


import argparse
import json
import os

from tensorflow.core.protobuf.saved_model_pba import SavedModel


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
lowerCAmelCase__    :List[Any]       =				'''.'''

# Internal TensorFlow ops that can be safely ignored (mostly specific to a saved model)
lowerCAmelCase__    :List[str]       =				[
    '''Assert''',
    '''AssignVariableOp''',
    '''EmptyTensorList''',
    '''MergeV2Checkpoints''',
    '''ReadVariableOp''',
    '''ResourceGather''',
    '''RestoreV2''',
    '''SaveV2''',
    '''ShardedFilename''',
    '''StatefulPartitionedCall''',
    '''StaticRegexFullMatch''',
    '''VarHandleOp''',
]

def 			lowerCAmelCase__					(     a__:						Dict     ,    a__:						int     ,    a__:						Any			)    ->						Optional[int]:


							'''simple docstring'''





							_UpperCAmelCase											=     SavedModel()
							_UpperCAmelCase											=     []

							with open(os.path.join(a__     ,    'utils'     ,    'tf_ops'     ,    'onnx.json'			)			) as f:
														_UpperCAmelCase											=     json.load(a__			)['opsets']

							for i in range(1     ,    opset + 1			):
														onnx_ops.extend(onnx_opsets[str(a__			)]			)

							with open(a__     ,    'rb'			) as f:
														saved_model.ParseFromString(f.read()			)

							_UpperCAmelCase											=     set()

							# Iterate over every metagraph in case there is more than one (a saved model can contain multiple graphs)
							for meta_graph in saved_model.meta_graphs:
														# Add operations in the graph definition
														model_op_names.update(node.op for node in meta_graph.graph_def.node			)

														# Go through the functions in the graph definition
														for func in meta_graph.graph_def.library.function:
																					# Add operations in each function
																					model_op_names.update(node.op for node in func.node_def			)

    # Convert to list, sorted if you want
							_UpperCAmelCase											=     sorted(a__			)
							_UpperCAmelCase											=     []

							for op in model_op_names:
														if op not in onnx_ops and op not in INTERNAL_OPS:
																					incompatible_ops.append(a__			)

							if strict and len(a__			) > 0:
														raise Exception(F'''Found the following incompatible ops for the opset {opset}:\n''' + incompatible_ops			)
							elif len(a__			) > 0:
														print(F'''Found the following incompatible ops for the opset {opset}:'''			)
														print(*a__     ,    sep='\n'			)
							else:
														print(F'''The saved model {saved_model_path} can properly be converted with ONNX.'''			)


if __name__ == "__main__":
		lowerCAmelCase__    :List[Any]       =				argparse.ArgumentParser()
		parser.add_argument('''--saved_model_path''', help='''Path of the saved model to check (the .pb file).''')
		parser.add_argument(
		    '''--opset''', default=1_2, type=int, help='''The ONNX opset against which the model has to be tested.'''
		)
		parser.add_argument(
		    '''--framework''', choices=['''onnx'''], default='''onnx''', help='''Frameworks against which to test the saved model.'''
		)
		parser.add_argument(
		    '''--strict''', action='''store_true''', help='''Whether make the checking strict (raise errors) or not (raise warnings)'''
		)
		lowerCAmelCase__    :Optional[int]       =				parser.parse_args()

		if args.framework == "onnx":
				onnx_compliancy(args.saved_model_path, args.strict, args.opset)




from typing import Any

def 			lowerCAmelCase__					(     a__:						list     ,    a__:						list     ,    a__:						dict     ,    a__:						dict     ,    a__:						dict     ,    )    ->						list:


							'''simple docstring'''





							_validation(
							    a__     ,    a__     ,    a__     ,    a__     ,    a__     ,    )
							# Creates data structures and fill initial step
							_UpperCAmelCase											=     {}
							_UpperCAmelCase											=     {}
							for state in states_space:
														_UpperCAmelCase											=     observations_space[0]
														_UpperCAmelCase											=     (
														    initial_probabilities[state] * emission_probabilities[state][observation]
														)
														_UpperCAmelCase											=     None

							# Fills the data structure with the probabilities of
							# different transitions and pointers to previous states
							for o in range(1     ,    len(a__			)			):
														_UpperCAmelCase											=     observations_space[o]
														_UpperCAmelCase											=     observations_space[o - 1]
														for state in states_space:
																					# Calculates the argmax for probability function
																					_UpperCAmelCase											=     ''
																					_UpperCAmelCase											=     -1
																					for k_state in states_space:
																												_UpperCAmelCase											=     (
																												    probabilities[(k_state, prior_observation)]
																												    * transition_probabilities[k_state][state]
																												    * emission_probabilities[state][observation]
																												)
																												if probability > max_probability:
																																			_UpperCAmelCase											=     probability
																																			_UpperCAmelCase											=     k_state

            # Update probabilities and pointers dicts
																					_UpperCAmelCase											=     (
																					    probabilities[(arg_max, prior_observation)]
																					    * transition_probabilities[arg_max][state]
																					    * emission_probabilities[state][observation]
																					)

																					_UpperCAmelCase											=     arg_max

    # The final observation
							_UpperCAmelCase											=     observations_space[len(a__			) - 1]

							# argmax for given final observation
							_UpperCAmelCase											=     ''
							_UpperCAmelCase											=     -1
							for k_state in states_space:
														_UpperCAmelCase											=     probabilities[(k_state, final_observation)]
														if probability > max_probability:
																					_UpperCAmelCase											=     probability
																					_UpperCAmelCase											=     k_state
							_UpperCAmelCase											=     arg_max

							# Process pointers backwards
							_UpperCAmelCase											=     last_state
							_UpperCAmelCase											=     []
							for o in range(len(a__			) - 1     ,    -1     ,    -1			):
														result.append(a__			)
														_UpperCAmelCase											=     pointers[previous, observations_space[o]]
							result.reverse()

							return result

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    )    ->						None:


							'''simple docstring'''





							_validate_not_empty(
							    a__     ,    a__     ,    a__     ,    a__     ,    a__     ,    )
							_validate_lists(a__     ,    a__			)
							_validate_dicts(
							    a__     ,    a__     ,    a__			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    )    ->						None:


							'''simple docstring'''





							if not all(
							    [
							        observations_space,
							        states_space,
							        initial_probabilities,
							        transition_probabilities,
							        emission_probabilities,
							    ]			):
														raise ValueError('There\'s an empty parameter'			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						Any			)    ->						None:


							'''simple docstring'''





							_validate_list(a__     ,    'observations_space'			)
							_validate_list(a__     ,    'states_space'			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						str			)    ->						None:


							'''simple docstring'''





							if not isinstance(_object     ,    a__			):
														_UpperCAmelCase											=     F'''{var_name} must be a list'''
														raise ValueError(a__			)
							else:
														for x in _object:
																					if not isinstance(a__     ,    a__			):
																												_UpperCAmelCase											=     F'''{var_name} must be a list of strings'''
																												raise ValueError(a__			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    )    ->						None:


							'''simple docstring'''





							_validate_dict(a__     ,    'initial_probabilities'     ,    a__			)
							_validate_nested_dict(a__     ,    'transition_probabilities'			)
							_validate_nested_dict(a__     ,    'emission_probabilities'			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						str			)    ->						None:


							'''simple docstring'''





							_validate_dict(_object     ,    a__     ,    a__			)
							for x in _object.values():
														_validate_dict(a__     ,    a__     ,    a__     ,    a__			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						str     ,    a__:						type     ,    a__:						bool = False			)    ->						None:


							'''simple docstring'''





							if not isinstance(_object     ,    a__			):
														_UpperCAmelCase											=     F'''{var_name} must be a dict'''
														raise ValueError(a__			)
							if not all(isinstance(a__     ,    a__			) for x in _object			):
														_UpperCAmelCase											=     F'''{var_name} all keys must be strings'''
														raise ValueError(a__			)
							if not all(isinstance(a__     ,    a__			) for x in _object.values()			):
														_UpperCAmelCase											=     'nested dictionary ' if nested else ''
														_UpperCAmelCase											=     F'''{var_name} {nested_text}all values must be {value_type.__name__}'''
														raise ValueError(a__			)


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

		testmod()
