




"""simple docstring"""


import os

import numpy
import onnx


def    UpperCAmelCase__			(snake_case__				:   List[str]						,  snake_case__				:   List[Any]       ):
  """simple docstring"""

  _snake_case				:						int								=    a.name
  _snake_case				:						Any								=    b.name

  _snake_case				:						Optional[Any]								=    """"""
  _snake_case				:						Dict								=    """"""

  _snake_case				:						Dict								=    a == b

  _snake_case				:						List[str]								=    name_a
  _snake_case				:						int								=    name_b

  return res


def    UpperCAmelCase__			(snake_case__				:   Tuple						,  snake_case__				:   Any						,  snake_case__				:   Tuple       ):
  """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    UpperCAmelCase__			(snake_case__				:   List[Any]						,  snake_case__				:   Any						,  snake_case__				:   List[Any]       ):
  """simple docstring"""

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


def    UpperCAmelCase__			(snake_case__				:   Union[str, Any]						,  snake_case__				:   str						,  snake_case__				:   Tuple       ):
  """simple docstring"""

  _snake_case				:						Optional[Any]								=    list(model.graph.initializer       )
  _snake_case				:						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

    _snake_case				:						str								=    inits[i].name
    _snake_case				:						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						,  UpperCamelCase__						,  UpperCamelCase__       )






def    UpperCAmelCase__			(snake_case__				:   Dict       ):
  """simple docstring"""

  _snake_case				:						int								=    os.path.dirname(UpperCamelCase__       )
  _snake_case				:						str								=    os.path.basename(UpperCamelCase__       )

  _snake_case				:						Union[str, Any]								=    onnx.load(os.path.join(UpperCamelCase__						,  UpperCamelCase__       )       )

  _snake_case				:						Optional[Any]								=    list(model.graph.initializer       )

  _snake_case				:						int								=    set()
  _snake_case				:						List[Any]								=    {}
  _snake_case				:						Any								=    []

  _snake_case				:						Optional[Any]								=    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__       )

        _snake_case				:						int								=    inits[j].data_type
        _snake_case				:						Optional[Any]								=    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

        _snake_case				:						Optional[Any]								=    inits[i].name
        _snake_case				:						Optional[Any]								=    inits[j].name

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

  print("""total reduced size: """						,  total_reduced_size / 10_24 / 10_24 / 10_24						,  """GB"""       )

  _snake_case				:						Dict								=    sorted(UpperCamelCase__       )
  _remove_dup_initializers_from_model(UpperCamelCase__						,  UpperCamelCase__						,  UpperCamelCase__       )

  _snake_case				:						Tuple								=    """optimized_""" + model_file_name
  _snake_case				:						Tuple								=    os.path.join(UpperCamelCase__						,  UpperCamelCase__       )
  onnx.save(UpperCamelCase__						,  UpperCamelCase__       )

  return new_model








def      lowerCamelCase_						(			UpperCamelCase__							: str )	->			bool:





				"""simple docstring"""


				__lowerCamelCase									=       0
				for ch in input_str:
								__lowerCamelCase									=       ord(UpperCamelCase__ )
								__lowerCamelCase									=       pow(2					,	UpperCamelCase__ )

								# If we already turned on bit for current character's unicode
								if bitmap >> ch_unicode & 1 == 1:
												return False
								bitmap |= ch_bit_index_on
				return True


if __name__ == "__main__":
					import doctest

					doctest.testmod()


