



from dataclasses import asdict, dataclass
from typing import Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase_	 =						logging.get_logger(__name__)

# TODO Update this
lowercase_	 =						{
    "facebook/esm-1b": "https://huggingface.co/facebook/esm-1b/resolve/main/config.json",
    # See all ESM models at https://huggingface.co/models?filter=esm
}






class __A    (						A		):



 '''simple docstring'''







 __lowerCamelCase					: str    = """esm"""



 def __init__(self				,     A=None				,     A=None				,     A=None				,     A=768				,     A=12				,     A=12				,     A=3_072				,     A=0.1				,     A=0.1				,     A=1_026				,     A=0.02				,     A=1E-12				,     A="absolute"				,     A=True				,     A=None				,     A=False				,     A=False				,     A=None				,     A=None				,     **A				,     )					->  int:


      """simple docstring"""



      super().__init__(pad_token_id=A				,     mask_token_id=A				,     **A )

      _a											=						vocab_size
      _a											=						hidden_size
      _a											=						num_hidden_layers
      _a											=						num_attention_heads
      _a											=						intermediate_size
      _a											=						hidden_dropout_prob
      _a											=						attention_probs_dropout_prob
      _a											=						max_position_embeddings
      _a											=						initializer_range
      _a											=						layer_norm_eps
      _a											=						position_embedding_type
      _a											=						use_cache
      _a											=						emb_layer_norm_before
      _a											=						token_dropout
      _a											=						is_folding_model
      if is_folding_model:
           if esmfold_config is None:
                logger.info('''No esmfold_config supplied for folding model, using default values.''' )
                _a											=						EsmFoldConfig()
           elif isinstance(A				,     A ):
                _a											=						EsmFoldConfig(**A )
           _a											=						esmfold_config
           if vocab_list is None:
                logger.warning('''No vocab_list supplied for folding model, assuming the ESM-2 vocabulary!''' )
                _a											=						get_default_vocab_list()
           else:
                _a											=						vocab_list
      else:
           _a											=						None
           _a											=						None
      if self.esmfold_config is not None and getattr(self.esmfold_config				,     '''use_esm_attn_map'''				,     A ):
           raise ValueError('''The HuggingFace port of ESMFold does not support use_esm_attn_map at this time!''' )



 def       a__						(self )					->  Optional[int]:


      """simple docstring"""



      _a											=						super().to_dict()
      if isinstance(self.esmfold_config				,     A ):
           _a											=						self.esmfold_config.to_dict()
      return output






@dataclass
class __A    :



 '''simple docstring'''







 __lowerCamelCase					: str    = None
 __lowerCamelCase					: bool    = True
 __lowerCamelCase					: bool    = False
 __lowerCamelCase					: bool    = False
 __lowerCamelCase					: bool    = False
 __lowerCamelCase					: float    = 0

 __lowerCamelCase					: bool    = True
 __lowerCamelCase					: bool    = False

 __lowerCamelCase					: int    = 128
 __lowerCamelCase					: "TrunkConfig"    = None



 def       a__						(self )					->  List[Any]:


      """simple docstring"""



      if self.trunk is None:
           _a											=						TrunkConfig()
      elif isinstance(self.trunk				,     A ):
           _a											=						TrunkConfig(**self.trunk )



 def       a__						(self )					->  Optional[Any]:


      """simple docstring"""



      _a											=						asdict(self )
      _a											=						self.trunk.to_dict()
      return output






@dataclass
class __A    :



 '''simple docstring'''







 __lowerCamelCase					: int    = 48
 __lowerCamelCase					: int    = 1_024
 __lowerCamelCase					: int    = 128
 __lowerCamelCase					: int    = 32
 __lowerCamelCase					: int    = 32
 __lowerCamelCase					: int    = 32
 __lowerCamelCase					: float    = 0
 __lowerCamelCase					: float    = 0
 __lowerCamelCase					: bool    = False
 __lowerCamelCase					: int    = 4
 __lowerCamelCase					: Optional[int]    = 128
 __lowerCamelCase					: "StructureModuleConfig"    = None



 def       a__						(self )					->  Dict:


      """simple docstring"""



      if self.structure_module is None:
           _a											=						StructureModuleConfig()
      elif isinstance(self.structure_module				,     A ):
           _a											=						StructureModuleConfig(**self.structure_module )

      if self.max_recycles <= 0:
           raise ValueError(f'''`max_recycles` should be positive, got {self.max_recycles}.''' )
      if self.sequence_state_dim % self.sequence_state_dim != 0:
           raise ValueError(
               '''`sequence_state_dim` should be a round multiple of `sequence_state_dim`, got'''
               f''' {self.sequence_state_dim} and {self.sequence_state_dim}.''' )
      if self.pairwise_state_dim % self.pairwise_state_dim != 0:
           raise ValueError(
               '''`pairwise_state_dim` should be a round multiple of `pairwise_state_dim`, got'''
               f''' {self.pairwise_state_dim} and {self.pairwise_state_dim}.''' )

      _a											=						self.sequence_state_dim // self.sequence_head_width
      _a											=						self.pairwise_state_dim // self.pairwise_head_width

      if self.sequence_state_dim != sequence_num_heads * self.sequence_head_width:
           raise ValueError(
               '''`sequence_state_dim` should be equal to `sequence_num_heads * sequence_head_width, got'''
               f''' {self.sequence_state_dim} != {sequence_num_heads} * {self.sequence_head_width}.''' )
      if self.pairwise_state_dim != pairwise_num_heads * self.pairwise_head_width:
           raise ValueError(
               '''`pairwise_state_dim` should be equal to `pairwise_num_heads * pairwise_head_width, got'''
               f''' {self.pairwise_state_dim} != {pairwise_num_heads} * {self.pairwise_head_width}.''' )
      if self.pairwise_state_dim % 2 != 0:
           raise ValueError(f'''`pairwise_state_dim` should be even, got {self.pairwise_state_dim}.''' )

      if self.dropout >= 0.4:
           raise ValueError(f'''`dropout` should not be greater than 0.4, got {self.dropout}.''' )



 def       a__						(self )					->  Optional[int]:


      """simple docstring"""



      _a											=						asdict(self )
      _a											=						self.structure_module.to_dict()
      return output






@dataclass
class __A    :



 '''simple docstring'''







 __lowerCamelCase					: int    = 384
 __lowerCamelCase					: int    = 128
 __lowerCamelCase					: int    = 16
 __lowerCamelCase					: int    = 128
 __lowerCamelCase					: int    = 12
 __lowerCamelCase					: int    = 4
 __lowerCamelCase					: int    = 8
 __lowerCamelCase					: float    = 0.1
 __lowerCamelCase					: int    = 8
 __lowerCamelCase					: int    = 1
 __lowerCamelCase					: int    = 2
 __lowerCamelCase					: int    = 7
 __lowerCamelCase					: int    = 10
 __lowerCamelCase					: float    = 1E-8
 __lowerCamelCase					: float    = 1E5



 def       a__						(self )					->  Any:


      """simple docstring"""



      return asdict(self )





def lowerCAmelCase						():



     """simple docstring"""



     return (
         "<cls>",
         "<pad>",
         "<eos>",
         "<unk>",
         "L",
         "A",
         "G",
         "V",
         "S",
         "E",
         "R",
         "T",
         "I",
         "D",
         "P",
         "K",
         "Q",
         "N",
         "F",
         "Y",
         "M",
         "H",
         "W",
         "C",
         "X",
         "B",
         "U",
         "Z",
         "O",
         ".",
         "-",
         "<null_1>",
         "<mask>",
     )








'''simple docstring'''





from __future__ import annotations

import typing
from collections.abc import Iterable

import numpy as np

lowercase_	 =						typing.Union[Iterable[float], Iterable[int], np.ndarray]  # noqa: UP007
lowercase_	 =						typing.Union[np.floataa, int, float]  # noqa: UP007




def lowerCAmelCase						(__A						,			__A):



     """simple docstring"""



     return np.sqrt(np.sum((np.asarray(__A) - np.asarray(__A)) ** 2))




def lowerCAmelCase						(__A						,			__A):



     """simple docstring"""



     return sum((va - va) ** 2 for va, va in zip(__A						,			__A)) ** (1 / 2)


if __name__ == "__main__":




  def lowerCAmelCase						():



       """simple docstring"""



       from timeit import timeit

       print('''Without Numpy''')
       print(
           timeit(
               '''euclidean_distance_no_np([1, 2, 3], [4, 5, 6])'''						,			number=10_000						,			globals=globals()						,			))
       print('''With Numpy''')
       print(
           timeit(
               '''euclidean_distance([1, 2, 3], [4, 5, 6])'''						,			number=10_000						,			globals=globals()						,			))
  benchmark()



