
'''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)


"""simple docstring"""






import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer


__A			   = logging.get_logger(__name__)

__A			   = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

__A			   = {
    "vocab_file": {
        "yjernite/retribert-base-uncased": (
            "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "yjernite/retribert-base-uncased": (
            "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json"
        ),
    },
}

__A			   = {
    "yjernite/retribert-base-uncased": 5_1_2,
}


__A			   = {
    "yjernite/retribert-base-uncased": {"do_lower_case": True},
}


class     UpperCAmelCase						(_UpperCAmelCase  ):



    """simple docstring"""

    _UpperCAmelCase	:Dict						    = VOCAB_FILES_NAMES
    _UpperCAmelCase	:str						    = PRETRAINED_VOCAB_FILES_MAP
    _UpperCAmelCase	:Optional[int]						    = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _UpperCAmelCase	:Optional[int]						    = PRETRAINED_INIT_CONFIGURATION
    _UpperCAmelCase	:str						    = RetriBertTokenizer
    _UpperCAmelCase	:List[str]						    = ["input_ids", "attention_mask"]






    def __init__(   self    ,			_UpperCAmelCase=None    ,			_UpperCAmelCase=None    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase="[UNK]"    ,			_UpperCAmelCase="[SEP]"    ,			_UpperCAmelCase="[PAD]"    ,			_UpperCAmelCase="[CLS]"    ,			_UpperCAmelCase="[MASK]"    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=None    ,			**_UpperCAmelCase    ,			):
       super().__init__(
           _UpperCAmelCase    ,			tokenizer_file=_UpperCAmelCase    ,			do_lower_case=_UpperCAmelCase    ,			unk_token=_UpperCAmelCase    ,			sep_token=_UpperCAmelCase    ,			pad_token=_UpperCAmelCase    ,			cls_token=_UpperCAmelCase    ,			mask_token=_UpperCAmelCase    ,			tokenize_chinese_chars=_UpperCAmelCase    ,			strip_accents=_UpperCAmelCase    ,			**_UpperCAmelCase    ,			)

       lowercase__:   Optional[Any]					=      json.loads(self.backend_tokenizer.normalizer.__getstate__()							)
       if (
           normalizer_state.get('''lowercase'''    ,			_UpperCAmelCase							) != do_lower_case
           or normalizer_state.get('''strip_accents'''    ,			_UpperCAmelCase							) != strip_accents
           or normalizer_state.get('''handle_chinese_chars'''    ,			_UpperCAmelCase							) != tokenize_chinese_chars
       ):
          lowercase__:   str					=      getattr(_UpperCAmelCase    ,			normalizer_state.pop('''type'''							)							)
          lowercase__:   Optional[Any]					=      do_lower_case
          lowercase__:   Tuple					=      strip_accents
          lowercase__:   str					=      tokenize_chinese_chars
          lowercase__:   Union[str, Any]					=      normalizer_class(**_UpperCAmelCase							)

       lowercase__:   List[str]					=      do_lower_case






    def _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase=None							):
       lowercase__:   Union[str, Any]					=      [self.cls_token_id] + token_ids_a + [self.sep_token_id]

       if token_ids_a:
          output += token_ids_a + [self.sep_token_id]

       return output






    def _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase = None							):
       lowercase__:   Optional[int]					=      [self.sep_token_id]
       lowercase__:   Union[str, Any]					=      [self.cls_token_id]
       if token_ids_a is None:
          return len(cls + token_ids_a + sep							) * [0]
       return len(cls + token_ids_a + sep							) * [0] + len(token_ids_a + sep							) * [1]






    def _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase = None							):
       lowercase__:   List[str]					=      self._tokenizer.model.save(_UpperCAmelCase    ,			name=_UpperCAmelCase							)
       return tuple(_UpperCAmelCase							)
