norm_legit_no_training.default']J pkg.torch.onnx.fx_node%_native_batch_norm_legit_no_training_11 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_54, %repeat_46, %repeat_47, %repeat_44, %repeat_45, 0.01, 0.001), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.conv', 'vision_model.vision._en.stages.3.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_11']J +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.conv', 'vision_model.vision._en.stages.3.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_11']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.stack_trace +File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 814, in forward x = self.conv(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/conv_bn_act.py", line 94, in forward x = self.bn(x) - File "/home/batman/xx/xx/training/path/allnorm.py", line 60, in forward + File "/home/batman/xx2/xx/training/path/allnorm.py", line 60, in forward return self.act(self.drop(self._allnorm_forward(x))) - + getitem_33 8vision_model.vision._en.stages.3.blocks.1.mlp.fc1.weight @@ -2553,47 +2565,47 @@ getitem_33 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.3.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.3.blocks.1.mlp.fc1: torch.nn.modules.conv.Conv2d/conv2d_55: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_55 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_33, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.fc1', 'conv2d_55']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.fc1', 'conv2d_55']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 815, in forward x = self.fc1(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_55gelu_17 node_gelu_17"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.3.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.3.blocks.1.mlp.act: timm.layers.activations.GELUTanh/gelu_17: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_17 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_55,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.act', 'gelu_17']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.act', 'gelu_17']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 816, in forward x = self.act(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_17 8vision_model.vision._en.stages.3.blocks.1.mlp.fc2.weight 6vision_model.vision._en.stages.3.blocks.1.mlp.fc2.bias conv2d_56node_conv2d_56"Conv* @@ -2605,64 +2617,64 @@ getitem_33 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.3.blocks.1.mlp: timm.models.fastvit.ConvMlp/vision_model.vision._en.stages.3.blocks.1.mlp.fc2: torch.nn.modules.conv.Conv2d/conv2d_56: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_56 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_22, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.fc2', 'conv2d_56']J -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.fc2', 'conv2d_56']J +pkg.torch.onnx.stack_trace File "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 818, in forward x = self.fc2(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_56 ;vision_model.vision._en.stages.3.blocks.1.layer_scale.gammamul_11 node_mul_11"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.1: timm.models.fastvit.RepMixerBlock/vision_model.vision._en.stages.3.blocks.1.layer_scale: timm.models.fastvit.LayerScale2d/mul_11: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']J pkg.torch.onnx.fx_node%mul_11 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_23, %p_vision_model_vision__en_stages_3_blocks_1_layer_scale_gamma), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.layer_scale', 'mul_11']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.layer_scale', 'mul_11']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 646, in forward return x.mul_(self.gamma) if self.inplace else x * self.gamma - + conv2d_53 mul_11add_11 node_add_11"AddJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.stages.3: timm.models.fastvit.FastVitStage/vision_model.vision._en.stages.3.blocks: torch.nn.modules.container.Sequential/vision_model.vision._en.stages.3.blocks.1: timm.models.fastvit.RepMixerBlock/add_11: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodet%add_11 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_53, %mul_11), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'add_11']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'add_11']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1167, in forward x = self.blocks(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1002, in forward x = x + self.drop_path(self.layer_scale(self.mlp(x))) - + add_11 6vision_model.vision._en.final_conv.reparam_conv.weight 4vision_model.vision._en.final_conv.reparam_conv.bias conv2d_57node_conv2d_57"Conv* @@ -2674,18 +2686,18 @@ getitem_33 namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.final_conv: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.final_conv.reparam_conv: torch.nn.modules.conv.Conv2d/conv2d_57: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_57 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_11, %p_vision_model_vision__en_final_conv_reparam_conv_weight, %p_vision_model_vision__en_final_conv_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 512), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.reparam_conv', 'conv2d_57']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.reparam_conv', 'conv2d_57']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_57 val_190mean node_mean" ReduceMean* @@ -2694,18 +2706,18 @@ ReduceMean* namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.final_conv: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.final_conv.se: timm.layers.squeeze_excite.SEModule/mean: aten.mean.dimJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'aten.mean.dim']J pkg.torch.onnx.fx_nodeu%mean : [num_users=1] = call_function[target=torch.ops.aten.mean.dim](args = (%conv2d_57, [2, 3], True), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'mean']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'mean']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 56, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 56, in forward x_se = x.mean((2, 3), keepdim=True) - + mean 0vision_model.vision._en.final_conv.se.fc1.weight .vision_model.vision._en.final_conv.se.fc1.bias conv2d_58node_conv2d_58"Conv* @@ -2717,38 +2729,38 @@ ReduceMean* namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.final_conv: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.final_conv.se: timm.layers.squeeze_excite.SEModule/vision_model.vision._en.final_conv.se.fc1: torch.nn.modules.conv.Conv2d/conv2d_58: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_58 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%mean, %p_vision_model_vision__en_final_conv_se_fc1_weight, %p_vision_model_vision__en_final_conv_se_fc1_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.fc1', 'conv2d_58']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.fc1', 'conv2d_58']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 60, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 60, in forward x_se = self.fc1(x_se) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_58relu node_relu"ReluJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.final_conv: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.final_conv.se: timm.layers.squeeze_excite.SEModule/vision_model.vision._en.final_conv.se.act: torch.nn.modules.activation.ReLU/relu: aten.relu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J pkg.torch.onnx.fx_nodel%relu : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%conv2d_58,), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.act', 'relu']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.act', 'relu']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 61, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 61, in forward x_se = self.act(self.bn(x_se)) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 143, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 143, in forward return F.relu(input, inplace=self.inplace) - + relu 0vision_model.vision._en.final_conv.se.fc2.weight .vision_model.vision._en.final_conv.se.fc2.bias conv2d_59node_conv2d_59"Conv* @@ -2760,72 +2772,72 @@ ReduceMean* namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.final_conv: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.final_conv.se: timm.layers.squeeze_excite.SEModule/vision_model.vision._en.final_conv.se.fc2: torch.nn.modules.conv.Conv2d/conv2d_59: aten.conv2d.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node%conv2d_59 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%relu, %p_vision_model_vision__en_final_conv_se_fc2_weight, %p_vision_model_vision__en_final_conv_se_fc2_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.fc2', 'conv2d_59']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.fc2', 'conv2d_59']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 62, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 62, in forward x_se = self.fc2(x_se) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/conv.py", line 553, in forward return self._conv_forward(input, self.weight, self.bias) - + conv2d_59sigmoid node_sigmoid"SigmoidJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.final_conv: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.final_conv.se: timm.layers.squeeze_excite.SEModule/vision_model.vision._en.final_conv.se.gate: timm.layers.activations.Sigmoid/sigmoid: aten.sigmoid.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'timm.layers.activations.Sigmoid', 'aten.sigmoid.default']J pkg.torch.onnx.fx_noder%sigmoid : [num_users=1] = call_function[target=torch.ops.aten.sigmoid.default](args = (%conv2d_59,), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.gate', 'sigmoid']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.gate', 'sigmoid']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 63, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 63, in forward return x * self.gate(x_se) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 57, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 57, in forward return x.sigmoid_() if self.inplace else x.sigmoid() - + conv2d_57 sigmoidmul_12 node_mul_12"MulJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.final_conv: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.final_conv.se: timm.layers.squeeze_excite.SEModule/mul_12: aten.mul.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'aten.mul.Tensor']J pkg.torch.onnx.fx_nodeu%mul_12 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%conv2d_57, %sigmoid), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'mul_12']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'mul_12']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 63, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/squeeze_excite.py", line 63, in forward return x * self.gate(x_se) - + mul_12gelu_18 node_gelu_18"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.final_conv: timm.models.fastvit.MobileOneBlock/vision_model.vision._en.final_conv.act: timm.layers.activations.GELUTanh/gelu_18: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J pkg.torch.onnx.fx_node}%gelu_18 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%mul_12,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.act', 'gelu_18']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.act', 'gelu_18']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 155, in forward return self.act(self.se(self.reparam_conv(x))) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/activations.py", line 159, in forward return F.gelu(input, approximate='tanh') - + gelu_18 val_193mean_1 node_mean_1" ReduceMean* @@ -2834,40 +2846,40 @@ ReduceMean* namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.head: timm.layers.classifier.ClassifierHead/vision_model.vision._en.head.global_pool: timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d/vision_model.vision._en.head.global_pool.pool: torch.nn.modules.pooling.AdaptiveAvgPool2d/mean_1: aten.mean.dimJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.layers.classifier.ClassifierHead', 'timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d', 'torch.nn.modules.pooling.AdaptiveAvgPool2d', 'aten.mean.dim']J pkg.torch.onnx.fx_nodew%mean_1 : [num_users=1] = call_function[target=torch.ops.aten.mean.dim](args = (%gelu_18, [-1, -2], True), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.global_pool', 'vision_model.vision._en.head.global_pool.pool', 'mean_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.global_pool', 'vision_model.vision._en.head.global_pool.pool', 'mean_1']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward x = self.forward_head(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 137, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 137, in forward x = self.global_pool(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/adaptive_avgmax_pool.py", line 172, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/adaptive_avgmax_pool.py", line 172, in forward x = self.pool(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/pooling.py", line 1510, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/pooling.py", line 1510, in forward return F.adaptive_avg_pool2d(input, self.output_size) - + mean_1 val_197view node_view"Reshape* allowzeroJ namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.head: timm.layers.classifier.ClassifierHead/vision_model.vision._en.head.global_pool: timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d/vision_model.vision._en.head.global_pool.flatten: torch.nn.modules.flatten.Flatten/view: aten.view.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.layers.classifier.ClassifierHead', 'timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d', 'torch.nn.modules.flatten.Flatten', 'aten.view.default']J pkg.torch.onnx.fx_nodes%view : [num_users=1] = call_function[target=torch.ops.aten.view.default](args = (%mean_1, [1, 1024]), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.global_pool', 'vision_model.vision._en.head.global_pool.flatten', 'view']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.global_pool', 'vision_model.vision._en.head.global_pool.flatten', 'view']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward x = self.forward_head(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 137, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 137, in forward x = self.global_pool(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/adaptive_avgmax_pool.py", line 173, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/adaptive_avgmax_pool.py", line 173, in forward x = self.flatten(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/flatten.py", line 55, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/flatten.py", line 55, in forward return input.flatten(self.start_dim, self.end_dim) - + view &vision_model.vision._en.head.fc.weight $vision_model.vision._en.head.fc.biaslinear node_linear"Gemm* @@ -2878,18 +2890,18 @@ $vision_model.vision._en.head.fc.biaslinear node_linear"Gemm* namespace: __main__.FlattenedVisionModel/vision_model.vision: xx.training.path.supercombo.Vision/vision_model.vision._en: timm.models.fastvit.FastVit/vision_model.vision._en.head: timm.layers.classifier.ClassifierHead/vision_model.vision._en.head.fc: torch.nn.modules.linear.Linear/linear: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.layers.classifier.ClassifierHead', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear : [num_users=3] = call_function[target=torch.ops.aten.linear.default](args = (%clone_24, %p_vision_model_vision__en_head_fc_weight, %p_vision_model_vision__en_head_fc_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.fc', 'linear']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.fc', 'linear']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 191, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 191, in forward return {ModelInputs.FEATURES: self._en((x - self._mean) / self._std)} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward x = self.forward_head(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 141, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/timm/layers/classifier.py", line 141, in forward x = self.fc(x) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + linear ;vision_model.point_policy.summarizer.mlp1.layer_norm.weight 9vision_model.point_policy.summarizer.mlp1.layer_norm.bias @@ -2901,18 +2913,18 @@ stash_type namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.summarizer: xx.training.path.supercombo.PointSummarizer/vision_model.point_policy.summarizer.mlp1: torch.nn.modules.container.Sequential/vision_model.point_policy.summarizer.mlp1.layer_norm: torch.nn.modules.normalization.LayerNorm/layer_norm: aten.layer_norm.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear, [512], %p_vision_model_point_policy_summarizer_mlp1_layer_norm_weight, %p_vision_model_point_policy_summarizer_mlp1_layer_norm_bias, 1e-05, False), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.layer_norm', 'layer_norm']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.layer_norm', 'layer_norm']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx/xx/training/path/supercombo.py", line 32, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 32, in forward x = self.mlp1(x) + x - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward return F.layer_norm( - + layer_norm 5vision_model.point_policy.summarizer.mlp1.c_fc.weightlinear_1 node_linear_1"Gemm* @@ -2923,35 +2935,35 @@ layer_norm namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.summarizer: xx.training.path.supercombo.PointSummarizer/vision_model.point_policy.summarizer.mlp1: torch.nn.modules.container.Sequential/vision_model.point_policy.summarizer.mlp1.c_fc: torch.nn.modules.linear.Linear/linear_1: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_1 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%layer_norm, %p_vision_model_point_policy_summarizer_mlp1_c_fc_weight), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.c_fc', 'linear_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.c_fc', 'linear_1']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx/xx/training/path/supercombo.py", line 32, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 32, in forward x = self.mlp1(x) + x - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + linear_1gelu_19 node_gelu_19"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.summarizer: xx.training.path.supercombo.PointSummarizer/vision_model.point_policy.summarizer.mlp1: torch.nn.modules.container.Sequential/vision_model.point_policy.summarizer.mlp1.act: torch.nn.modules.activation.GELU/gelu_19: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.GELU', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_19 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%linear_1,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.act', 'gelu_19']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.act', 'gelu_19']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx/xx/training/path/supercombo.py", line 32, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 32, in forward x = self.mlp1(x) + x - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward return F.gelu(input, approximate=self.approximate) - + gelu_19 7vision_model.point_policy.summarizer.mlp1.c_proj.weightlinear_2 node_linear_2"Gemm* beta?* @@ -2961,31 +2973,31 @@ layer_norm namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.summarizer: xx.training.path.supercombo.PointSummarizer/vision_model.point_policy.summarizer.mlp1: torch.nn.modules.container.Sequential/vision_model.point_policy.summarizer.mlp1.c_proj: torch.nn.modules.linear.Linear/linear_2: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_2 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%gelu_19, %p_vision_model_point_policy_summarizer_mlp1_c_proj_weight), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.c_proj', 'linear_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp1', 'vision_model.point_policy.summarizer.mlp1.c_proj', 'linear_2']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx/xx/training/path/supercombo.py", line 32, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 32, in forward x = self.mlp1(x) + x - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + linear_2 linearadd_12 node_add_12"AddJ namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.summarizer: xx.training.path.supercombo.PointSummarizer/add_12: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodes%add_12 : [num_users=2] = call_function[target=torch.ops.aten.add.Tensor](args = (%clone_25, %linear), kwargs = {})Jq -pkg.torch.onnx.name_scopesS['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'add_12']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopesS['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'add_12']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx/xx/training/path/supercombo.py", line 32, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 32, in forward x = self.mlp1(x) + x - + add_12 ;vision_model.point_policy.summarizer.mlp2.layer_norm.weight 9vision_model.point_policy.summarizer.mlp2.layer_norm.bias layer_norm_1node_layer_norm_1"LayerNormalization* @@ -2996,18 +3008,18 @@ stash_type namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.summarizer: xx.training.path.supercombo.PointSummarizer/vision_model.point_policy.summarizer.mlp2: torch.nn.modules.container.Sequential/vision_model.point_policy.summarizer.mlp2.layer_norm: torch.nn.modules.normalization.LayerNorm/layer_norm_1: aten.layer_norm.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm_1 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%add_12, [512], %p_vision_model_point_policy_summarizer_mlp2_layer_norm_weight, %p_vision_model_point_policy_summarizer_mlp2_layer_norm_bias, 1e-05, False), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.layer_norm', 'layer_norm_1']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.layer_norm', 'layer_norm_1']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx/xx/training/path/supercombo.py", line 33, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 33, in forward x = self.mlp2(x) + x - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward return F.layer_norm( - + layer_norm_1 5vision_model.point_policy.summarizer.mlp2.c_fc.weightlinear_3 node_linear_3"Gemm* beta?* @@ -3017,35 +3029,35 @@ stash_type namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.summarizer: xx.training.path.supercombo.PointSummarizer/vision_model.point_policy.summarizer.mlp2: torch.nn.modules.container.Sequential/vision_model.point_policy.summarizer.mlp2.c_fc: torch.nn.modules.linear.Linear/linear_3: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_3 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%layer_norm_1, %p_vision_model_point_policy_summarizer_mlp2_c_fc_weight), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.c_fc', 'linear_3']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.c_fc', 'linear_3']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx/xx/training/path/supercombo.py", line 33, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 33, in forward x = self.mlp2(x) + x - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + linear_3gelu_20 node_gelu_20"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.summarizer: xx.training.path.supercombo.PointSummarizer/vision_model.point_policy.summarizer.mlp2: torch.nn.modules.container.Sequential/vision_model.point_policy.summarizer.mlp2.act: torch.nn.modules.activation.GELU/gelu_20: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.GELU', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_20 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%linear_3,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.act', 'gelu_20']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.act', 'gelu_20']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx/xx/training/path/supercombo.py", line 33, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 33, in forward x = self.mlp2(x) + x - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward return F.gelu(input, approximate=self.approximate) - + gelu_20 7vision_model.point_policy.summarizer.mlp2.c_proj.weightlinear_4 node_linear_4"Gemm* beta?* @@ -3055,31 +3067,31 @@ stash_type namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.summarizer: xx.training.path.supercombo.PointSummarizer/vision_model.point_policy.summarizer.mlp2: torch.nn.modules.container.Sequential/vision_model.point_policy.summarizer.mlp2.c_proj: torch.nn.modules.linear.Linear/linear_4: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_4 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%gelu_20, %p_vision_model_point_policy_summarizer_mlp2_c_proj_weight), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.c_proj', 'linear_4']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.mlp2', 'vision_model.point_policy.summarizer.mlp2.c_proj', 'linear_4']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx/xx/training/path/supercombo.py", line 33, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 33, in forward x = self.mlp2(x) + x - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + linear_4 add_12add_13 node_add_13"AddJ namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.summarizer: xx.training.path.supercombo.PointSummarizer/add_13: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodes%add_13 : [num_users=9] = call_function[target=torch.ops.aten.add.Tensor](args = (%clone_26, %add_12), kwargs = {})Jq -pkg.torch.onnx.name_scopesS['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'add_13']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopesS['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'add_13']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 125, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 125, in forward summary_outs = self.summarizer(vision_features) - File "/home/batman/xx/xx/training/path/supercombo.py", line 33, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 33, in forward x = self.mlp2(x) + x - + add_13 ?vision_model.point_policy.hydra.head_mlp.pose.layer_norm.weight =vision_model.point_policy.hydra.head_mlp.pose.layer_norm.bias layer_norm_2node_layer_norm_2"LayerNormalization* @@ -3090,18 +3102,18 @@ stash_type namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.hydra: xx.training.path.supercombo.Hydra/vision_model.point_policy.hydra.head_mlp.pose: torch.nn.modules.container.Sequential/vision_model.point_policy.hydra.head_mlp.pose.layer_norm: torch.nn.modules.normalization.LayerNorm/layer_norm_2: aten.layer_norm.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node%layer_norm_2 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%add_13, [512], %p_vision_model_point_policy_hydra_head_mlp_pose_layer_norm_weight, %p_vision_model_point_policy_hydra_head_mlp_pose_layer_norm_bias, 1e-05, False), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.layer_norm', 'layer_norm_2']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.layer_norm', 'layer_norm_2']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx/xx/training/path/supercombo.py", line 105, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 105, in forward k: self.head_mlp[k](in_feats) + in_feats if k in self.head_mlp else in_feats - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/normalization.py", line 229, in forward return F.layer_norm( - + layer_norm_2 9vision_model.point_policy.hydra.head_mlp.pose.c_fc.weightlinear_5 node_linear_5"Gemm* beta?* @@ -3111,35 +3123,35 @@ stash_type namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.hydra: xx.training.path.supercombo.Hydra/vision_model.point_policy.hydra.head_mlp.pose: torch.nn.modules.container.Sequential/vision_model.point_policy.hydra.head_mlp.pose.c_fc: torch.nn.modules.linear.Linear/linear_5: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_5 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%layer_norm_2, %p_vision_model_point_policy_hydra_head_mlp_pose_c_fc_weight), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.c_fc', 'linear_5']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.c_fc', 'linear_5']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx/xx/training/path/supercombo.py", line 105, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 105, in forward k: self.head_mlp[k](in_feats) + in_feats if k in self.head_mlp else in_feats - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + linear_5gelu_21 node_gelu_21"Gelu* approximate"tanhJ namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.hydra: xx.training.path.supercombo.Hydra/vision_model.point_policy.hydra.head_mlp.pose: torch.nn.modules.container.Sequential/vision_model.point_policy.hydra.head_mlp.pose.act: torch.nn.modules.activation.GELU/gelu_21: aten.gelu.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.GELU', 'aten.gelu.default']J pkg.torch.onnx.fx_node%gelu_21 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%linear_5,), kwargs = {approximate: tanh})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.act', 'gelu_21']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.act', 'gelu_21']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx/xx/training/path/supercombo.py", line 105, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 105, in forward k: self.head_mlp[k](in_feats) + in_feats if k in self.head_mlp else in_feats - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/activation.py", line 816, in forward return F.gelu(input, approximate=self.approximate) - + gelu_21 ;vision_model.point_policy.hydra.head_mlp.pose.c_proj.weightlinear_6 node_linear_6"Gemm* beta?* @@ -3149,31 +3161,31 @@ stash_type namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.hydra: xx.training.path.supercombo.Hydra/vision_model.point_policy.hydra.head_mlp.pose: torch.nn.modules.container.Sequential/vision_model.point_policy.hydra.head_mlp.pose.c_proj: torch.nn.modules.linear.Linear/linear_6: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_6 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%gelu_21, %p_vision_model_point_policy_hydra_head_mlp_pose_c_proj_weight), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.c_proj', 'linear_6']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.head_mlp.pose', 'vision_model.point_policy.hydra.head_mlp.pose.c_proj', 'linear_6']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx/xx/training/path/supercombo.py", line 105, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 105, in forward k: self.head_mlp[k](in_feats) + in_feats if k in self.head_mlp else in_feats - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/container.py", line 253, in forward input = module(input) - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + linear_6 add_13add_14 node_add_14"AddJ namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.hydra: xx.training.path.supercombo.Hydra/add_14: aten.add.TensorJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodes%add_14 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%clone_27, %add_13), kwargs = {})Jl -pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_14']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_14']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx/xx/training/path/supercombo.py", line 105, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 105, in forward k: self.head_mlp[k](in_feats) + in_feats if k in self.head_mlp else in_feats - + add_13 =vision_model.point_policy.hydra.final_layer.lane_lines.weight ;vision_model.point_policy.hydra.final_layer.lane_lines.biaslinear_7 node_linear_7"Gemm* @@ -3184,16 +3196,16 @@ stash_type namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.hydra: xx.training.path.supercombo.Hydra/vision_model.point_policy.hydra.final_layer.lane_lines: torch.nn.modules.linear.Linear/linear_7: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_7 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %p_vision_model_point_policy_hydra_final_layer_lane_lines_weight, %p_vision_model_point_policy_hydra_final_layer_lane_lines_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.lane_lines', 'linear_7']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.lane_lines', 'linear_7']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + add_13 Bvision_model.point_policy.hydra.final_layer.lane_lines_prob.weight @vision_model.point_policy.hydra.final_layer.lane_lines_prob.biaslinear_8 node_linear_8"Gemm* @@ -3204,16 +3216,16 @@ Bvision_model.point_policy.hydra.final_layer.lane_lines_prob.weight namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.hydra: xx.training.path.supercombo.Hydra/vision_model.point_policy.hydra.final_layer.lane_lines_prob: torch.nn.modules.linear.Linear/linear_8: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_8 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %p_vision_model_point_policy_hydra_final_layer_lane_lines_prob_weight, %p_vision_model_point_policy_hydra_final_layer_lane_lines_prob_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.lane_lines_prob', 'linear_8']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.lane_lines_prob', 'linear_8']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + add_13 =vision_model.point_policy.hydra.final_layer.road_edges.weight ;vision_model.point_policy.hydra.final_layer.road_edges.biaslinear_9 node_linear_9"Gemm* @@ -3224,16 +3236,16 @@ Bvision_model.point_policy.hydra.final_layer.lane_lines_prob.weight namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.hydra: xx.training.path.supercombo.Hydra/vision_model.point_policy.hydra.final_layer.road_edges: torch.nn.modules.linear.Linear/linear_9: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_9 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %p_vision_model_point_policy_hydra_final_layer_road_edges_weight, %p_vision_model_point_policy_hydra_final_layer_road_edges_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.road_edges', 'linear_9']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.road_edges', 'linear_9']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + add_13 7vision_model.point_policy.hydra.final_layer.meta.weight 5vision_model.point_policy.hydra.final_layer.meta.bias linear_10node_linear_10"Gemm* @@ -3244,16 +3256,16 @@ Bvision_model.point_policy.hydra.final_layer.lane_lines_prob.weight namespace: __main__.FlattenedVisionModel/vision_model.point_policy: xx.training.path.supercombo.Policy/vision_model.point_policy.hydra: xx.training.path.supercombo.Hydra/vision_model.point_policy.hydra.final_layer.meta: torch.nn.modules.linear.Linear/linear_10: aten.linear.defaultJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_node%linear_10 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%add_13, %p_vision_model_point_policy_hydra_final_layer_meta_weight, %p_vision_model_point_policy_hydra_final_layer_meta_bias), kwargs = {})J -pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.meta', 'linear_10']J -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward +pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.meta', 'linear_10']J +pkg.torch.onnx.stack_traceFile "/home/batman/xx2/./ml_tools/openpilot_compile/compile_supercombo.py", line 82, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 126, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 126, in forward policy_outs = self.hydra(summary_outs) - File "/home/batman/xx/xx/training/path/supercombo.py", line 108, in forward + File "/home/batman/xx2/xx/training/path/supercombo.py", line 108, in forward ret = {k: v(head_feats[k]) for k,v in self.final_layer.items()} - File "/home/batman/xx/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward + File "/home/batman/xx2/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 134, in forward return F.linear(input, self.weight, self.bias) - + add_13 >vision_model.point_policy.hydra.final_layer.desire_pred.weight