


"""simple docstring"""







import os
from typing import List, Optional, Union

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


lowerCAmelCase__      				=   logging.get_logger(__name__)

lowerCAmelCase__      				=   {'''vocab_file''': '''vocab.txt'''}

lowerCAmelCase__      				=   {
    '''vocab_file''': {
        '''facebook/esm2_t6_8M_UR50D''': '''https://huggingface.co/facebook/esm2_t6_8M_UR50D/resolve/main/vocab.txt''',
        '''facebook/esm2_t12_35M_UR50D''': '''https://huggingface.co/facebook/esm2_t12_35M_UR50D/resolve/main/vocab.txt''',
    },
}

lowerCAmelCase__      				=   {
    '''facebook/esm2_t6_8M_UR50D''': 1_024,
    '''facebook/esm2_t12_35M_UR50D''': 1_024,
}
def 					a__			(				SCREAMING_SNAKE_CASE    :    Optional[Any]				):


  '''simple docstring'''







  with open(SCREAMING_SNAKE_CASE				,      "r"				) as f:
    lowerCAmelCase     :     str								=							f.read().splitlines()
    return [l.strip() for l in lines]





class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				Any   =VOCAB_FILES_NAMES
       a  :				List[str]   =PRETRAINED_VOCAB_FILES_MAP
       a  :				Any   =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       a  :				List[str]   =["input_ids", "attention_mask"]

       def __init__(						self		,     snake_case__		,     snake_case__="<unk>"		,     snake_case__="<cls>"		,     snake_case__="<pad>"		,     snake_case__="<mask>"		,     snake_case__="<eos>"		,     **snake_case__		,     ):






         """simple docstring"""





         super().__init__(**snake_case__						)
         lowerCAmelCase     :     List[Any]								=							load_vocab_file(snake_case__						)
         lowerCAmelCase     :     Dict								=							dict(enumerate(self.all_tokens						)						)
         lowerCAmelCase     :     Union[str, Any]								=							{tok: ind for ind, tok in enumerate(self.all_tokens						)}
         lowerCAmelCase     :     Union[str, Any]								=							unk_token
         lowerCAmelCase     :     int								=							cls_token
         lowerCAmelCase     :     Any								=							pad_token
         lowerCAmelCase     :     Union[str, Any]								=							mask_token
         lowerCAmelCase     :     List[str]								=							eos_token
         lowerCAmelCase     :     str								=							self.all_tokens
         self._create_trie(self.unique_no_split_tokens						)

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         return self._id_to_token.get(snake_case__		,     self.unk_token						)

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         return self._token_to_id.get(snake_case__		,     self._token_to_id.get(self.unk_token						)						)

       def        lowercase__							(						self		,     snake_case__		,     **snake_case__						):






         """simple docstring"""





         return text.split()

       def        lowercase__							(						self		,     snake_case__=False						):






         """simple docstring"""





         return len(self._id_to_token						)

       def        lowercase__							(						self						):






         """simple docstring"""





         return {token: i for i, token in enumerate(self.all_tokens						)}

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         return self._token_to_id.get(snake_case__		,     self._token_to_id.get(self.unk_token						)						)

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         return self._id_to_token.get(snake_case__		,     self.unk_token						)

       def        lowercase__							(						self		,     snake_case__		,     snake_case__ = None						):






         """simple docstring"""





         lowerCAmelCase     :     Tuple								=							[self.cls_token_id]
         lowerCAmelCase     :     Dict								=							[self.eos_token_id]  # No sep token in ESM vocabulary
         if token_ids_a is None:
           if self.eos_token_id is None:
             return cls + token_ids_a
           else:
             return cls + token_ids_a + sep
         elif self.eos_token_id is None:
           raise ValueError("Cannot tokenize multiple sequences when EOS token is not set!"						)
         return cls + token_ids_a + sep + token_ids_a + sep  # Multiple inputs always have an EOS token

       def        lowercase__							(						self		,     snake_case__		,     snake_case__ = None		,     snake_case__ = False						):






         """simple docstring"""





         if already_has_special_tokens:
           if token_ids_a is not None:
             raise ValueError(
                 "You should not supply a second sequence if the provided sequence of "
                 "ids is already formatted with special tokens for the model."						)

           return [1 if token in self.all_special_ids else 0 for token in token_ids_a]
         lowerCAmelCase     :     List[str]								=							[1] + ([0] * len(snake_case__						)) + [1]
         if token_ids_a is not None:
           mask += [0] * len(snake_case__						) + [1]
         return mask

       def        lowercase__							(						self		,     snake_case__		,     snake_case__						):






         """simple docstring"""





         lowerCAmelCase     :     Optional[int]								=							os.path.join(snake_case__		,     (filename_prefix + "-" if filename_prefix else "") + "vocab.txt"						)
         with open(snake_case__		,     "w"						) as f:
           f.write("\n".join(self.all_tokens						)						)
         return (vocab_file,)

       @property
       def        lowercase__							(						self						):






         """simple docstring"""





         return self.get_vocab_size(with_added_tokens=snake_case__						)







       def        lowercase__							(						self		,     snake_case__		,     snake_case__ = False						):






         """simple docstring"""





         return super()._add_tokens(snake_case__		,     special_tokens=snake_case__						)






'''simple docstring'''




from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


__SCREAMING_SNAKE_CASE       :     Optional[int]     =  {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXConfig"""]}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __SCREAMING_SNAKE_CASE       :     Tuple     =  ["""GPTNeoXTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __SCREAMING_SNAKE_CASE       :     Dict     =  [
      """GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """GPTNeoXForCausalLM""",
      """GPTNeoXForQuestionAnswering""",
      """GPTNeoXForSequenceClassification""",
      """GPTNeoXForTokenClassification""",
      """GPTNeoXLayer""",
      """GPTNeoXModel""",
      """GPTNeoXPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_gpt_neox import (
        GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
        GPTNeoXForCausalLM,
        GPTNeoXForQuestionAnswering,
        GPTNeoXForSequenceClassification,
        GPTNeoXForTokenClassification,
        GPTNeoXLayer,
        GPTNeoXModel,
        GPTNeoXPreTrainedModel,
    )


else:
  import sys

  __SCREAMING_SNAKE_CASE       :     Any     =  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

