



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""": 1024,
    """facebook/esm2_t12_35M_UR50D""": 1024,
}

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			Dict    ):
				"""simple docstring"""







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






class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):
							__lowerCamelCase	:	int    =VOCAB_FILES_NAMES
							__lowerCamelCase	:	str    =PRETRAINED_VOCAB_FILES_MAP
							__lowerCamelCase	:	Optional[int]    =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__lowerCamelCase	:	List[Any]    =['input_ids', 'attention_mask']





							def __init__(   self		:		Any      ,				__lowercase		:		Tuple      ,				__lowercase		:		Tuple="<unk>"      ,				__lowercase		:		Optional[Any]="<cls>"      ,				__lowercase		:		Tuple="<pad>"      ,				__lowercase		:		Optional[Any]="<mask>"      ,				__lowercase		:		int="<eos>"      ,				**__lowercase		:		Tuple      ,				):

											'''simple docstring'''
											super().__init__(**__lowercase	)
											__a       =		load_vocab_file(__lowercase	)
											__a       =		dict(enumerate(self.all_tokens	)	)
											__a       =		{tok: ind for ind, tok in enumerate(self.all_tokens	)}
											__a       =		unk_token
											__a       =		cls_token
											__a       =		pad_token
											__a       =		mask_token
											__a       =		eos_token
											__a       =		self.all_tokens
											self._create_trie(self.unique_no_split_tokens	)





							def 						UpperCamelCase_					(   self		:		Dict      ,				__lowercase		:		int	):

											'''simple docstring'''
											return self._id_to_token.get(__lowercase      ,				self.unk_token	)





							def 						UpperCamelCase_					(   self		:		Optional[int]      ,				__lowercase		:		str	):

											'''simple docstring'''
											return self._token_to_id.get(__lowercase      ,				self._token_to_id.get(self.unk_token	)	)





							def 						UpperCamelCase_					(   self		:		List[str]      ,				__lowercase		:		List[Any]      ,				**__lowercase		:		Any	):

											'''simple docstring'''
											return text.split()





							def 						UpperCamelCase_					(   self		:		Tuple      ,				__lowercase		:		Any=False	):

											'''simple docstring'''
											return len(self._id_to_token	)





							def 						UpperCamelCase_					(   self		:		Any	):

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





							def 						UpperCamelCase_					(   self		:		Union[str, Any]      ,				__lowercase		:		str	):

											'''simple docstring'''
											return self._token_to_id.get(__lowercase      ,				self._token_to_id.get(self.unk_token	)	)





							def 						UpperCamelCase_					(   self		:		Optional[Any]      ,				__lowercase		:		int	):

											'''simple docstring'''
											return self._id_to_token.get(__lowercase      ,				self.unk_token	)





							def 						UpperCamelCase_					(   self		:		Optional[int]      ,				__lowercase		:		List[int]      ,				__lowercase		:		Optional[List[int]] = None	):

											'''simple docstring'''
											__a       =		[self.cls_token_id]
											__a       =		[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 						UpperCamelCase_					(   self		:		List[Any]      ,				__lowercase		:		List      ,				__lowercase		:		Optional[List] = None      ,				__lowercase		:		bool = 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]
											__a       =		[1] + ([0] * len(__lowercase	)) + [1]
											if token_ids_a is not None:
															mask += [0] * len(__lowercase	) + [1]
											return mask





							def 						UpperCamelCase_					(   self		:		str      ,				__lowercase		:		int      ,				__lowercase		:		List[str]	):

											'''simple docstring'''
											__a       =		os.path.join(__lowercase      ,				(filename_prefix + """-""" if filename_prefix else """""") + """vocab.txt"""	)
											with open(__lowercase      ,				"""w"""	) as f:
															f.write("""\n""".join(self.all_tokens	)	)
											return (vocab_file,)





							@property
							def 						UpperCamelCase_					(   self		:		Tuple	):

											'''simple docstring'''
											return self.get_vocab_size(with_added_tokens=__lowercase	)







							def 						UpperCamelCase_					(   self		:		Optional[Any]      ,				__lowercase		:		Union[List[str], List[AddedToken]]      ,				__lowercase		:		bool = False	):

											'''simple docstring'''
											return super()._add_tokens(__lowercase      ,				special_tokens=__lowercase	)





from typing import TYPE_CHECKING

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


lowerCamelCase__			= {
    """configuration_nezha""": ["""NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NezhaConfig"""],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__			= [
						    """NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """NezhaForNextSentencePrediction""",
						    """NezhaForMaskedLM""",
						    """NezhaForPreTraining""",
						    """NezhaForMultipleChoice""",
						    """NezhaForQuestionAnswering""",
						    """NezhaForSequenceClassification""",
						    """NezhaForTokenClassification""",
						    """NezhaModel""",
						    """NezhaPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_nezha import (
												    NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST,
												    NezhaForMaskedLM,
												    NezhaForMultipleChoice,
												    NezhaForNextSentencePrediction,
												    NezhaForPreTraining,
												    NezhaForQuestionAnswering,
												    NezhaForSequenceClassification,
												    NezhaForTokenClassification,
												    NezhaModel,
												    NezhaPreTrainedModel,
												)


else:
						import sys

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