
'''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
lowercase    :							Dict      =					"."

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







def 				SCREAMING_SNAKE_CASE__	(   __A			,				__A			,				__A	)       ->	List[Any]:
	_snake_case   						=		SavedModel()
	_snake_case   						=		[]

	with open(os.path.join(__A			,				'utils'			,				'tf_ops'			,				'onnx.json'	)	) as f:
		_snake_case   						=		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   						=		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   						=		sorted(__A	)
	_snake_case   						=		[]

	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    :							str      =					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    :							List[Any]      =					parser.parse_args()

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







import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin







class __snake_case			(			a ,  unittest.TestCase		):
   UpperCAmelCase__  :    Any          =  PhobertTokenizer
   UpperCAmelCase__  :    List[str]          =  False







   def lowerCamelCase						(      self		:						str):

        """simple docstring"""


        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        UpperCAmelCase_          =							['''T@@''', '''i''', '''I''', '''R@@''', '''r''', '''e@@''']
        UpperCAmelCase_          =							dict(zip(_snake_case					,						range(len(_snake_case))))
        UpperCAmelCase_          =							['''#version: 0.2''', '''l à</w>''']
        UpperCAmelCase_          =							{'''unk_token''': '''<unk>'''}

        UpperCAmelCase_          =							os.path.join(self.tmpdirname					,						VOCAB_FILES_NAMES['''vocab_file'''])
        UpperCAmelCase_          =							os.path.join(self.tmpdirname					,						VOCAB_FILES_NAMES['''merges_file'''])

        with open(self.vocab_file					,						'''w'''					,						encoding='''utf-8''') as fp:
             for token in vocab_tokens:
                  fp.write(F"""{token} {vocab_tokens[token]}\n""")
        with open(self.merges_file					,						'''w'''					,						encoding='''utf-8''') as fp:
             fp.write('''\n'''.join(_snake_case))







   def lowerCamelCase						(      self		:						int					,						**_snake_case		:						Any):

        """simple docstring"""


        kwargs.update(self.special_tokens_map)
        return PhobertTokenizer.from_pretrained(self.tmpdirname					,						**_snake_case)







   def lowerCamelCase						(      self		:						Optional[Any]					,						_snake_case		:						Union[str, Any]):

        """simple docstring"""


        UpperCAmelCase_          =							'''Tôi là VinAI Research'''
        UpperCAmelCase_          =							'''T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'''
        return input_text, output_text







   def lowerCamelCase						(      self		:						List[str]):

        """simple docstring"""


        UpperCAmelCase_          =							PhobertTokenizer(self.vocab_file					,						self.merges_file					,						**self.special_tokens_map)
        UpperCAmelCase_          =							'''Tôi là VinAI Research'''
        UpperCAmelCase_          =							'''T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'''.split()
        UpperCAmelCase_          =							tokenizer.tokenize(_snake_case)
        print(_snake_case)
        self.assertListEqual(_snake_case					,						_snake_case)

        UpperCAmelCase_          =							tokens + [tokenizer.unk_token]

        UpperCAmelCase_          =							[4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case)					,						_snake_case)






