






"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase					=     {"""configuration_sew_d""": ["""SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWDConfig"""]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase					=     [
      """SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """SEWDForCTC""",
      """SEWDForSequenceClassification""",
      """SEWDModel""",
      """SEWDPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_sew_d import (
        SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
        SEWDForCTC,
        SEWDForSequenceClassification,
        SEWDModel,
        SEWDPreTrainedModel,
    )


else:
  import sys

  UpperCamelCase					=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)











"""simple docstring"""


from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_clip import CLIPTokenizer


snake_case_								=			logging.get_logger(__name__)

snake_case_								=			{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

snake_case_								=			{
    """vocab_file""": {
        """openai/clip-vit-base-patch32""": """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """openai/clip-vit-base-patch32""": """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """openai/clip-vit-base-patch32""": (
            """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json"""
        ),
    },
}

snake_case_								=			{
    """openai/clip-vit-base-patch32""": 77,
}







class  A_     (	SCREAMING_SNAKE_CASE_							):



						"""simple docstring"""
						__UpperCamelCase													=				VOCAB_FILES_NAMES
						__UpperCamelCase													=				PRETRAINED_VOCAB_FILES_MAP
						__UpperCamelCase													=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						__UpperCamelCase													=				["""input_ids""", """attention_mask"""]
						__UpperCamelCase													=				CLIPTokenizer






						def __init__(   self					:int  ,    lowercase_					:Optional[int]=None  ,    lowercase_					:int=None  ,    lowercase_					:Optional[Any]=None  ,    lowercase_					:Dict="<|endoftext|>"  ,    lowercase_					:List[Any]="<|startoftext|>"  ,    lowercase_					:Any="<|endoftext|>"  ,    lowercase_					:List[str]="<|endoftext|>"  ,    **lowercase_					:Tuple  ,    )							->     List[Any]:
												super().__init__(
												    lowercase_  ,    lowercase_  ,    tokenizer_file=lowercase_  ,    unk_token=lowercase_  ,    bos_token=lowercase_  ,    eos_token=lowercase_  ,    pad_token=lowercase_  ,    **lowercase_  ,    )

												if not isinstance(self.backend_tokenizer.pre_tokenizer  ,    pre_tokenizers.Sequence   ):
																		raise ValueError(
																		    'The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been'
																		    ' heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using'
																		    ' to be compatible with this version.The easiest way to do so is'
																		    ' `CLIPTokenizerFast.from_pretrained("path_to_local_folder_or_hub_repo, from_slow=True)`. If you want'
																		    ' to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of'
																		    ' transformers.'   )

												self._wrap_decode_method_backend_tokenizer()






						def       UpperCAmelCase__	(   self					:Dict   )							->     List[Any]:
												UpperCAmelCase			 =					self.backend_tokenizer.decode

												def new_decode_method(*lowercase_					:List[Any]  ,    **lowercase_					:Optional[Any]   ):
																		UpperCAmelCase			 =					orig_decode_method(*lowercase_  ,    **lowercase_   )
																		UpperCAmelCase			 =					text.replace(self.backend_tokenizer.model.end_of_word_suffix  ,    ' '   ).strip()
																		return text

												UpperCAmelCase			 =					new_decode_method






						def       UpperCAmelCase__	(   self					:Optional[int]  ,    lowercase_					:List[int]  ,    lowercase_					:Optional[List[int]] = None   )							->     List[int]:
												UpperCAmelCase			 =					[self.bos_token_id]
												UpperCAmelCase			 =					[self.eos_token_id]

												if token_ids_a is None:
																		return bos_token + token_ids_a + eos_token
												return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token






						def       UpperCAmelCase__	(   self					:Dict  ,    lowercase_					:List[int]  ,    lowercase_					:Optional[List[int]] = None   )							->     List[int]:
												UpperCAmelCase			 =					[self.bos_token_id]
												UpperCAmelCase			 =					[self.eos_token_id]

												if token_ids_a is None:
																		return len(bos_token + token_ids_a + eos_token   ) * [0]
												return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token   ) * [0]






						def       UpperCAmelCase__	(   self					:Optional[Any]  ,    lowercase_					:str  ,    lowercase_					:Optional[str] = None   )							->     Tuple[str]:
												UpperCAmelCase			 =					self._tokenizer.model.save(lowercase_  ,    name=lowercase_   )
												return tuple(lowercase_   )





