



'''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     :    Optional[int]      						=					logging.get_logger(__name__)

a     :    Any      						=					{"""vocab_file""": """vocab.txt"""}

a     :    List[Any]      						=					{
    """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     :    List[str]      						=					{
    """facebook/esm2_t6_8M_UR50D""": 1_0_2_4,
    """facebook/esm2_t12_35M_UR50D""": 1_0_2_4,
}



def    __lowerCamelCase						(      _lowercase	)   ->    Optional[Any]:
       with open(_lowercase			,       """r"""	) as f:
              UpperCAmelCase  :	Optional[Any]							  =	f.read().splitlines()
              return [l.strip() for l in lines]


class     UpperCamelCase_				(							__magic_name__    ):
 lowercase    =				VOCAB_FILES_NAMES
 lowercase    =				PRETRAINED_VOCAB_FILES_MAP
 lowercase    =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase    =				['input_ids', 'attention_mask']





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





 def 				_lowercase(						self	,	A					)    ->    str:
        return self._id_to_token.get(A	,	self.unk_token					)





 def 				_lowercase(						self	,	A					)    ->    int:
        return self._token_to_id.get(A	,	self._token_to_id.get(self.unk_token					)					)





 def 				_lowercase(						self	,	A	,	**A					)    ->    Any:
        return text.split()





 def 				_lowercase(						self	,	A=False					)    ->    Optional[int]:
        return len(self._id_to_token					)





 def 				_lowercase(						self					)    ->    Any:
        return {token: i for i, token in enumerate(self.all_tokens					)}





 def 				_lowercase(						self	,	A					)    ->    int:
        return self._token_to_id.get(A	,	self._token_to_id.get(self.unk_token					)					)





 def 				_lowercase(						self	,	A					)    ->    str:
        return self._id_to_token.get(A	,	self.unk_token					)





 def 				_lowercase(						self	,	A	,	A = None					)    ->    List[int]:
        UpperCAmelCase  :	Optional[Any]							  =	[self.cls_token_id]
        UpperCAmelCase  :	str							  =	[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	,	A	,	A = None	,	A = 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]
        UpperCAmelCase  :	Optional[int]							  =	[1] + ([0] * len(A					)) + [1]
        if token_ids_a is not None:
               mask += [0] * len(A					) + [1]
        return mask





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





 @property
 def 				_lowercase(						self					)    ->    int:
        return self.get_vocab_size(with_added_tokens=A					)






 def 				_lowercase(						self	,	A	,	A = False					)    ->    int:
        return super()._add_tokens(A	,	special_tokens=A					)






'''simple docstring'''




from collections.abc import Callable

import numpy as np



def    __lowerCamelCase						(      _lowercase			,       _lowercase			,       _lowercase			,       _lowercase			,       _lowercase	)   ->    np.array:
							UpperCAmelCase  :	Optional[Any]							  =	int(np.ceil((x_end - xa) / step_size	)	)
							UpperCAmelCase  :	str							  =	np.zeros((n + 1,)	)
							UpperCAmelCase  :	Optional[Any]							  =	ya
							UpperCAmelCase  :	Union[str, Any]							  =	xa

							for k in range(_lowercase	):
														UpperCAmelCase  :	Dict							  =	y[k] + step_size * ode_func(_lowercase			,       y[k]	)
														UpperCAmelCase  :	Optional[int]							  =	y[k] + (
														    (step_size / 2) * (ode_func(_lowercase			,       y[k]	) + ode_func(x + step_size			,       _lowercase	))
														)
														x += step_size

							return y


if __name__ == "__main__":
							import doctest

							doctest.testmod()

