


import os
from typing import List, Optional, Union

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


snake_case							:	Dict					      =				logging.get_logger(__name__)

snake_case							:	List[str]					      =				{'''vocab_file''': '''vocab.txt'''}

snake_case							:	Optional[int]					      =				{
    '''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''',
    },
}

snake_case							:	List[str]					      =				{
    '''facebook/esm2_t6_8M_UR50D''': 10_24,
    '''facebook/esm2_t12_35M_UR50D''': 10_24,
}






def 							__lowercase       (			__lowerCAmelCase							:    Dict       ):
							with open(__lowerCAmelCase ,   'r'       ) as f:
														a__					=					f.read().splitlines()
														return [l.strip() for l in lines]







class 	snake_case_       (lowerCamelCase_				):
					UpperCAmelCase__ :   List[str]   				=      VOCAB_FILES_NAMES
					UpperCAmelCase__ :   Optional[int]   				=      PRETRAINED_VOCAB_FILES_MAP
					UpperCAmelCase__ :   List[Any]   				=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					UpperCAmelCase__ :   int   				=      ['''input_ids''', '''attention_mask''']
					def __init__(				self       :Optional[int]      ,__snake_case       :int      ,__snake_case       :int="<unk>"      ,__snake_case       :Any="<cls>"      ,__snake_case       :Optional[Any]="<pad>"      ,__snake_case       :List[str]="<mask>"      ,__snake_case       :Union[str, Any]="<eos>"      ,**__snake_case       :List[Any]      ,) ->   Dict:
												super().__init__(**__snake_case				)
												a__					=					load_vocab_file(__snake_case				)
												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 			lowerCamelCase__(				self       :Dict      ,__snake_case       :int				) ->   str:
												return self._id_to_token.get(__snake_case      ,self.unk_token				)
					def 			lowerCamelCase__(				self       :Union[str, Any]      ,__snake_case       :str				) ->   int:
												return self._token_to_id.get(__snake_case      ,self._token_to_id.get(self.unk_token				)				)
					def 			lowerCamelCase__(				self       :Union[str, Any]      ,__snake_case       :List[Any]      ,**__snake_case       :int				) ->   Any:
												return text.split()
					def 			lowerCamelCase__(				self       :List[Any]      ,__snake_case       :Any=False				) ->   str:
												return len(self._id_to_token				)
					def 			lowerCamelCase__(				self       :Union[str, Any]				) ->   Optional[Any]:
												return {token: i for i, token in enumerate(self.all_tokens				)}
					def 			lowerCamelCase__(				self       :Any      ,__snake_case       :str				) ->   int:
												return self._token_to_id.get(__snake_case      ,self._token_to_id.get(self.unk_token				)				)
					def 			lowerCamelCase__(				self       :Tuple      ,__snake_case       :int				) ->   str:
												return self._id_to_token.get(__snake_case      ,self.unk_token				)
					def 			lowerCamelCase__(				self       :Optional[int]      ,__snake_case       :List[int]      ,__snake_case       :Optional[List[int]] = None				) ->   List[int]:
												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 			lowerCamelCase__(				self       :Tuple      ,__snake_case       :List      ,__snake_case       :Optional[List] = None      ,__snake_case       :bool = False				) ->   List[int]:
												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(__snake_case				)) + [1]
												if token_ids_a is not None:
																			mask += [0] * len(__snake_case				) + [1]
												return mask
					def 			lowerCamelCase__(				self       :Any      ,__snake_case       :str      ,__snake_case       :List[str]				) ->   Optional[Any]:
												a__					=					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 			lowerCamelCase__(				self       :Tuple				) ->   int:
												return self.get_vocab_size(with_added_tokens=__snake_case				)



					def 			lowerCamelCase__(				self       :Tuple      ,__snake_case       :Union[List[str], List[AddedToken]]      ,__snake_case       :bool = False				) ->   int:
												return super()._add_tokens(__snake_case      ,special_tokens=__snake_case				)








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case							:	Optional[int]					      =				{
    '''configuration_clipseg''': [
        '''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''CLIPSegConfig''',
        '''CLIPSegTextConfig''',
        '''CLIPSegVisionConfig''',
    ],
    '''processing_clipseg''': ['''CLIPSegProcessor'''],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						snake_case							:	List[str]					      =				[
						    '''CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''CLIPSegModel''',
						    '''CLIPSegPreTrainedModel''',
						    '''CLIPSegTextModel''',
						    '''CLIPSegVisionModel''',
						    '''CLIPSegForImageSegmentation''',
						]

if TYPE_CHECKING:
						from .configuration_clipseg import (
						    CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    CLIPSegConfig,
						    CLIPSegTextConfig,
						    CLIPSegVisionConfig,
						)
						from .processing_clipseg import CLIPSegProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_clipseg import (
												    CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
												    CLIPSegForImageSegmentation,
												    CLIPSegModel,
												    CLIPSegPreTrainedModel,
												    CLIPSegTextModel,
												    CLIPSegVisionModel,
												)

else:
						import sys

						snake_case							:	Optional[int]					      =				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




