
"""simple docstring"""




import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs



class 	lowerCAmelCase_						(a__  ):


				"""simple docstring"""



				def __init__(self   ,       SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__=None   ,       SCREAMING_SNAKE_CASE__=True   ,       SCREAMING_SNAKE_CASE__=None   ,       **SCREAMING_SNAKE_CASE__    )					->		List[str]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Any           =   parent
											SCREAMING_SNAKE_CASE__						:       List[Any]           =   config_class
											SCREAMING_SNAKE_CASE__						:       int           =   has_text_modality
											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   kwargs
											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   common_properties



				def 	__magic_name__    (self    )					->		int:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Any           =   self.config_class(**self.inputs_dict    )
											SCREAMING_SNAKE_CASE__						:       Dict           =   (
											    ["""hidden_size""", """num_attention_heads""", """num_hidden_layers"""]
											    if self.common_properties is None
											    else self.common_properties
											)

											# Add common fields for text models
											if self.has_text_modality:
																		common_properties.extend(["""vocab_size"""]    )

											# Test that config has the common properties as getters
											for prop in common_properties:
																		self.parent.assertTrue(hasattr(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )   ,       msg=F'''`{prop}` does not exist'''    )

											# Test that config has the common properties as setter
											for idx, name in enumerate(SCREAMING_SNAKE_CASE__    ):
																		try:
																									setattr(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )
																									self.parent.assertEqual(
																									    getattr(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )   ,       SCREAMING_SNAKE_CASE__   ,       msg=F'''`{name} value {idx} expected, but was {getattr(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )}'''    )
																		except NotImplementedError:
																									# Some models might not be able to implement setters for common_properties
																									# In that case, a NotImplementedError is raised
																									pass

        # Test if config class can be called with Config(prop_name=..)
											for idx, name in enumerate(SCREAMING_SNAKE_CASE__    ):
																		try:
																									SCREAMING_SNAKE_CASE__						:       Tuple           =   self.config_class(**{name: idx}    )
																									self.parent.assertEqual(
																									    getattr(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )   ,       SCREAMING_SNAKE_CASE__   ,       msg=F'''`{name} value {idx} expected, but was {getattr(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )}'''    )
																		except NotImplementedError:
																									# Some models might not be able to implement setters for common_properties
																									# In that case, a NotImplementedError is raised
																									pass



				def 	__magic_name__    (self    )					->		List[str]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Optional[int]           =   self.config_class(**self.inputs_dict    )
											SCREAMING_SNAKE_CASE__						:       Any           =   json.loads(config.to_json_string()    )
											for key, value in self.inputs_dict.items():
																		self.parent.assertEqual(obj[key]   ,       SCREAMING_SNAKE_CASE__    )



				def 	__magic_name__    (self    )					->		Optional[Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Dict           =   self.config_class(**self.inputs_dict    )

											with tempfile.TemporaryDirectory() as tmpdirname:
																		SCREAMING_SNAKE_CASE__						:       Any           =   os.path.join(SCREAMING_SNAKE_CASE__   ,       """config.json"""    )
																		config_first.to_json_file(SCREAMING_SNAKE_CASE__    )
																		SCREAMING_SNAKE_CASE__						:       str           =   self.config_class.from_json_file(SCREAMING_SNAKE_CASE__    )

											self.parent.assertEqual(config_second.to_dict()   ,       config_first.to_dict()    )



				def 	__magic_name__    (self    )					->		List[str]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Tuple           =   self.config_class(**self.inputs_dict    )

											with tempfile.TemporaryDirectory() as tmpdirname:
																		config_first.save_pretrained(SCREAMING_SNAKE_CASE__    )
																		SCREAMING_SNAKE_CASE__						:       Any           =   self.config_class.from_pretrained(SCREAMING_SNAKE_CASE__    )

											self.parent.assertEqual(config_second.to_dict()   ,       config_first.to_dict()    )



				def 	__magic_name__    (self    )					->		Union[str, Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   self.config_class(**self.inputs_dict    )

											SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   """test"""
											with tempfile.TemporaryDirectory() as tmpdirname:
																		SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   os.path.join(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )
																		config_first.save_pretrained(SCREAMING_SNAKE_CASE__    )
																		SCREAMING_SNAKE_CASE__						:       Any           =   self.config_class.from_pretrained(SCREAMING_SNAKE_CASE__   ,       subfolder=SCREAMING_SNAKE_CASE__    )

											self.parent.assertEqual(config_second.to_dict()   ,       config_first.to_dict()    )



				def 	__magic_name__    (self    )					->		Union[str, Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   self.config_class(**self.inputs_dict   ,       num_labels=5    )
											self.parent.assertEqual(len(config.idalabel    )   ,       5    )
											self.parent.assertEqual(len(config.labelaid    )   ,       5    )

											SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   3
											self.parent.assertEqual(len(config.idalabel    )   ,       3    )
											self.parent.assertEqual(len(config.labelaid    )   ,       3    )



				def 	__magic_name__    (self    )					->		Any:



											"""simple docstring"""




											if self.config_class.is_composition:
																		return
											SCREAMING_SNAKE_CASE__						:       str           =   self.config_class()
											self.parent.assertIsNotNone(SCREAMING_SNAKE_CASE__    )



				def 	__magic_name__    (self    )					->		Union[str, Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   copy.deepcopy(SCREAMING_SNAKE_CASE__    )
											SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   self.config_class(**SCREAMING_SNAKE_CASE__    )
											SCREAMING_SNAKE_CASE__						:       str           =   []
											for key, value in config_common_kwargs.items():
																		if key == "torch_dtype":
																									if not is_torch_available():
																																continue
																									else:
																																import torch

																																if config.torch_dtype != torch.floataa:
																																							wrong_values.append(("""torch_dtype""", config.torch_dtype, torch.floataa)    )
																		elif getattr(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    ) != value:
																									wrong_values.append((key, getattr(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    ), value)    )

											if len(SCREAMING_SNAKE_CASE__    ) > 0:
																		SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   """\n""".join([F'''- {v[0]}: got {v[1]} instead of {v[2]}''' for v in wrong_values]    )
																		raise ValueError(F'''The following keys were not properly set in the config:\n{errors}'''    )



				def 	__magic_name__    (self    )					->		Optional[Any]:



											"""simple docstring"""




											self.create_and_test_config_common_properties()
											self.create_and_test_config_to_json_string()
											self.create_and_test_config_to_json_file()
											self.create_and_test_config_from_and_save_pretrained()
											self.create_and_test_config_from_and_save_pretrained_subfolder()
											self.create_and_test_config_with_num_labels()
											self.check_config_can_be_init_without_params()
											self.check_config_arguments_init()






"""simple docstring"""




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
UpperCAmelCase__      :    List[str]    							= '.'

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

def lowercase_  (   _snake_case   ,_snake_case   ,_snake_case						):
							SCREAMING_SNAKE_CASE__						:       List[str]           =   SavedModel()
							SCREAMING_SNAKE_CASE__						:       Dict           =   []

							with open(os.path.join(_snake_case   ,"""utils"""   ,"""tf_ops"""   ,"""onnx.json"""						)						) as f:
														SCREAMING_SNAKE_CASE__						:       Any           =   json.load(_snake_case						)["""opsets"""]

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

							with open(_snake_case   ,"""rb"""						) as f:
														saved_model.ParseFromString(f.read()						)

							SCREAMING_SNAKE_CASE__						:       List[str]           =   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
							SCREAMING_SNAKE_CASE__						:       int           =   sorted(_snake_case						)
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   []

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

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


if __name__ == "__main__":
					UpperCAmelCase__      :    Optional[int]    							= 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)'
					)
					UpperCAmelCase__      :    Dict    							= parser.parse_args()

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




