Files
sunnypilot/release/ci/model_generator.py
T
James Vecellio-Grant 94a32493e3 modeld_v2: chestnut support (#1894)
* modeld_v2: Support eGpu

* bump tg

* egpu

* no pkls please

* god no onnx either

* fix test

* done in build model now

* lint

* rip

* egpu ready build all split

* manual seed , reuse memory buffers across runs

* dont download big when we dont have big lol

* whoops

* no i and x

* cd

* who put those there. ??

* reduce flakiness by using artifact-name from build-model to regex, speed up pub b y checking the name before trying to clone and publish again

* try hf as a trusted publisher :)

* mf its a dataaset. i knew that

* fucking validation wants raw to fetch and full to push. grr

* smh

* dude i am missing so much

* pkl name

* move build all to hf

* tests: migrate sunnypilot tests to unittest and remove pytest

* red diff mf

* im scared , this may be a bad idea lol

* fetch latest commit.

* transition to requests

* models: use requests instead of aiohttp

* tici

* fix

* gpu fixes from upstream

* lint

* bump

* needed to say

* old

* how??

* epgu flag reduce

* this made me cry

* support monolith still

* precache warp in legacy

* Move jsons to param for sunnylink

---------

Co-authored-by: Jason Wen <haibin.wen3@gmail.com>
2026-08-16 21:40:16 -04:00

178 lines
5.9 KiB
Python
Executable File

"""
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 _read_pkl_bytes(pkl_path: Path) -> bytes:
manifest = Path(f"{pkl_path}.chunkmanifest")
if manifest.exists():
num_chunks = int(manifest.read_text().strip())
parts = []
for i in range(num_chunks):
chunk = Path(f"{pkl_path}.chunk{i + 1:02d}of{num_chunks:02d}")
parts.append(chunk.read_bytes())
return b''.join(parts)
return pkl_path.read_bytes()
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 generate_chunked_model(driving_pkl: Path) -> dict:
tinygrad_hash = hashlib.sha256(_read_pkl_bytes(driving_pkl)).hexdigest()
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") -> 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": {},
"models": models,
}
# 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)
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)
create_metadata_json([_model_metadata], _output_dir, args.custom_name, _short_name, args.is_20hz, args.upstream_branch)