


import os

import numpy
import onnx



def 				UpperCamelCase_(      lowerCamelCase_							, lowerCamelCase_ )    ->						Any:
    _lowercase       :							Optional[Any]      		=		a.name
    _lowercase       :							Dict      		=		b.name

    _lowercase       :							List[str]      		=		''
    _lowercase       :							int      		=		''

    _lowercase       :							Optional[int]      		=		a == b

    _lowercase       :							str      		=		name_a
    _lowercase       :							Optional[int]      		=		name_b

    return res



def 				UpperCamelCase_(      lowerCamelCase_							, lowerCamelCase_							, lowerCamelCase_ )    ->						Union[str, Any]:
    for i, input_name in enumerate(node_proto.input ):
        if input_name == name:
            node_proto.input.insert(lowerCamelCase_							, lowerCamelCase_ )
            node_proto.input.pop(i + 1 )

    if node_proto.op_type == "If":
        _graph_replace_input_with(node_proto.attribute[0].g							, lowerCamelCase_							, lowerCamelCase_ )
        _graph_replace_input_with(node_proto.attribute[1].g							, lowerCamelCase_							, lowerCamelCase_ )
    if node_proto.op_type == "Loop":
        _graph_replace_input_with(node_proto.attribute[0].g							, lowerCamelCase_							, lowerCamelCase_ )



def 				UpperCamelCase_(      lowerCamelCase_							, lowerCamelCase_							, lowerCamelCase_ )    ->						int:
    for n in graph_proto.node:
        _node_replace_input_with(lowerCamelCase_							, lowerCamelCase_							, lowerCamelCase_ )



def 				UpperCamelCase_(      lowerCamelCase_							, lowerCamelCase_							, lowerCamelCase_ )    ->						Optional[int]:
    _lowercase       :							List[str]      		=		list(model.graph.initializer )
    _lowercase       :							str      		=		list(model_without_ext.graph.initializer )
    for i, ref_i in ind_to_replace:
        assert inits_with_data[i].name == inits[i].name
        assert inits_with_data[ref_i].name == inits[ref_i].name
        assert i > ref_i

        _lowercase       :							List[Any]      		=		inits[i].name
        _lowercase       :							Optional[int]      		=		inits[ref_i].name

        model_without_ext.graph.initializer.remove(inits[i] )

        # for n in model.graph.node:
        _graph_replace_input_with(model_without_ext.graph							, lowerCamelCase_							, lowerCamelCase_ )



def 				UpperCamelCase_(      lowerCamelCase_ )    ->						Optional[int]:
    _lowercase       :							str      		=		os.path.dirname(lowerCamelCase_ )
    _lowercase       :							Tuple      		=		os.path.basename(lowerCamelCase_ )

    _lowercase       :							Optional[int]      		=		onnx.load(os.path.join(lowerCamelCase_							, lowerCamelCase_ ) )

    _lowercase       :							Optional[int]      		=		list(model.graph.initializer )

    _lowercase       :							Dict      		=		set()
    _lowercase       :							Optional[int]      		=		{}
    _lowercase       :							Union[str, Any]      		=		[]

    _lowercase       :							Optional[int]      		=		0

    for i in range(len(lowerCamelCase_ ) ):
        if i in dup_set:
            continue

        for j in range(i + 1							, len(lowerCamelCase_ ) ):
            if j in dup_set:
                continue
            if _is_equal_tensor_proto(inits[i]							, inits[j] ):
                dup_set.add(lowerCamelCase_ )
                dup_set.add(lowerCamelCase_ )

                _lowercase       :							Optional[int]      		=		inits[j].data_type
                _lowercase       :							Optional[int]      		=		numpy.prod(inits[j].dims )
                if dtype == 1:
                    mem_size *= 4
                elif dtype == 6:
                    mem_size *= 4
                elif dtype == 7 or dtype == 11:
                    mem_size *= 8
                else:
                    print('unexpected data type: '							, lowerCamelCase_ )
                total_reduced_size += mem_size

                _lowercase       :							str      		=		inits[i].name
                _lowercase       :							List[str]      		=		inits[j].name

                if name_i in dup_map:
                    dup_map[name_i].append(lowerCamelCase_ )
                else:
                    _lowercase       :							Tuple      		=		[name_j]
                ind_to_replace.append((j, i) )

    print('total reduced size: '							, total_reduced_size / 1024 / 1024 / 1024							, 'GB' )

    _lowercase       :							int      		=		sorted(lowerCamelCase_ )
    _remove_dup_initializers_from_model(lowerCamelCase_							, lowerCamelCase_							, lowerCamelCase_ )

    _lowercase       :							Tuple      		=		'optimized_' + model_file_name
    _lowercase       :							int      		=		os.path.join(lowerCamelCase_							, lowerCamelCase_ )
    onnx.save(lowerCamelCase_							, lowerCamelCase_ )

    return new_model







import argparse
from collections import defaultdict

import yaml


_snake_case		=  "docs/source/en/_toctree.yml"






def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							Dict    =    defaultdict(_lowerCamelCase  )
							_lowerCAmelCase     :							Any    =    []
							_lowerCAmelCase     :							List[str]    =    []
							for doc in doc_list:
														if "local" in doc:
																					counts[doc["local"]] += 1

														if doc["title"].lower() == "overview":
																					overview_doc.append({"local": doc["local"], "title": doc["title"]}  )
														else:
																					new_doc_list.append(_lowerCamelCase  )

							_lowerCAmelCase     :							Optional[Any]    =    new_doc_list
							_lowerCAmelCase     :							List[Any]    =    [key for key, value in counts.items() if value > 1]

							_lowerCAmelCase     :							str    =    []
							for duplicate_key in duplicates:
														_lowerCAmelCase     :							List[str]    =    list({doc["title"] for doc in doc_list if doc["local"] == duplicate_key}  )
														if len(_lowerCamelCase  ) > 1:
																					raise ValueError(
																					    F"{duplicate_key} is present several times in the documentation table of content at "
																					    "`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the "
																					    "others."  )
														# Only add this once
														new_doc.append({"local": duplicate_key, "title": titles[0]}  )

							# Add none duplicate-keys
							new_doc.extend([doc for doc in doc_list if "local" not in counts or counts[doc["local"]] == 1]  )
							_lowerCAmelCase     :							Optional[Any]    =    sorted(_lowerCamelCase				, key=lambda _lowerCamelCase  : s["title"].lower()  )

							# "overview" gets special treatment and is always first
							if len(_lowerCamelCase  ) > 1:
														raise ValueError("{doc_list} has two 'overview' docs which is not allowed."  )

							overview_doc.extend(_lowerCamelCase  )

							# Sort
							return overview_doc






def 				A				(					_lowerCamelCase=False  ):





							'''simple docstring'''




							with open(_lowerCamelCase				, encoding="utf-8"  ) as f:
														_lowerCAmelCase     :							int    =    yaml.safe_load(f.read()  )

							# Get to the API doc
							_lowerCAmelCase     :							Optional[Any]    =    0
							while content[api_idx]["title"] != "API":
														api_idx += 1
							_lowerCAmelCase     :							List[str]    =    content[api_idx]["sections"]

							# Then to the model doc
							_lowerCAmelCase     :							Union[str, Any]    =    0
							while api_doc[scheduler_idx]["title"] != "Schedulers":
														scheduler_idx += 1

							_lowerCAmelCase     :							Optional[Any]    =    api_doc[scheduler_idx]["sections"]
							_lowerCAmelCase     :							Optional[Any]    =    clean_doc_toc(_lowerCamelCase  )

							_lowerCAmelCase     :							int    =    False
							if new_scheduler_doc != scheduler_doc:
														_lowerCAmelCase     :							List[Any]    =    True
														if overwrite:
																					_lowerCAmelCase     :							Dict    =    new_scheduler_doc

							if diff:
														if overwrite:
																					_lowerCAmelCase     :							Tuple    =    api_doc
																					with open(_lowerCamelCase				, "w"				, encoding="utf-8"  ) as f:
																												f.write(yaml.dump(_lowerCamelCase				, allow_unicode=_lowerCamelCase  )  )
														else:
																					raise ValueError(
																					    "The model doc part of the table of content is not properly sorted, run `make style` to fix this."  )






def 				A				(					_lowerCamelCase=False  ):





							'''simple docstring'''




							with open(_lowerCamelCase				, encoding="utf-8"  ) as f:
														_lowerCAmelCase     :							Tuple    =    yaml.safe_load(f.read()  )

							# Get to the API doc
							_lowerCAmelCase     :							Optional[int]    =    0
							while content[api_idx]["title"] != "API":
														api_idx += 1
							_lowerCAmelCase     :							int    =    content[api_idx]["sections"]

							# Then to the model doc
							_lowerCAmelCase     :							List[str]    =    0
							while api_doc[pipeline_idx]["title"] != "Pipelines":
														pipeline_idx += 1

							_lowerCAmelCase     :							Dict    =    False
							_lowerCAmelCase     :							Optional[int]    =    api_doc[pipeline_idx]["sections"]
							_lowerCAmelCase     :							Tuple    =    []

							# sort sub pipeline docs
							for pipeline_doc in pipeline_docs:
														if "section" in pipeline_doc:
																					_lowerCAmelCase     :							List[Any]    =    pipeline_doc["section"]
																					_lowerCAmelCase     :							Union[str, Any]    =    clean_doc_toc(_lowerCamelCase  )
																					if overwrite:
																												_lowerCAmelCase     :							Optional[Any]    =    new_sub_pipeline_doc
														new_pipeline_docs.append(_lowerCamelCase  )

							# sort overall pipeline doc
							_lowerCAmelCase     :							Union[str, Any]    =    clean_doc_toc(_lowerCamelCase  )

							if new_pipeline_docs != pipeline_docs:
														_lowerCAmelCase     :							Dict    =    True
														if overwrite:
																					_lowerCAmelCase     :							Optional[int]    =    new_pipeline_docs

							if diff:
														if overwrite:
																					_lowerCAmelCase     :							Optional[int]    =    api_doc
																					with open(_lowerCamelCase				, "w"				, encoding="utf-8"  ) as f:
																												f.write(yaml.dump(_lowerCamelCase				, allow_unicode=_lowerCamelCase  )  )
														else:
																					raise ValueError(
																					    "The model doc part of the table of content is not properly sorted, run `make style` to fix this."  )


if __name__ == "__main__":
						_snake_case		=  argparse.ArgumentParser()
						parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
						_snake_case		=  parser.parse_args()

						check_scheduler_doc(args.fix_and_overwrite)
						check_pipeline_doc(args.fix_and_overwrite)
