mirror of
https://github.com/sunnypilot/sunnypilot.git
synced 2026-02-18 11:53:57 +08:00
Chunk big model files (#37134)
* file chunking * try this * more cleanup * cleaner
This commit is contained in:
2
.gitignore
vendored
2
.gitignore
vendored
@@ -64,7 +64,7 @@ flycheck_*
|
||||
cppcheck_report.txt
|
||||
comma*.sh
|
||||
|
||||
selfdrive/modeld/models/*.pkl
|
||||
selfdrive/modeld/models/*.pkl*
|
||||
|
||||
# openpilot log files
|
||||
*.bz2
|
||||
|
||||
27
common/file_chunker.py
Normal file
27
common/file_chunker.py
Normal file
@@ -0,0 +1,27 @@
|
||||
import glob
|
||||
import os
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
CHUNK_SIZE = 49 * 1024 * 1024 # 49MB, under GitHub's 50MB limit
|
||||
|
||||
|
||||
def chunk_file(path):
|
||||
with open(path, 'rb') as f:
|
||||
data = f.read()
|
||||
for i in range(0, len(data), CHUNK_SIZE):
|
||||
with open(f"{path}.chunk{i // CHUNK_SIZE:02d}", 'wb') as f:
|
||||
f.write(data[i:i + CHUNK_SIZE])
|
||||
os.remove(path)
|
||||
|
||||
|
||||
def read_file_chunked(path):
|
||||
files = sorted(glob.glob(f"{path}.chunk*")) or ([path] if os.path.isfile(path) else [])
|
||||
if not files:
|
||||
raise FileNotFoundError(path)
|
||||
return b''.join(Path(f).read_bytes() for f in files)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
for path in sys.argv[1:]:
|
||||
chunk_file(path)
|
||||
@@ -8,6 +8,8 @@ tinygrad_root = env.Dir("#").abspath
|
||||
tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "/**", recursive=True, root_dir=tinygrad_root)
|
||||
if 'pycache' not in x and os.path.isfile(os.path.join(tinygrad_root, x))]
|
||||
|
||||
chunk_cmd = f'python3 {Dir("#common").abspath}/file_chunker.py'
|
||||
|
||||
# Get model metadata
|
||||
for model_name in ['driving_vision', 'driving_policy', 'dmonitoring_model']:
|
||||
fn = File(f"models/{model_name}").abspath
|
||||
@@ -24,21 +26,23 @@ image_flag = {
|
||||
'larch64': 'IMAGE=2',
|
||||
}.get(arch, 'IMAGE=0')
|
||||
script_files = [File(Dir("#selfdrive/modeld").File("compile_warp.py").abspath)]
|
||||
cmd = f'{tg_flags} python3 {Dir("#selfdrive/modeld").abspath}/compile_warp.py '
|
||||
compile_warp_cmd = f'{tg_flags} python3 {Dir("#selfdrive/modeld").abspath}/compile_warp.py '
|
||||
from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
|
||||
warp_targets = []
|
||||
for cam in [_ar_ox_fisheye, _os_fisheye]:
|
||||
w, h = cam.width, cam.height
|
||||
warp_targets += [File(f"models/warp_{w}x{h}_tinygrad.pkl").abspath, File(f"models/dm_warp_{w}x{h}_tinygrad.pkl").abspath]
|
||||
lenv.Command(warp_targets, tinygrad_files + script_files, cmd)
|
||||
lenv.Command([t + ".chunk00" for t in warp_targets], tinygrad_files + script_files,
|
||||
f'{compile_warp_cmd} && {chunk_cmd} {" ".join(warp_targets)}')
|
||||
|
||||
def tg_compile(flags, model_name):
|
||||
pythonpath_string = 'PYTHONPATH="${PYTHONPATH}:' + env.Dir("#tinygrad_repo").abspath + '"'
|
||||
fn = File(f"models/{model_name}").abspath
|
||||
pkl = fn + "_tinygrad.pkl"
|
||||
return lenv.Command(
|
||||
fn + "_tinygrad.pkl",
|
||||
pkl + ".chunk00",
|
||||
[fn + ".onnx"] + tinygrad_files,
|
||||
f'{pythonpath_string} {flags} {image_flag} python3 {Dir("#tinygrad_repo").abspath}/examples/openpilot/compile3.py {fn}.onnx {fn}_tinygrad.pkl'
|
||||
f'{pythonpath_string} {flags} {image_flag} python3 {Dir("#tinygrad_repo").abspath}/examples/openpilot/compile3.py {fn}.onnx {pkl} && {chunk_cmd} {pkl}'
|
||||
)
|
||||
|
||||
# Compile small models
|
||||
|
||||
@@ -16,6 +16,7 @@ from openpilot.common.realtime import config_realtime_process
|
||||
from openpilot.common.transformations.model import dmonitoringmodel_intrinsics
|
||||
from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
|
||||
from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
|
||||
from openpilot.common.file_chunker import read_file_chunked
|
||||
from openpilot.selfdrive.modeld.parse_model_outputs import sigmoid, safe_exp
|
||||
|
||||
PROCESS_NAME = "selfdrive.modeld.dmonitoringmodeld"
|
||||
@@ -43,8 +44,7 @@ class ModelState:
|
||||
self.frame_buf_params = None
|
||||
self.tensor_inputs = {k: Tensor(v, device='NPY').realize() for k,v in self.numpy_inputs.items()}
|
||||
self.image_warp = None
|
||||
with open(MODEL_PKL_PATH, "rb") as f:
|
||||
self.model_run = pickle.load(f)
|
||||
self.model_run = pickle.loads(read_file_chunked(str(MODEL_PKL_PATH)))
|
||||
|
||||
def run(self, buf: VisionBuf, calib: np.ndarray, transform: np.ndarray) -> tuple[np.ndarray, float]:
|
||||
self.numpy_inputs['calib'][0,:] = calib
|
||||
@@ -54,8 +54,7 @@ class ModelState:
|
||||
if self.image_warp is None:
|
||||
self.frame_buf_params = get_nv12_info(buf.width, buf.height)
|
||||
warp_path = MODELS_DIR / f'dm_warp_{buf.width}x{buf.height}_tinygrad.pkl'
|
||||
with open(warp_path, "rb") as f:
|
||||
self.image_warp = pickle.load(f)
|
||||
self.image_warp = pickle.loads(read_file_chunked(str(warp_path)))
|
||||
self.warp_inputs['frame'] = Tensor.from_blob(buf.data.ctypes.data, (self.frame_buf_params[3],), dtype='uint8').realize()
|
||||
|
||||
self.warp_inputs_np['transform'][:] = transform[:]
|
||||
|
||||
@@ -27,6 +27,7 @@ from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper
|
||||
from openpilot.selfdrive.controls.lib.drive_helpers import get_accel_from_plan, smooth_value, get_curvature_from_plan
|
||||
from openpilot.selfdrive.modeld.parse_model_outputs import Parser
|
||||
from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState
|
||||
from openpilot.common.file_chunker import read_file_chunked
|
||||
from openpilot.selfdrive.modeld.constants import ModelConstants, Plan
|
||||
|
||||
|
||||
@@ -177,11 +178,8 @@ class ModelState:
|
||||
self.frame_buf_params : dict[str, tuple[int, int, int, int]] = {}
|
||||
self.update_imgs = None
|
||||
|
||||
with open(VISION_PKL_PATH, "rb") as f:
|
||||
self.vision_run = pickle.load(f)
|
||||
|
||||
with open(POLICY_PKL_PATH, "rb") as f:
|
||||
self.policy_run = pickle.load(f)
|
||||
self.vision_run = pickle.loads(read_file_chunked(str(VISION_PKL_PATH)))
|
||||
self.policy_run = pickle.loads(read_file_chunked(str(POLICY_PKL_PATH)))
|
||||
|
||||
def slice_outputs(self, model_outputs: np.ndarray, output_slices: dict[str, slice]) -> dict[str, np.ndarray]:
|
||||
parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in output_slices.items()}
|
||||
@@ -198,8 +196,7 @@ class ModelState:
|
||||
w, h = bufs[key].width, bufs[key].height
|
||||
self.frame_buf_params[key] = get_nv12_info(w, h)
|
||||
warp_path = MODELS_DIR / f'warp_{w}x{h}_tinygrad.pkl'
|
||||
with open(warp_path, "rb") as f:
|
||||
self.update_imgs = pickle.load(f)
|
||||
self.update_imgs = pickle.loads(read_file_chunked(str(warp_path)))
|
||||
|
||||
|
||||
for key in bufs.keys():
|
||||
|
||||
Reference in New Issue
Block a user