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cad17b1255
* WIP try modeld all in python * fix plan * add lane lines stds * fix lane lines prob * add lead prob * add meta * simplify plan parsing * add hard brake pred * add confidence * fix desire state and desire pred * check this file for now * rm prints * rm debug * add todos * add plan_t_idxs * same as cpp * removed cython * add wfd width - rm cpp code * add new files rm old files * get metadata at compile time * forgot this file * now uses more CPU * not used * update readme * lint * copy this too * simplify disengage probs * update model replay ref commit * update again * confidence: remove if statemens * use publish_state.enqueue * Revert "use publish_state.enqueue" This reverts commit d8807c8348338a1f773a8de00fd796abb8181404. * confidence: better shape defs * use ModelConstants class * fix confidence * Parser * slightly more power too * no inline ifs :( * confidence: just use if statements
30 lines
1.0 KiB
Python
Executable File
30 lines
1.0 KiB
Python
Executable File
#!/usr/bin/env python3
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import sys
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import pathlib
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import onnx
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import codecs
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import pickle
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from typing import Tuple
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def get_name_and_shape(value_info:onnx.ValueInfoProto) -> Tuple[str, Tuple[int,...]]:
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shape = tuple([int(dim.dim_value) for dim in value_info.type.tensor_type.shape.dim])
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name = value_info.name
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return name, shape
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if __name__ == "__main__":
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model_path = pathlib.Path(sys.argv[1])
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model = onnx.load(str(model_path))
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i = [x.key for x in model.metadata_props].index('output_slices')
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output_slices = model.metadata_props[i].value
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metadata = {}
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metadata['output_slices'] = pickle.loads(codecs.decode(output_slices.encode(), "base64"))
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metadata['input_shapes'] = dict([get_name_and_shape(x) for x in model.graph.input])
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metadata['output_shapes'] = dict([get_name_and_shape(x) for x in model.graph.output])
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metadata_path = model_path.parent / (model_path.stem + '_metadata.pkl')
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with open(metadata_path, 'wb') as f:
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pickle.dump(metadata, f)
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print(f'saved metadata to {metadata_path}')
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