
'''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


_lowercase :  Optional[Any]    							=       logging.get_logger(__name__)

_lowercase :  str    							=       {"vocab_file": "vocab.txt"}

_lowercase :  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",
    },
}

_lowercase :  Optional[int]    							=       {
    "facebook/esm2_t6_8M_UR50D": 1_0_2_4,
    "facebook/esm2_t12_35M_UR50D": 1_0_2_4,
}
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: Any							):



						"""simple docstring"""





						with open(__SCREAMING_SNAKE_CASE      ,      '''r'''							) as f:
												lowercase_	:     Dict													=       f.read().splitlines()
												return [l.strip() for l in lines]






class  lowerCAmelCase__   (  lowerCamelCase_     ):
					lowerCAmelCase_        =     VOCAB_FILES_NAMES
					lowerCAmelCase_        =     PRETRAINED_VOCAB_FILES_MAP
					lowerCAmelCase_        =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCAmelCase_        =     ['''input_ids''', '''attention_mask''']






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


											"""simple docstring"""





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






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





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






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





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






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											return text.split()






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE=False		):


											"""simple docstring"""





											return len(self._id_to_token		)






					def 	_snake_case    (   self		):


											"""simple docstring"""





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






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





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






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





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






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE = None		):


											"""simple docstring"""





											lowercase_	:     Dict													=       [self.cls_token_id]
											lowercase_	:     List[Any]													=       [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 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE = None				,							__SCREAMING_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]
											lowercase_	:     int													=       [1] + ([0] * len(__SCREAMING_SNAKE_CASE		)) + [1]
											if token_ids_a is not None:
																	mask += [0] * len(__SCREAMING_SNAKE_CASE		) + [1]
											return mask






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_	:     List[str]													=       os.path.join(__SCREAMING_SNAKE_CASE				,							(filename_prefix + '''-''' if filename_prefix else '''''') + '''vocab.txt'''		)
											with open(__SCREAMING_SNAKE_CASE				,							'''w'''		) as f:
																	f.write('''\n'''.join(self.all_tokens		)		)
											return (vocab_file,)






					@property
					def 	_snake_case    (   self		):


											"""simple docstring"""





											return self.get_vocab_size(with_added_tokens=__SCREAMING_SNAKE_CASE		)






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE = False		):


											"""simple docstring"""





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





'''simple docstring'''







from typing import TYPE_CHECKING

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


_lowercase :  Union[str, Any]    							=       {
    "configuration_pix2struct": [
        "PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Pix2StructConfig",
        "Pix2StructTextConfig",
        "Pix2StructVisionConfig",
    ],
    "processing_pix2struct": ["Pix2StructProcessor"],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase :  Dict    							=       ["Pix2StructImageProcessor"]


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase :  List[str]    							=       [
							    "PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "Pix2StructPreTrainedModel",
							    "Pix2StructForConditionalGeneration",
							    "Pix2StructVisionModel",
							    "Pix2StructTextModel",
							]

if TYPE_CHECKING:
							from .configuration_pixastruct import (
							    PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    PixaStructConfig,
							    PixaStructTextConfig,
							    PixaStructVisionConfig,
							)
							from .processing_pixastruct import PixaStructProcessor

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .image_processing_pixastruct import PixaStructImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_pixastruct import (
														    PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    PixaStructForConditionalGeneration,
														    PixaStructPreTrainedModel,
														    PixaStructTextModel,
														    PixaStructVisionModel,
														)

else:
							import sys

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



