


import os

import numpy
import onnx





def 							A     (					_UpperCAmelCase    :       Tuple							,       _UpperCAmelCase    :       int   )    ->			Dict:







			'''simple docstring'''
			_UpperCAmelCase			=       a.name
			_UpperCAmelCase			=       b.name

			_UpperCAmelCase			=       ''''''
			_UpperCAmelCase			=       ''''''

			_UpperCAmelCase			=       a == b

			_UpperCAmelCase			=       name_a
			_UpperCAmelCase			=       name_b

			return res





def 							A     (					_UpperCAmelCase    :       Any							,       _UpperCAmelCase    :       Tuple							,       _UpperCAmelCase    :       Dict   )    ->			Optional[int]:







			'''simple docstring'''
			for i, input_name in enumerate(node_proto.input   ):
						if input_name == name:
									node_proto.input.insert(UpperCamelCase__							,       UpperCamelCase__   )
									node_proto.input.pop(i + 1   )

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





def 							A     (					_UpperCAmelCase    :       int							,       _UpperCAmelCase    :       Dict							,       _UpperCAmelCase    :       Any   )    ->			int:







			'''simple docstring'''
			for n in graph_proto.node:
						_node_replace_input_with(UpperCamelCase__							,       UpperCamelCase__							,       UpperCamelCase__   )





def 							A     (					_UpperCAmelCase    :       Tuple							,       _UpperCAmelCase    :       Any							,       _UpperCAmelCase    :       Optional[Any]   )    ->			Dict:







			'''simple docstring'''
			_UpperCAmelCase			=       list(model.graph.initializer   )
			_UpperCAmelCase			=       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

						_UpperCAmelCase			=       inits[i].name
						_UpperCAmelCase			=       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							,       UpperCamelCase__							,       UpperCamelCase__   )





def 							A     (					_UpperCAmelCase    :       List[str]   )    ->			int:







			'''simple docstring'''
			_UpperCAmelCase			=       os.path.dirname(UpperCamelCase__   )
			_UpperCAmelCase			=       os.path.basename(UpperCamelCase__   )

			_UpperCAmelCase			=       onnx.load(os.path.join(UpperCamelCase__							,       UpperCamelCase__   )   )

			_UpperCAmelCase			=       list(model.graph.initializer   )

			_UpperCAmelCase			=       set()
			_UpperCAmelCase			=       {}
			_UpperCAmelCase			=       []

			_UpperCAmelCase			=       0

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

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

												_UpperCAmelCase			=       inits[j].data_type
												_UpperCAmelCase			=       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: '							,       UpperCamelCase__   )
												total_reduced_size += mem_size

												_UpperCAmelCase			=       inits[i].name
												_UpperCAmelCase			=       inits[j].name

												if name_i in dup_map:
															dup_map[name_i].append(UpperCamelCase__   )
												else:
															_UpperCAmelCase			=       [name_j]
												ind_to_replace.append((j, i)   )

			print('total reduced size: '							,       total_reduced_size / 1_024 / 1_024 / 1_024							,       'GB'   )

			_UpperCAmelCase			=       sorted(UpperCamelCase__   )
			_remove_dup_initializers_from_model(UpperCamelCase__							,       UpperCamelCase__							,       UpperCamelCase__   )

			_UpperCAmelCase			=       '''optimized_''' + model_file_name
			_UpperCAmelCase			=       os.path.join(UpperCamelCase__							,       UpperCamelCase__   )
			onnx.save(UpperCamelCase__							,       UpperCamelCase__   )

			return new_model





from typing import TYPE_CHECKING

from ...utils import _LazyModule


UpperCAmelCase__       =	{"tokenization_bertweet": ["BertweetTokenizer"]}


if TYPE_CHECKING:
							from .tokenization_bertweet import BertweetTokenizer

else:
							import sys

							UpperCAmelCase__       =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
