






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
lowercase  :							Tuple			  =    '''.'''

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

def      lowerCAmelCase__	(    _a       :			Union[str, Any]  ,      _a       :			Dict  ,      _a       :			List[str]    ):
		snake_case_				:							Optional[int]						 =       SavedModel()
		snake_case_				:							Any						 =       []

		with open(os.path.join(_a  ,      "utils"  ,      "tf_ops"  ,      "onnx.json"    )    ) as f:
				snake_case_				:							int						 =       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()    )

		snake_case_				:							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
		snake_case_				:							int						 =       sorted(_a    )
		snake_case_				:							Optional[int]						 =       []

		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__":
							lowercase  :							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=12, 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)'''
							)
							lowercase  :							int			  =    parser.parse_args()

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








import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


sys.path.append(str(Path(__file__).parent.parent.parent.parent / '''utils'''))

from test_module.custom_configuration import CustomConfig  # noqa E402


lowercase  :							Optional[Any]			  =    get_tests_dir('''fixtures/dummy-config.json''')




class 		UpperCAmelCase_						(	unittest.TestCase					):


						'''simple docstring'''




						def       _lowerCAmelCase       (	self				) ->				int:
								snake_case_				:							str						 =       0






						def       _lowerCAmelCase       (	self				) ->				str:
								self.assertIsNotNone(transformers.models.auto.__spec__				)
								self.assertIsNotNone(importlib.util.find_spec("transformers.models.auto"				)				)






						def       _lowerCAmelCase       (	self				) ->				int:
								snake_case_				:							List[Any]						 =       AutoConfig.from_pretrained("bert-base-uncased"				)
								self.assertIsInstance(_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE				)






						def       _lowerCAmelCase       (	self				) ->				Optional[int]:
								snake_case_				:							List[str]						 =       AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE				)
								self.assertIsInstance(_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE				)






						def       _lowerCAmelCase       (	self				) ->				str:
								snake_case_				:							str						 =       AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE				)
								self.assertIsInstance(_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE				)






						def       _lowerCAmelCase       (	self				) ->				Dict:
								snake_case_				:							Tuple						 =       AutoConfig.for_model("roberta"				)
								self.assertIsInstance(_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE				)






						def       _lowerCAmelCase       (	self				) ->				Tuple:
								with tempfile.TemporaryDirectory() as tmp_dir:
										# This model name contains bert and roberta, but roberta ends up being picked.
										snake_case_				:							str						 =       os.path.join(_SCREAMING_SNAKE_CASE		,				"fake-roberta"				)
										os.makedirs(_SCREAMING_SNAKE_CASE		,				exist_ok=_SCREAMING_SNAKE_CASE				)
										with open(os.path.join(_SCREAMING_SNAKE_CASE		,				"config.json"				)		,				"w"				) as f:
												f.write(json.dumps({}				)				)
										snake_case_				:							int						 =       AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE				)
										self.assertEqual(type(_SCREAMING_SNAKE_CASE				)		,				_SCREAMING_SNAKE_CASE				)






						def       _lowerCAmelCase       (	self				) ->				Dict:
								try:
										AutoConfig.register("custom"		,				_SCREAMING_SNAKE_CASE				)
										# Wrong model type will raise an error
										with self.assertRaises(_SCREAMING_SNAKE_CASE				):
												AutoConfig.register("model"		,				_SCREAMING_SNAKE_CASE				)
										# Trying to register something existing in the Transformers library will raise an error
										with self.assertRaises(_SCREAMING_SNAKE_CASE				):
												AutoConfig.register("bert"		,				_SCREAMING_SNAKE_CASE				)

										# Now that the config is registered, it can be used as any other config with the auto-API
										snake_case_				:							Union[str, Any]						 =       CustomConfig()
										with tempfile.TemporaryDirectory() as tmp_dir:
												config.save_pretrained(_SCREAMING_SNAKE_CASE				)
												snake_case_				:							int						 =       AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE				)
												self.assertIsInstance(_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE				)

								finally:
										if "custom" in CONFIG_MAPPING._extra_content:
												del CONFIG_MAPPING._extra_content["custom"]






						def       _lowerCAmelCase       (	self				) ->				int:
								with self.assertRaisesRegex(
								    _SCREAMING_SNAKE_CASE		,				"bert-base is not a local folder and is not a valid model identifier"				):
										snake_case_				:							Optional[Any]						 =       AutoConfig.from_pretrained("bert-base"				)






						def       _lowerCAmelCase       (	self				) ->				Tuple:
								with self.assertRaisesRegex(
								    _SCREAMING_SNAKE_CASE		,				r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"				):
										snake_case_				:							List[Any]						 =       AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE		,				revision="aaaaaa"				)






						def       _lowerCAmelCase       (	self				) ->				str:
								with self.assertRaisesRegex(
								    _SCREAMING_SNAKE_CASE		,				"hf-internal-testing/no-config-test-repo does not appear to have a file named config.json."		,				):
										snake_case_				:							Dict						 =       AutoConfig.from_pretrained("hf-internal-testing/no-config-test-repo"				)






						def       _lowerCAmelCase       (	self				) ->				Optional[int]:
								# If remote code is not set, we will time out when asking whether to load the model.
								with self.assertRaises(_SCREAMING_SNAKE_CASE				):
										snake_case_				:							Tuple						 =       AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"				)
								# If remote code is disabled, we can't load this config.
								with self.assertRaises(_SCREAMING_SNAKE_CASE				):
										snake_case_				:							Optional[Any]						 =       AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"		,				trust_remote_code=_SCREAMING_SNAKE_CASE				)

								snake_case_				:							List[Any]						 =       AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"		,				trust_remote_code=_SCREAMING_SNAKE_CASE				)
								self.assertEqual(config.__class__.__name__		,				"NewModelConfig"				)

								# Test config can be reloaded.
								with tempfile.TemporaryDirectory() as tmp_dir:
										config.save_pretrained(_SCREAMING_SNAKE_CASE				)
										snake_case_				:							Optional[Any]						 =       AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE		,				trust_remote_code=_SCREAMING_SNAKE_CASE				)
								self.assertEqual(reloaded_config.__class__.__name__		,				"NewModelConfig"				)






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




								class 		UpperCAmelCase_						(	SCREAMING_SNAKE_CASE__					):


														'''simple docstring'''




														A     :   List[Any]						=					'new-model'

								try:
										AutoConfig.register("new-model"		,				_SCREAMING_SNAKE_CASE				)
										# If remote code is not set, the default is to use local
										snake_case_				:							Union[str, Any]						 =       AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"				)
										self.assertEqual(config.__class__.__name__		,				"NewModelConfigLocal"				)

										# If remote code is disabled, we load the local one.
										snake_case_				:							Optional[Any]						 =       AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"		,				trust_remote_code=_SCREAMING_SNAKE_CASE				)
										self.assertEqual(config.__class__.__name__		,				"NewModelConfigLocal"				)

										# If remote is enabled, we load from the Hub
										snake_case_				:							List[str]						 =       AutoConfig.from_pretrained("hf-internal-testing/test_dynamic_model"		,				trust_remote_code=_SCREAMING_SNAKE_CASE				)
										self.assertEqual(config.__class__.__name__		,				"NewModelConfig"				)

								finally:
										if "new-model" in CONFIG_MAPPING._extra_content:
												del CONFIG_MAPPING._extra_content["new-model"]
