Files
sunnypilot/release/ci/model_generator.py
T
James Vecellio-Grant 45814e3313 modeld_v2: spatial features (#1934)
* modeld_v2: spatial features

* Update fetcher.py

* dont reshape non 4 dim arrays

* realize for non compiled

* Update compile_modeld.py

* god dammit it was realize()

* it was fucking frozen tinygrad. just need to recompile

* bump

* ci: add is_big flag to metadata.json to support backward compat

* Update model_generator.py

* Update sunnypilot-build-model.yaml

* Update helpers.py

* Revert "Update helpers.py"

This reverts commit 3a955ca11a.

* Reapply "Update helpers.py"

This reverts commit ca9c6e1933.

* models: use less strict chestnut detection state

---------

Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
2026-08-24 22:52:29 -04:00

203 lines
6.5 KiB
Python
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"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
This file is part of sunnypilot and is licensed under the MIT License.
See the LICENSE.md file in the root directory for more details.
"""
import sys
import hashlib
import json
import re
from pathlib import Path
from datetime import datetime, UTC
def create_short_name(full_name: str) -> str:
# Remove parentheses and extract alphanumeric words
clean_name = re.sub(r'\([^)]*\)', '', full_name)
words = [re.sub(r'[^a-zA-Z0-9]', '', word) for word in clean_name.split() if re.sub(r'[^a-zA-Z0-9]', '', word)]
if len(words) == 1:
return words[0][:8].upper()
# Handle special case: Name + Version (e.g., "Word A1" -> "WordA1")
if len(words) == 2 and re.match(r'^[A-Za-z]\d+$', words[1]):
return (words[0] + words[1])[:8].upper()
result = ""
for word in words:
# Version or number patterns
if (re.match(r'^\d+[a-zA-Z]+$', word) or
re.match(r'^\d+[vVbB]\d+$', word) or
re.match(r'^[vVbB]\d+$', word) or
re.match(r'^\d{4}$', word)):
result += word.upper()
# All uppercase abbreviations (2-3 letters)
elif re.match(r'^[A-Z]{2,3}$', word):
result += word
# Letters+digits (for example tr15 rev2)
elif re.match(r'^[a-zA-Z]+[0-9]+$', word):
result += word[0].upper() + ''.join(re.findall(r'\d+', word))
elif word.isalpha():
result += word[0].upper()
elif word.isdigit():
result += word
else:
result += word[0].upper()
return result[:8]
def create_pkl_name(full_name: str) -> str:
pkl = re.sub(r'[^a-zA-Z0-9]+', '_', full_name).strip('_').lower()
return pkl
def _hash_pkl(pkl_path: Path) -> str:
manifest = Path(f"{pkl_path}.chunkmanifest")
if manifest.exists():
num_chunks = int(manifest.read_text().strip())
paths = [Path(f"{pkl_path}.chunk{i + 1:02d}of{num_chunks:02d}") for i in range(num_chunks)]
else:
paths = [pkl_path]
digest = hashlib.sha256()
for path in paths:
with path.open('rb') as f:
while block := f.read(1024 * 1024):
digest.update(block)
return digest.hexdigest()
def _find_driving_pkl(output_path: Path) -> Path | None:
for pattern in ('*driving_tinygrad.pkl', '*driving_*_tinygrad.pkl'):
matches = sorted(output_path.glob(pattern))
if matches:
return matches[0]
for pattern in ('*driving_tinygrad.pkl.chunkmanifest', '*driving_*_tinygrad.pkl.chunkmanifest'):
matches = sorted(output_path.glob(pattern))
if matches:
return Path(str(matches[0]).removesuffix('.chunkmanifest'))
return None
def _rename_pkl_with_chunks(old_pkl: Path, new_pkl: Path) -> Path:
manifest = Path(f"{old_pkl}.chunkmanifest")
if manifest.exists():
for f in sorted(old_pkl.parent.glob(f"{old_pkl.name}.chunk*")):
f.rename(old_pkl.parent / f.name.replace(old_pkl.name, new_pkl.name, 1))
return new_pkl
return old_pkl.rename(new_pkl)
def _hash_onnx_files(model_dir: Path) -> str | None:
onnx_files = sorted(model_dir.glob("*.onnx"))
if not onnx_files:
return None
digest = hashlib.sha256()
for f in onnx_files:
with f.open('rb') as fh:
while block := fh.read(1024 * 1024):
digest.update(block)
return digest.hexdigest()
def generate_chunked_model(driving_pkl: Path) -> dict:
tinygrad_hash = _hash_pkl(driving_pkl)
chunks_config = []
manifest_file = Path(f"{driving_pkl}.chunkmanifest")
if manifest_file.exists():
num_chunks = int(manifest_file.read_text().strip())
for i in range(num_chunks):
chunk_path = Path(f"{driving_pkl}.chunk{i + 1:02d}of{num_chunks:02d}")
if chunk_path.exists():
chunk_hash = hashlib.sha256(chunk_path.read_bytes()).hexdigest()
chunks_config.append({
"file_name": chunk_path.name,
"sha256": chunk_hash
})
artifact_data = {
"file_name": driving_pkl.name,
"download_uri": {
"url": "https://gitlab.com/sunnypilot/public/docs.sunnypilot.ai/-/raw/main/",
"sha256": tinygrad_hash
}
}
if chunks_config:
artifact_data["chunks"] = chunks_config
return {
"type": "chunked",
"artifact": artifact_data,
}
def create_metadata_json(models: list, output_dir: Path, custom_name=None, short_name=None, is_20hz=False, upstream_branch="unknown",
onnx_sha256=None, is_big=False) -> None:
bundle_json = {
"short_name": short_name,
"display_name": custom_name or upstream_branch,
"is_20hz": is_20hz,
"ref": upstream_branch,
"environment": "development",
"runner": "tinygrad",
"index": -1,
"minimum_selector_version": "-1",
"generation": "-1",
"build_time": datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ"),
"overrides": {},
"is_big": is_big,
"models": models,
}
if onnx_sha256:
bundle_json["onnx_sha256"] = onnx_sha256
# Write metadata to output_dir
metadata_json = {
"bundles": [bundle_json]
}
with open(output_dir / "metadata.json", "w") as f:
json.dump(metadata_json, f, indent=2)
print("Generated metadata.json")
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(description="Generate metadata JSON for the compiled JIT model")
parser.add_argument("--model-dir", default="./models", help="Directory containing the model files")
parser.add_argument("--output-dir", default="./output", help="Output directory for metadata")
parser.add_argument("--custom-name", help="Custom display name for the model")
parser.add_argument("--is-20hz", action="store_true", help="Whether this is a 20Hz model")
parser.add_argument("--upstream-branch", default="unknown", help="Upstream branch name")
args = parser.parse_args()
_output_dir = Path(args.output_dir)
_output_dir.mkdir(exist_ok=True, parents=True)
_short_name = create_short_name(args.custom_name) if args.custom_name else None
_pkl = create_pkl_name(args.custom_name) if args.custom_name else None
_driving_pkl = _find_driving_pkl(_output_dir)
if not _driving_pkl:
print(f"No driving_tinygrad.pkl found in {_output_dir}", file=sys.stderr)
sys.exit(1)
is_big = _driving_pkl.name.startswith('big_')
if _pkl:
new_pkl = _output_dir / f"driving_{_pkl}_tinygrad.pkl"
if not new_pkl.exists():
_driving_pkl = _rename_pkl_with_chunks(_driving_pkl, new_pkl)
else:
_driving_pkl = new_pkl
_model_metadata = generate_chunked_model(_driving_pkl)
_onnx_sha256 = _hash_onnx_files(Path(args.model_dir))
create_metadata_json([_model_metadata], _output_dir, args.custom_name, _short_name, args.is_20hz, args.upstream_branch,
onnx_sha256=_onnx_sha256, is_big=is_big)