

"""simple docstring"""




import os

import numpy
import onnx
def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase      ):
 '''simple docstring'''





 UpperCAmelCase__					:  str					   =					a.name
 UpperCAmelCase__					:  Tuple					   =					b.name

 UpperCAmelCase__					:  Optional[int]					   =					""""""
 UpperCAmelCase__					:  Tuple					   =					""""""

 UpperCAmelCase__					:  List[str]					   =					a == b

 UpperCAmelCase__					:  Optional[int]					   =					name_a
 UpperCAmelCase__					:  Union[str, Any]					   =					name_b

 return res
def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase      ):
 '''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   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase      ):
 '''simple docstring'''





 for n in graph_proto.node:
  _node_replace_input_with(__UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase      )
def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase      ):
 '''simple docstring'''





 UpperCAmelCase__					:  Any					   =					list(model.graph.initializer      )
 UpperCAmelCase__					:  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

  UpperCAmelCase__					:  Any					   =					inits[i].name
  UpperCAmelCase__					:  str					   =					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   lowerCAmelCase						(					__UpperCamelCase      ):
 '''simple docstring'''





 UpperCAmelCase__					:  str					   =					os.path.dirname(__UpperCamelCase      )
 UpperCAmelCase__					:  Any					   =					os.path.basename(__UpperCamelCase      )

 UpperCAmelCase__					:  List[str]					   =					onnx.load(os.path.join(__UpperCamelCase							,    __UpperCamelCase      )      )

 UpperCAmelCase__					:  Tuple					   =					list(model.graph.initializer      )

 UpperCAmelCase__					:  List[Any]					   =					set()
 UpperCAmelCase__					:  str					   =					{}
 UpperCAmelCase__					:  Tuple					   =					[]

 UpperCAmelCase__					:  List[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      )

    UpperCAmelCase__					:  str					   =					inits[j].data_type
    UpperCAmelCase__					:  List[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

    UpperCAmelCase__					:  List[Any]					   =					inits[i].name
    UpperCAmelCase__					:  Tuple					   =					inits[j].name

    if name_i in dup_map:
     dup_map[name_i].append(__UpperCamelCase      )
    else:
     UpperCAmelCase__					:  int					   =					[name_j]
    ind_to_replace.append((j, i)      )

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

 UpperCAmelCase__					:  List[Any]					   =					sorted(__UpperCamelCase      )
 _remove_dup_initializers_from_model(__UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase      )

 UpperCAmelCase__					:  List[Any]					   =					"""optimized_""" + model_file_name
 UpperCAmelCase__					:  List[Any]					   =					os.path.join(__UpperCamelCase							,    __UpperCamelCase      )
 onnx.save(__UpperCamelCase							,    __UpperCamelCase      )

 return new_model








"""simple docstring"""




import random
from typing import Any
def   lowerCAmelCase						(					__UpperCamelCase      ):
 '''simple docstring'''





 for _ in range(len(__UpperCamelCase      )      ):
  UpperCAmelCase__					:  Dict					   =					random.randint(0							,    len(__UpperCamelCase      ) - 1      )
  UpperCAmelCase__					:  Tuple					   =					random.randint(0							,    len(__UpperCamelCase      ) - 1      )
  UpperCAmelCase__   ,      UpperCAmelCase__					:  int					   =					data[b], data[a]
 return data


if __name__ == "__main__":
      __UpperCAmelCase =				[0, 1, 2, 3, 4, 5, 6, 7]
      __UpperCAmelCase =				['python', 'says', 'hello', '!']
      print('Fisher-Yates Shuffle:')
      print('List', integers, strings)
      print('FY Shuffle', fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))





