





from dataclasses import asdict, dataclass
from typing import Optional

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


lowercase    : str    	=  logging.get_logger(__name__)

# TODO Update this
lowercase    : str    	=  {
    "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(						_UpperCAmelCase ):
					__A	  =       "esm"

					def __init__(      self,       A=None,       A=None,       A=None,       A=768,       A=12,       A=12,       A=3072,       A=0.1,       A=0.1,       A=1026,       A=0.02,       A=1E-1_2,       A="absolute",       A=True,       A=None,       A=False,       A=False,       A=None,       A=None,       **A,       ):





												"""simple docstring"""

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

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



					def 	_UpperCamelCase     (      self      ):





												"""simple docstring"""

												_UpperCamelCase              =						super().to_dict()
												if isinstance(self.esmfold_config,       lowerCamelCase_      ):
																			_UpperCamelCase              =						self.esmfold_config.to_dict()
												return output






@dataclass
class  __A:
					__A	  =       None
					__A	  =       True
					__A	  =       False
					__A	  =       False
					__A	  =       False
					__A	  =       0

					__A	  =       True
					__A	  =       False

					__A	  =       1_28
					__A	  =       None

					def 	_UpperCamelCase     (      self      ):





												"""simple docstring"""

												if self.trunk is None:
																			_UpperCamelCase              =						TrunkConfig()
												elif isinstance(self.trunk,       lowerCamelCase_      ):
																			_UpperCamelCase              =						TrunkConfig(**self.trunk      )



					def 	_UpperCamelCase     (      self      ):





												"""simple docstring"""

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






@dataclass
class  __A:
					__A	  =       48
					__A	  =       10_24
					__A	  =       1_28
					__A	  =       32
					__A	  =       32
					__A	  =       32
					__A	  =       0
					__A	  =       0
					__A	  =       False
					__A	  =       4
					__A	  =       1_28
					__A	  =       None

					def 	_UpperCamelCase     (      self      ):





												"""simple docstring"""

												if self.structure_module is None:
																			_UpperCamelCase              =						StructureModuleConfig()
												elif isinstance(self.structure_module,       lowerCamelCase_      ):
																			_UpperCamelCase              =						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}.'''      )

												_UpperCamelCase              =						self.sequence_state_dim // self.sequence_head_width
												_UpperCamelCase              =						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 	_UpperCamelCase     (      self      ):





												"""simple docstring"""

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






@dataclass
class  __A:
					__A	  =       3_84
					__A	  =       1_28
					__A	  =       16
					__A	  =       1_28
					__A	  =       12
					__A	  =       4
					__A	  =       8
					__A	  =       0.1
					__A	  =       8
					__A	  =       1
					__A	  =       2
					__A	  =       7
					__A	  =       10
					__A	  =       1E-8
					__A	  =       1E5

					def 	_UpperCamelCase     (      self      ):





												"""simple docstring"""

												return asdict(self      )






def     SCREAMING_SNAKE_CASE			(      ):
							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>",
							)













def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       _UpperCamelCase              =						[]
       if len(lowerCAmelCase					) == 1:
              return [nums.copy()]
       for _ in range(len(lowerCAmelCase					)					):
              _UpperCamelCase              =						nums.pop(0					)
              _UpperCamelCase              =						permute(lowerCAmelCase					)
              for perm in permutations:
                     perm.append(lowerCAmelCase					)
              result.extend(lowerCAmelCase					)
              nums.append(lowerCAmelCase					)
       return result


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):

       def backtrack(lowerCAmelCase					):
              if start == len(lowerCAmelCase					) - 1:
                     output.append(nums[:]					)
              else:
                     for i in range(lowerCAmelCase    ,       len(lowerCAmelCase					)					):
                            _UpperCamelCase       ,		_UpperCamelCase              =						nums[i], nums[start]
                            backtrack(start + 1					)
                            _UpperCamelCase       ,		_UpperCamelCase              =						nums[i], nums[start]  # backtrack

       _UpperCamelCase              =						[]
       backtrack(0					)
       return output


if __name__ == "__main__":
       import doctest

       # use res to print the data in permute2 function
       lowercase    : Optional[Any]    	=  permutea([1, 2, 3])
       print(res)
       doctest.testmod()






