

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 						UpperCamelCase	(			a			)				->     Optional[int]:






     '''simple docstring'''




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






class   _SCREAMING_SNAKE_CASE   (   UpperCamelCase__     ):
 __SCREAMING_SNAKE_CASE					:Any      	=					VOCAB_FILES_NAMES
 __SCREAMING_SNAKE_CASE					:Optional[Any]      	=					PRETRAINED_VOCAB_FILES_MAP
 __SCREAMING_SNAKE_CASE					:int      	=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __SCREAMING_SNAKE_CASE					:List[Any]      	=					['''input_ids''', '''attention_mask''']



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



 def 			snake_case__  (   self		:   Tuple			,				a__		:   int      ):
      return self._id_to_token.get(UpperCamelCase_			,				self.unk_token      )



 def 			snake_case__  (   self		:   str			,				a__		:   str      ):
      return self._token_to_id.get(UpperCamelCase_			,				self._token_to_id.get(self.unk_token      )      )



 def 			snake_case__  (   self		:   List[Any]			,				a__		:   str			,				**a__		:   Optional[int]      ):
      return text.split()



 def 			snake_case__  (   self		:   Tuple			,				a__		:   Tuple=False      ):
      return len(self._id_to_token      )



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



 def 			snake_case__  (   self		:   Optional[int]			,				a__		:   str      ):
      return self._token_to_id.get(UpperCamelCase_			,				self._token_to_id.get(self.unk_token      )      )



 def 			snake_case__  (   self		:   Optional[Any]			,				a__		:   int      ):
      return self._id_to_token.get(UpperCamelCase_			,				self.unk_token      )



 def 			snake_case__  (   self		:   int			,				a__		:   List[int]			,				a__		:   Optional[List[int]] = None      ):
      __magic_name__						       =    [self.cls_token_id]
      __magic_name__						       =    [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		:   Any			,				a__		:   List			,				a__		:   Optional[List] = None			,				a__		:   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]
      __magic_name__						       =    [1] + ([0] * len(UpperCamelCase_      )) + [1]
      if token_ids_a is not None:
           mask += [0] * len(UpperCamelCase_      ) + [1]
      return mask



 def 			snake_case__  (   self		:   Tuple			,				a__		:   Any			,				a__		:   Optional[int]      ):
      __magic_name__						       =    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 			snake_case__  (   self		:   Optional[Any]      ):
      return self.get_vocab_size(with_added_tokens=UpperCamelCase_      )



 def 			snake_case__  (   self		:   Union[str, Any]			,				a__		:   Union[List[str], List[AddedToken]]			,				a__		:   bool = False      ):
      return super()._add_tokens(UpperCamelCase_			,				special_tokens=UpperCamelCase_      )









'''simple docstring'''




import re

from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P


# Sentinels
_lowerCAmelCase         =						object()

# For specifying empty leaf dict `{}`
_lowerCAmelCase         =						object()




def 						UpperCamelCase	(			a		,						a			)				->     Union[str, Any]:






     '''simple docstring'''
     __magic_name__						       =    tuple((re.compile(x + '''$'''			) for x in qs)			)
     for i in range(len(a			) - len(a			) + 1			):
          __magic_name__						       =    [x.match(a			) for x, y in zip(a		,						ks[i:]			)]
          if matches and all(a			):
               return True
     return False




def 						UpperCamelCase	(			a			)				->     Tuple:






     '''simple docstring'''
     def replace(a		,						a			):
          for rule, replacement in rules:
               if _match(a		,						a			):
                    return replacement
          return val

     return replace




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






     '''simple docstring'''
     return [
         # embeddings
         (("transformer", "wpe", "embedding"), P('''mp'''		,						a			)),
         (("transformer", "wte", "embedding"), P('''mp'''		,						a			)),
         # atention
         (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(a		,						'''mp'''			)),
         (("attention", "out_proj", "kernel"), P('''mp'''		,						a			)),
         (("attention", "out_proj", "bias"), None),
         # mlp
         (("mlp", "c_fc", "kernel"), P(a		,						'''mp'''			)),
         (("mlp", "c_fc", "bias"), P('''mp'''			)),
         (("mlp", "c_proj", "kernel"), P('''mp'''		,						a			)),
         (("mlp", "c_proj", "bias"), None),
         # layer norms
         ((r"ln_\d+", "bias"), None),
         ((r"\d+", r"ln_\d+", "scale"), None),
         (("ln_f", "bias"), None),
         (("ln_f", "scale"), None),
     ]




def 						UpperCamelCase	(			a			)				->     str:






     '''simple docstring'''
     __magic_name__						       =    _get_partition_rules()
     __magic_name__						       =    _replacement_rules(a			)
     __magic_name__						       =    {k: _unmatched for k in flatten_dict(a			)}
     __magic_name__						       =    {k: replace(a		,						a			) for k, v in initd.items()}
     assert _unmatched not in result.values(), "Incomplete partition spec."
     return freeze(unflatten_dict(a			)			)






