
import os

import numpy
import onnx


def     __lowerCAmelCase			(			a__						,    a__  )       ->  Optional[int]:
				__a										=    a.name
				__a										=    b.name

				__a										=    ''''''
				__a										=    ''''''

				__a										=    a == b

				__a										=    name_a
				__a										=    name_b

				return res


def     __lowerCAmelCase			(			a__						,    a__						,    a__  )       ->  List[Any]:
				for i, input_name in enumerate(node_proto.input  ):
								if input_name == name:
												node_proto.input.insert(a__						,    a__  )
												node_proto.input.pop(i + 1  )

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


def     __lowerCAmelCase			(			a__						,    a__						,    a__  )       ->  Optional[Any]:
				for n in graph_proto.node:
								_node_replace_input_with(a__						,    a__						,    a__  )


def     __lowerCAmelCase			(			a__						,    a__						,    a__  )       ->  Optional[int]:
				__a										=    list(model.graph.initializer  )
				__a										=    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

								__a										=    inits[i].name
								__a										=    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						,    a__						,    a__  )






def     __lowerCAmelCase			(			a__  )       ->  List[str]:
				__a										=    os.path.dirname(a__  )
				__a										=    os.path.basename(a__  )

				__a										=    onnx.load(os.path.join(a__						,    a__  )  )

				__a										=    list(model.graph.initializer  )

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

				__a										=    0

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

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

																__a										=    inits[j].data_type
																__a										=    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: '''						,    a__  )
																total_reduced_size += mem_size

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

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

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

				__a										=    sorted(a__  )
				_remove_dup_initializers_from_model(a__						,    a__						,    a__  )

				__a										=    '''optimized_''' + model_file_name
				__a										=    os.path.join(a__						,    a__  )
				onnx.save(a__						,    a__  )

				return new_model





from math import pi, sqrt





def 		__A		(	__lowerCamelCase    )      ->       float:
	if num <= 0:
		raise ValueError("""math domain error"""    )
	if num > 171.5:
		raise OverflowError("""math range error"""    )
	elif num - int(__lowerCamelCase    ) not in (0, 0.5):
		raise NotImplementedError("""num must be an integer or a half-integer"""    )
	elif num == 0.5:
		return sqrt(__lowerCamelCase    )
	else:
		return 1.0 if num == 1 else (num - 1) * gamma(num - 1    )





def 		__A		(	)      ->       None:
	assert gamma(0.5    ) == sqrt(__lowerCamelCase    )
	assert gamma(1    ) == 1.0
	assert gamma(2    ) == 1.0


if __name__ == "__main__":
		from doctest import testmod

		testmod()
		__UpperCamelCase					:       str    					=      1.0
		while num:
				__UpperCamelCase					:       Dict    					=      float(input("Gamma of: "))
				print(F'gamma({num}) = {gamma(num)}')
				print("\nEnter 0 to exit...")

