
"""simple docstring"""

import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


UpperCamelCase			:       Any									=				logging.get_logger(__name__)


UpperCamelCase			:       Tuple									=				{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

# See all BART models at https://huggingface.co/models?filter=bart
UpperCamelCase			:       Optional[Any]									=				{
    """vocab_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/vocab.json""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/vocab.json""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/merges.txt""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/merges.txt""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt""",
    },
}

UpperCamelCase			:       List[Any]									=				{
    """facebook/bart-base""": 1_0_2_4,
    """facebook/bart-large""": 1_0_2_4,
    """facebook/bart-large-mnli""": 1_0_2_4,
    """facebook/bart-large-cnn""": 1_0_2_4,
    """facebook/bart-large-xsum""": 1_0_2_4,
    """yjernite/bart_eli5""": 1_0_2_4,
}






@lru_cache()
def 							A		(       )   ->			Optional[int]:
 __UpperCamelCase       						= (
     list(range(ord('!'	)       ,      ord('~'	) + 1	)	) + list(range(ord('¡'	)       ,      ord('¬'	) + 1	)	) + list(range(ord('®'	)       ,      ord('ÿ'	) + 1	)	)
 )
 __UpperCamelCase       						= bs[:]
 __UpperCamelCase       						= 0
 for b in range(2**8	):
  if b not in bs:
   bs.append(snake_case_	)
   cs.append(2**8 + n	)
   n += 1
 __UpperCamelCase       						= [chr(snake_case_	) for n in cs]
 return dict(zip(snake_case_       ,      snake_case_	)	)






def 							A		(       snake_case   :List[Any]	)   ->			Dict:
 __UpperCamelCase       						= set()
 __UpperCamelCase       						= word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)	)
  __UpperCamelCase       						= char
 return pairs





class __lowerCAmelCase	(   UpperCamelCase_    ):
     lowercase		     =		VOCAB_FILES_NAMES
     lowercase		     =		PRETRAINED_VOCAB_FILES_MAP
     lowercase		     =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowercase		     =		["input_ids", "attention_mask"]





     def __init__(			self			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase="replace"			,  __UpperCAmelCase="<s>"			,  __UpperCAmelCase="</s>"			,  __UpperCAmelCase="</s>"			,  __UpperCAmelCase="<s>"			,  __UpperCAmelCase="<unk>"			,  __UpperCAmelCase="<pad>"			,  __UpperCAmelCase="<mask>"			,  __UpperCAmelCase=False			,  **__UpperCAmelCase			,  ):

      '''simple docstring'''




      __UpperCamelCase       						= AddedToken(__A			,  lstrip=__A			,  rstrip=__A   ) if isinstance(__A			,  __A   ) else bos_token
      __UpperCamelCase       						= AddedToken(__A			,  lstrip=__A			,  rstrip=__A   ) if isinstance(__A			,  __A   ) else eos_token
      __UpperCamelCase       						= AddedToken(__A			,  lstrip=__A			,  rstrip=__A   ) if isinstance(__A			,  __A   ) else sep_token
      __UpperCamelCase       						= AddedToken(__A			,  lstrip=__A			,  rstrip=__A   ) if isinstance(__A			,  __A   ) else cls_token
      __UpperCamelCase       						= AddedToken(__A			,  lstrip=__A			,  rstrip=__A   ) if isinstance(__A			,  __A   ) else unk_token
      __UpperCamelCase       						= AddedToken(__A			,  lstrip=__A			,  rstrip=__A   ) if isinstance(__A			,  __A   ) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      __UpperCamelCase       						= AddedToken(__A			,  lstrip=__A			,  rstrip=__A   ) if isinstance(__A			,  __A   ) else mask_token

      super().__init__(
          errors=__A			,  bos_token=__A			,  eos_token=__A			,  unk_token=__A			,  sep_token=__A			,  cls_token=__A			,  pad_token=__A			,  mask_token=__A			,  add_prefix_space=__A			,  **__A			,  )

      with open(__A			,  encoding='utf-8'   ) as vocab_handle:
       __UpperCamelCase       						= json.load(__A   )
      __UpperCamelCase       						= {v: k for k, v in self.encoder.items()}
      __UpperCamelCase       						= errors  # how to handle errors in decoding
      __UpperCamelCase       						= bytes_to_unicode()
      __UpperCamelCase       						= {v: k for k, v in self.byte_encoder.items()}
      with open(__A			,  encoding='utf-8'   ) as merges_handle:
       __UpperCamelCase       						= merges_handle.read().split('\n'   )[1:-1]
      __UpperCamelCase       						= [tuple(merge.split()   ) for merge in bpe_merges]
      __UpperCamelCase       						= dict(zip(__A			,  range(len(__A   )   )   )   )
      __UpperCamelCase       						= {}
      __UpperCamelCase       						= add_prefix_space

      # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
      __UpperCamelCase       						= re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'   )





     @property
     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      return len(self.encoder   )





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      return dict(self.encoder			,  **self.added_tokens_encoder   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      if token in self.cache:
       return self.cache[token]
      __UpperCamelCase       						= tuple(__A   )
      __UpperCamelCase       						= get_pairs(__A   )

      if not pairs:
       return token

      while True:
       __UpperCamelCase       						= min(__A			,  key=lambda __UpperCAmelCase   : self.bpe_ranks.get(__A			,  float('inf'   )   )   )
       if bigram not in self.bpe_ranks:
        break
       __UpperCamelCase       						= bigram
       __UpperCamelCase       						= []
       __UpperCamelCase       						= 0
       while i < len(__A   ):
        try:
         __UpperCamelCase       						= word.index(__A			,  __A   )
        except ValueError:
         new_word.extend(word[i:]   )
         break
        else:
         new_word.extend(word[i:j]   )
         __UpperCamelCase       						= j

        if word[i] == first and i < len(__A   ) - 1 and word[i + 1] == second:
         new_word.append(first + second   )
         i += 2
        else:
         new_word.append(word[i]   )
         i += 1
       __UpperCamelCase       						= tuple(__A   )
       __UpperCamelCase       						= new_word
       if len(__A   ) == 1:
        break
       else:
        __UpperCamelCase       						= get_pairs(__A   )
      __UpperCamelCase       						= " ".join(__A   )
      __UpperCamelCase       						= word
      return word





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= []
      for token in re.findall(self.pat			,  __A   ):
       __UpperCamelCase       						= "".join(
           self.byte_encoder[b] for b in token.encode('utf-8'   )   )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
       bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__A   ).split(' '   )   )
      return bpe_tokens





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      return self.encoder.get(__A			,  self.encoder.get(self.unk_token   )   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      return self.decoder.get(__A   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= "".join(__A   )
      __UpperCamelCase       						= bytearray([self.byte_decoder[c] for c in text]   ).decode('utf-8'			,  errors=self.errors   )
      return text





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase = None   ):

      '''simple docstring'''




      if not os.path.isdir(__A   ):
       logger.error(F'Vocabulary path ({save_directory}) should be a directory'   )
       return
      __UpperCamelCase       						= os.path.join(
          __A			,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )
      __UpperCamelCase       						= os.path.join(
          __A			,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']   )

      with open(__A			,  'w'			,  encoding='utf-8'   ) as f:
       f.write(json.dumps(self.encoder			,  indent=2			,  sort_keys=__A			,  ensure_ascii=__A   ) + '\n'   )

      __UpperCamelCase       						= 0
      with open(__A			,  'w'			,  encoding='utf-8'   ) as writer:
       writer.write('#version: 0.2\n'   )
       for bpe_tokens, token_index in sorted(self.bpe_ranks.items()			,  key=lambda __UpperCAmelCase   : kv[1]   ):
        if index != token_index:
         logger.warning(
             F'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
             ' Please check that the tokenizer is not corrupted!'   )
         __UpperCamelCase       						= token_index
        writer.write(' '.join(__A   ) + '\n'   )
        index += 1

      return vocab_file, merge_file





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase = None   ):

      '''simple docstring'''




      if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      __UpperCamelCase       						= [self.cls_token_id]
      __UpperCamelCase       						= [self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase = None			,  __UpperCAmelCase = False   ):

      '''simple docstring'''




      if already_has_special_tokens:
       return super().get_special_tokens_mask(
           token_ids_a=__A			,  token_ids_a=__A			,  already_has_special_tokens=__A   )

      if token_ids_a is None:
       return [1] + ([0] * len(__A   )) + [1]
      return [1] + ([0] * len(__A   )) + [1, 1] + ([0] * len(__A   )) + [1]





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase = None   ):

      '''simple docstring'''




      __UpperCamelCase       						= [self.sep_token_id]
      __UpperCamelCase       						= [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 + sep + token_ids_a + sep   ) * [0]







     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase=False			,  **__UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= kwargs.pop('add_prefix_space'			,  self.add_prefix_space   )
      if (is_split_into_words or add_prefix_space) and (len(__A   ) > 0 and not text[0].isspace()):
       __UpperCamelCase       						= " " + text
      return (text, kwargs)





"""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			:       Tuple									=				"."

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






def 							A		(       snake_case   :List[str]       ,      snake_case   :Optional[int]       ,      snake_case   :Optional[Any]	)   ->			Any:
 __UpperCamelCase       						= SavedModel()
 __UpperCamelCase       						= []

 with open(os.path.join(snake_case       ,      'utils'       ,      'tf_ops'       ,      'onnx.json'	)	) as f:
  __UpperCamelCase       						= 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()	)

 __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(snake_case	)
 __UpperCamelCase       						= []

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

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



