mirror of
https://github.com/sunnypilot/sunnypilot.git
synced 2026-06-20 01:02:07 +08:00
Jason Wen
10a33a4bf1
* Reapply "bump tg (#37700)" This reverts commit9022b4d322. * fixup! Reapply "bump tg (#37700)" * Revert "Revert "autodetect tg backend (#37778)"" This reverts commitb782958a* Reapply "autodetect tg backend: use CPU:LLVM on Linux (#37785)" This reverts commit3fa6726f88. * Reapply "Modeld: support uncompiled" This reverts commit8c240cc1a4. * fixup! Reapply "bump tg (#37700)" * fixup! Reapply "autodetect tg backend: use CPU:LLVM on Linux (#37785)" * fixup! Revert "Revert "autodetect tg backend (#37778)"" * fixup! Reapply "autodetect tg backend: use CPU:LLVM on Linux (#37785)" * fixup! Reapply "autodetect tg backend: use CPU:LLVM on Linux (#37785)" * fixup! Revert "Revert "autodetect tg backend (#37778)"" * fixup! Reapply "bump tg (#37700)" * fixup! Reapply "bump tg (#37700)"
89 lines
3.5 KiB
Python
89 lines
3.5 KiB
Python
import glob
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import json
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import os
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from SCons.Script import Value
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from openpilot.common.file_chunker import chunk_file, get_chunk_paths
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from tinygrad import Device
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Import('env', 'arch')
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chunker_file = File("#common/file_chunker.py")
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lenv = env.Clone()
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tinygrad_root = env.Dir("#").abspath
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tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "/**", recursive=True, root_dir=tinygrad_root)
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if 'pycache' not in x and os.path.isfile(os.path.join(tinygrad_root, x))]
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def estimate_pickle_max_size(onnx_size):
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return 1.2 * onnx_size + 10 * 1024 * 1024 # 20% + 10MB is plenty
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# THREADS=0 is need to prevent bug: https://github.com/tinygrad/tinygrad/issues/14689
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# get fastest TG config
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available = set(Device.get_available_devices())
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# FIXME-SP: reset when we bump tg
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if False: # 'CUDA' in available:
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tg_backend = 'CUDA'
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tg_flags = f'DEV={tg_backend}'
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elif 'QCOM' in available:
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tg_backend = 'QCOM'
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tg_flags = f'DEV={tg_backend} FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0'
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else:
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tg_backend = 'CPU' if arch == 'Darwin' else 'CPU CPU_LLVM=1' # FIXME-SP: reset when we bump tg
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tg_flags = f'DEV={tg_backend} THREADS=0'
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def write_tg_compiled_flags(target, source, env):
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with open(str(target[0]), "w") as f:
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json.dump({"DEV": tg_backend}, f)
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f.write("\n")
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compiled_flags_node = lenv.Command(
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File("models/tg_compiled_flags.json").abspath,
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tinygrad_files + [Value(tg_backend)],
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write_tg_compiled_flags,
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)
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# tinygrad calls brew which needs a $HOME in the env
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mac_brew_string = f'HOME={os.path.expanduser("~")}' if arch == 'Darwin' else ''
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# Get model metadata
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for model_name in ['driving_vision', 'driving_policy', 'dmonitoring_model']:
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fn = File(f"models/{model_name}").abspath
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script_files = [File(Dir("#selfdrive/modeld").File("get_model_metadata.py").abspath)]
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cmd = f'{tg_flags} {mac_brew_string} python3 {Dir("#selfdrive/modeld").abspath}/get_model_metadata.py {fn}.onnx'
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lenv.Command(fn + "_metadata.pkl", [fn + ".onnx"] + tinygrad_files + script_files + [compiled_flags_node], cmd)
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image_flag = {
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'larch64': 'IMAGE=2',
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}.get(arch, 'IMAGE=0')
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script_files = [File(Dir("#selfdrive/modeld").File("compile_warp.py").abspath)]
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compile_warp_cmd = f'{tg_flags} {mac_brew_string} python3 {Dir("#selfdrive/modeld").abspath}/compile_warp.py '
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from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
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warp_targets = []
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for cam in [_ar_ox_fisheye, _os_fisheye]:
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w, h = cam.width, cam.height
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warp_targets += [File(f"models/warp_{w}x{h}_tinygrad.pkl").abspath, File(f"models/dm_warp_{w}x{h}_tinygrad.pkl").abspath]
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lenv.Command(warp_targets, tinygrad_files + script_files + [compiled_flags_node], compile_warp_cmd)
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def tg_compile(flags, model_name):
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pythonpath_string = 'PYTHONPATH="${PYTHONPATH}:' + env.Dir("#tinygrad_repo").abspath + '"'
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fn = File(f"models/{model_name}").abspath
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pkl = fn + "_tinygrad.pkl"
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onnx_path = fn + ".onnx"
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chunk_targets = get_chunk_paths(pkl, estimate_pickle_max_size(os.path.getsize(onnx_path)))
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compile_node = lenv.Command(
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pkl,
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[onnx_path] + tinygrad_files + [chunker_file, compiled_flags_node],
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f'{pythonpath_string} {flags} {image_flag} python3 {Dir("#tinygrad_repo").abspath}/examples/openpilot/compile3.py {fn}.onnx {pkl}',
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)
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def do_chunk(target, source, env):
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chunk_file(pkl, chunk_targets)
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return lenv.Command(
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chunk_targets,
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compile_node,
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do_chunk,
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)
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# Compile small models
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for model_name in ['driving_vision', 'driving_policy', 'dmonitoring_model']:
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tg_compile(tg_flags, model_name)
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