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Add TorchScript schema parser (#990)
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''' TorchScript metadata script ''' | ||
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import collections | ||
import json | ||
import os | ||
import re | ||
import sys | ||
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root_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) | ||
sys.path.append(root_dir) | ||
sys.pycache_prefix = os.path.join(root_dir, 'dist', 'pycache', 'test', 'backend') | ||
pytorch = __import__('source.pytorch').pytorch | ||
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source_dir = os.path.join(root_dir, 'source') | ||
third_party_dir = os.path.join(root_dir, 'third_party') | ||
metadata_file = os.path.join(source_dir, 'pytorch-metadata.json') | ||
pytorch_source_dir = os.path.join(third_party_dir, 'source', 'pytorch') | ||
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def _read(path): | ||
with open(path, 'r', encoding='utf-8') as file: | ||
return file.read() | ||
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def _write(path, content): | ||
with open(path, 'w', encoding='utf-8') as file: | ||
file.write(content) | ||
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def _read_metadata(): | ||
metadata = json.loads(_read(metadata_file)) | ||
return dict(map(lambda item: [ item['name'], item ], metadata)) | ||
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def _write_metadata(value): | ||
metadata = list(collections.OrderedDict(sorted(value.items())).values()) | ||
content = json.dumps(metadata, indent=2, ensure_ascii=False) | ||
content = re.sub(r'\s {8}', ' ', content) | ||
content = re.sub(r',\s {8}', ', ', content) | ||
content = re.sub(r'\s {6}}', ' }', content) | ||
_write(metadata_file, content) | ||
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schema_source_files = [ | ||
('aten/src/ATen/native/native_functions.yaml', | ||
re.compile(r'-\s*func:\s*(.*)', re.MULTILINE), 'aten::'), | ||
('aten/src/ATen/native/quantized/library.cpp', | ||
re.compile(r'TORCH_SELECTIVE_SCHEMA\("(.*)"\)', re.MULTILINE)), | ||
('aten/src/ATen/native/xnnpack/RegisterOpContextClass.cpp', | ||
re.compile(r'TORCH_SELECTIVE_SCHEMA\("(.*)"', re.MULTILINE)), | ||
('torch/csrc/jit/runtime/register_prim_ops_fulljit.cpp', | ||
re.compile(r'(aten::.*->\s*Tensor)', re.MULTILINE)), | ||
('torch/csrc/jit/passes/shape_analysis.cpp', | ||
re.compile(r'(aten::.*->\s*Tensor)', re.MULTILINE)), | ||
('caffe2/operators/copy_op.cc', | ||
re.compile(r'(_caffe2::.*->\s*Tensor)', re.MULTILINE)), | ||
('caffe2/operators/batch_permutation_op.cc', | ||
re.compile(r'(_caffe2::.*->\s*Tensor)', re.MULTILINE)), | ||
('caffe2/operators/collect_and_distribute_fpn_rpn_proposals_op.cc', | ||
re.compile(r'"(_caffe2::[\w+]*\([\w"\s\[\],]*\)\s*->\s*\([\w"\s\[\],]*\))"', re.MULTILINE)), | ||
('caffe2/operators/box_with_nms_limit_op.cc', | ||
re.compile(r'"(_caffe2::[\w+]*\([\w"\s\[\],]*\)\s*->\s*\([\w"\s\[\],]*\))"', re.MULTILINE)), | ||
('caffe2/operators/bbox_transform_op.cc', | ||
re.compile(r'"(_caffe2::[\w+]*\([\w"\s\[\],]*\)\s*->\s*\([\w"\s\[\],]*\))"', re.MULTILINE)), | ||
('caffe2/operators/generate_proposals_op.cc', | ||
re.compile(r'"(_caffe2::[\w+]*\([\w"\s\[\],]*\)\s*->\s*\([\w"\s\[\],]*\))"', re.MULTILINE)), | ||
('caffe2/operators/roi_align_op.cc', | ||
re.compile(r'"(_caffe2::[\w+]*\([\w"\s\[\],]*\)\s*->.*)"', re.MULTILINE)) | ||
] | ||
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def _metadata(): | ||
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types = _read_metadata() | ||
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_write_metadata(types) | ||
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for key in list(types.keys()): | ||
if key.startswith('torch.nn'): | ||
types.pop(key) | ||
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for entry in schema_source_files: | ||
path = os.path.join(pytorch_source_dir, entry[0]) | ||
content = _read(path) | ||
for value in entry[1].findall(content): | ||
value = re.sub(r'\n|\r|\s*"', '', value) if value.startswith('_caffe2::') else value | ||
definition = entry[2] + value if len(entry) > 2 else value | ||
schema = pytorch.Schema(definition) | ||
if schema.name in types: | ||
# value = types[schema.name] | ||
# if len(schema.arguments) != len(value['inputs']): | ||
# pass | ||
types.pop(schema.name) | ||
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print('\n'.join(list(types.keys()))) | ||
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def main(): # pylint: disable=missing-function-docstring | ||
_metadata() | ||
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if __name__ == '__main__': | ||
main() |