"""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


__A  =				logging.get_logger(__name__)

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

__A  =				{
    '''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''',
    },
}

__A  =				{
    '''facebook/esm2_t6_8M_UR50D''': 1024,
    '''facebook/esm2_t12_35M_UR50D''': 1024,
}


def    lowercase_   (   _lowerCamelCase:	str      ) ->      Dict:



							'''simple docstring'''

							with open(_lowerCamelCase						,   "r"      ) as f:
														__lowerCamelCase					:		Optional[int]		   =     f.read().splitlines()
														return [l.strip() for l in lines]







class  _snake_case     (					a__		):
						snake_case__			  =			VOCAB_FILES_NAMES
						snake_case__			  =			PRETRAINED_VOCAB_FILES_MAP
						snake_case__			  =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						snake_case__			  =			["input_ids", "attention_mask"]






						def __init__(       self      :			List[Any]							,					UpperCAmelCase      :			Any							,					UpperCAmelCase      :			Optional[Any]="<unk>"							,					UpperCAmelCase      :			Optional[Any]="<cls>"							,					UpperCAmelCase      :			int="<pad>"							,					UpperCAmelCase      :			Dict="<mask>"							,					UpperCAmelCase      :			Union[str, Any]="<eos>"							,					**UpperCAmelCase      :			str							,					):
													super().__init__(**UpperCAmelCase    )
													__lowerCamelCase					:		List[Any]		   =     load_vocab_file(UpperCAmelCase    )
													__lowerCamelCase					:		Union[str, Any]		   =     dict(enumerate(self.all_tokens    )    )
													__lowerCamelCase					:		str		   =     {tok: ind for ind, tok in enumerate(self.all_tokens    )}
													__lowerCamelCase					:		Any		   =     unk_token
													__lowerCamelCase					:		str		   =     cls_token
													__lowerCamelCase					:		Optional[int]		   =     pad_token
													__lowerCamelCase					:		Optional[Any]		   =     mask_token
													__lowerCamelCase					:		Tuple		   =     eos_token
													__lowerCamelCase					:		Optional[int]		   =     self.all_tokens
													self._create_trie(self.unique_no_split_tokens    )






						def       lowerCamelCase__     (       self      :			List[str]							,					UpperCAmelCase      :			int    ):
													return self._id_to_token.get(UpperCAmelCase							,					self.unk_token    )






						def       lowerCamelCase__     (       self      :			List[str]							,					UpperCAmelCase      :			str    ):
													return self._token_to_id.get(UpperCAmelCase							,					self._token_to_id.get(self.unk_token    )    )






						def       lowerCamelCase__     (       self      :			Optional[int]							,					UpperCAmelCase      :			Union[str, Any]							,					**UpperCAmelCase      :			Tuple    ):
													return text.split()






						def       lowerCamelCase__     (       self      :			str							,					UpperCAmelCase      :			str=False    ):
													return len(self._id_to_token    )






						def       lowerCamelCase__     (       self      :			Optional[int]    ):
													return {token: i for i, token in enumerate(self.all_tokens    )}






						def       lowerCamelCase__     (       self      :			List[Any]							,					UpperCAmelCase      :			str    ):
													return self._token_to_id.get(UpperCAmelCase							,					self._token_to_id.get(self.unk_token    )    )






						def       lowerCamelCase__     (       self      :			Optional[Any]							,					UpperCAmelCase      :			int    ):
													return self._id_to_token.get(UpperCAmelCase							,					self.unk_token    )






						def       lowerCamelCase__     (       self      :			str							,					UpperCAmelCase      :			List[int]							,					UpperCAmelCase      :			Optional[List[int]] = None    ):
													__lowerCamelCase					:		Dict		   =     [self.cls_token_id]
													__lowerCamelCase					:		Union[str, 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       lowerCamelCase__     (       self      :			Union[str, Any]							,					UpperCAmelCase      :			List							,					UpperCAmelCase      :			Optional[List] = None							,					UpperCAmelCase      :			bool = False    ):
													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					:		str		   =     [1] + ([0] * len(UpperCAmelCase    )) + [1]
													if token_ids_a is not None:
																				mask += [0] * len(UpperCAmelCase    ) + [1]
													return mask






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






						@property
						def       lowerCamelCase__     (       self      :			Optional[int]    ):
													return self.get_vocab_size(with_added_tokens=UpperCAmelCase    )







						def       lowerCamelCase__     (       self      :			Optional[int]							,					UpperCAmelCase      :			Union[List[str], List[AddedToken]]							,					UpperCAmelCase      :			bool = False    ):
													return super()._add_tokens(UpperCAmelCase							,					special_tokens=UpperCAmelCase    )
"""simple docstring"""





# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import doctest
import sys
import warnings
from os.path import abspath, dirname, join

import _pytest

from transformers.testing_utils import HfDoctestModule, HfDocTestParser


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
__A  =				abspath(join(dirname(__file__), '''src'''))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='''ignore''', category=FutureWarning)


def    lowercase_   (   _lowerCamelCase:	List[Any]      ) ->      Union[str, Any]:



							'''simple docstring'''

							config.addinivalue_line(
							    "markers"						,   "is_pt_tf_cross_test: mark test to run only when PT and TF interactions are tested"      )
							config.addinivalue_line(
							    "markers"						,   "is_pt_flax_cross_test: mark test to run only when PT and FLAX interactions are tested"      )
							config.addinivalue_line("markers"						,   "is_pipeline_test: mark test to run only when pipelines are tested"      )
							config.addinivalue_line("markers"						,   "is_staging_test: mark test to run only in the staging environment"      )
							config.addinivalue_line("markers"						,   "accelerate_tests: mark test that require accelerate"      )
							config.addinivalue_line("markers"						,   "tool_tests: mark the tool tests that are run on their specific schedule"      )


def    lowercase_   (   _lowerCamelCase:	Union[str, Any]      ) ->      Any:



							'''simple docstring'''

							from transformers.testing_utils import pytest_addoption_shared

							pytest_addoption_shared(_lowerCamelCase      )


def    lowercase_   (   _lowerCamelCase:	Optional[int]      ) ->      Tuple:



							'''simple docstring'''

							from transformers.testing_utils import pytest_terminal_summary_main

							__lowerCamelCase					:		Any		   =     terminalreporter.config.getoption("--make-reports"      )
							if make_reports:
														pytest_terminal_summary_main(_lowerCamelCase						,   id=_lowerCamelCase      )


def    lowercase_   (   _lowerCamelCase:	Union[str, Any]						,   _lowerCamelCase:	Tuple      ) ->      Dict:



							'''simple docstring'''

							if exitstatus == 5:
														__lowerCamelCase					:		Optional[int]		   =     0


# Doctest custom flag to ignore output.
__A  =				doctest.register_optionflag('''IGNORE_RESULT''')

__A  =				doctest.OutputChecker
class  _snake_case     (					a__		):






						def       lowerCamelCase__     (       self      :			List[str]							,					UpperCAmelCase      :			int							,					UpperCAmelCase      :			Any							,					UpperCAmelCase      :			int    ):
													if IGNORE_RESULT & optionflags:
																				return True
													return OutputChecker.check_output(self							,					UpperCAmelCase							,					UpperCAmelCase							,					UpperCAmelCase    )

__A  =				CustomOutputChecker
__A  =				HfDoctestModule







__A  =				HfDocTestParser