
from dataclasses import asdict, dataclass
from typing import Optional

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


__magic_name__  							=	logging.get_logger(__name__)

# TODO Update this
__magic_name__  							=	{
    '''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        _SCREAMING_SNAKE_CASE	(   __UpperCamelCase			):
      _A    :		int     						=  'esm'
      def __init__(      self		,						lowerCamelCase=None		,						lowerCamelCase=None		,						lowerCamelCase=None		,						lowerCamelCase=7_68		,						lowerCamelCase=12		,						lowerCamelCase=12		,						lowerCamelCase=30_72		,						lowerCamelCase=0.1		,						lowerCamelCase=0.1		,						lowerCamelCase=10_26		,						lowerCamelCase=0.0_2		,						lowerCamelCase=1e-12		,						lowerCamelCase="absolute"		,						lowerCamelCase=True		,						lowerCamelCase=None		,						lowerCamelCase=False		,						lowerCamelCase=False		,						lowerCamelCase=None		,						lowerCamelCase=None		,						**lowerCamelCase		,						):
          super().__init__(pad_token_id=lowerCamelCase		,						mask_token_id=lowerCamelCase		,						**lowerCamelCase			)

          snake_case__    =					vocab_size
          snake_case__    =					hidden_size
          snake_case__    =					num_hidden_layers
          snake_case__    =					num_attention_heads
          snake_case__    =					intermediate_size
          snake_case__    =					hidden_dropout_prob
          snake_case__    =					attention_probs_dropout_prob
          snake_case__    =					max_position_embeddings
          snake_case__    =					initializer_range
          snake_case__    =					layer_norm_eps
          snake_case__    =					position_embedding_type
          snake_case__    =					use_cache
          snake_case__    =					emb_layer_norm_before
          snake_case__    =					token_dropout
          snake_case__    =					is_folding_model
          if is_folding_model:
              if esmfold_config is None:
                  logger.info("No esmfold_config supplied for folding model, using default values."			)
                  snake_case__    =					EsmFoldConfig()
              elif isinstance(lowerCamelCase		,						lowerCamelCase			):
                  snake_case__    =					EsmFoldConfig(**lowerCamelCase			)
              snake_case__    =					esmfold_config
              if vocab_list is None:
                  logger.warning("No vocab_list supplied for folding model, assuming the ESM-2 vocabulary!"			)
                  snake_case__    =					get_default_vocab_list()
              else:
                  snake_case__    =					vocab_list
          else:
              snake_case__    =					None
              snake_case__    =					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 A_      (      self			):
          snake_case__    =					super().to_dict()
          if isinstance(self.esmfold_config		,						lowerCamelCase			):
              snake_case__    =					self.esmfold_config.to_dict()
          return output





@dataclass
class        _SCREAMING_SNAKE_CASE	:
      _A    :		str     						=  None
      _A    :		bool     						=  True
      _A    :		bool     						=  False
      _A    :		bool     						=  False
      _A    :		bool     						=  False
      _A    :		float     						=  0

      _A    :		bool     						=  True
      _A    :		bool     						=  False

      _A    :		int     						=  1_28
      _A    :		"TrunkConfig"     						=  None
      def A_      (      self			):
          if self.trunk is None:
              snake_case__    =					TrunkConfig()
          elif isinstance(self.trunk		,						lowerCamelCase			):
              snake_case__    =					TrunkConfig(**self.trunk			)



      def A_      (      self			):
          snake_case__    =					asdict(self			)
          snake_case__    =					self.trunk.to_dict()
          return output





@dataclass
class        _SCREAMING_SNAKE_CASE	:
      _A    :		int     						=  48
      _A    :		int     						=  10_24
      _A    :		int     						=  1_28
      _A    :		int     						=  32
      _A    :		int     						=  32
      _A    :		int     						=  32
      _A    :		float     						=  0
      _A    :		float     						=  0
      _A    :		bool     						=  False
      _A    :		int     						=  4
      _A    :		Optional[int]     						=  1_28
      _A    :		"StructureModuleConfig"     						=  None
      def A_      (      self			):
          if self.structure_module is None:
              snake_case__    =					StructureModuleConfig()
          elif isinstance(self.structure_module		,						lowerCamelCase			):
              snake_case__    =					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}."""			)

          snake_case__    =					self.sequence_state_dim // self.sequence_head_width
          snake_case__    =					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			):
          snake_case__    =					asdict(self			)
          snake_case__    =					self.structure_module.to_dict()
          return output





@dataclass
class        _SCREAMING_SNAKE_CASE	:
      _A    :		int     						=  3_84
      _A    :		int     						=  1_28
      _A    :		int     						=  16
      _A    :		int     						=  1_28
      _A    :		int     						=  12
      _A    :		int     						=  4
      _A    :		int     						=  8
      _A    :		float     						=  0.1
      _A    :		int     						=  8
      _A    :		int     						=  1
      _A    :		int     						=  2
      _A    :		int     						=  7
      _A    :		int     						=  10
      _A    :		float     						=  1e-8
      _A    :		float     						=  1e5
      def A_      (      self			):
          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>",
    )





from __future__ import annotations

import math





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase				):

    if 1 < number < 4:
        # 2 and 3 are primes
        return True
    elif number < 2 or number % 2 == 0 or number % 3 == 0:
        # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
        return False

    # All primes number are in format of 6k +/- 1
    for i in range(5     ,		int(math.sqrt(__lowerCAmelCase				) + 1				)     ,		6				):
        if number % i == 0 or number % (i + 2) == 0:
            return False
    return True





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase				):
    snake_case__    =					str(__lowerCAmelCase				)
    snake_case__    =					[n]
    for i in range(1     ,		len(__lowerCAmelCase				)				):
        list_nums.append(int(str_num[i:]				)				)
        list_nums.append(int(str_num[:-i]				)				)
    return list_nums





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase				):
    if len(str(__lowerCAmelCase				)				) > 3:
        if not is_prime(int(str(__lowerCAmelCase				)[-3:]				)				) or not is_prime(int(str(__lowerCAmelCase				)[:3]				)				):
            return False
    return True





def 						SCREAMING_SNAKE_CASE__     (   __lowerCAmelCase = 11				):
    snake_case__    =					[]
    snake_case__    =					13
    while len(__lowerCAmelCase				) != count:
        if validate(__lowerCAmelCase				):
            snake_case__    =					list_truncated_nums(__lowerCAmelCase				)
            if all(is_prime(__lowerCAmelCase				) for i in list_nums				):
                list_truncated_primes.append(__lowerCAmelCase				)
        num += 2
    return list_truncated_primes





def 						SCREAMING_SNAKE_CASE__     (   ):
    return sum(compute_truncated_primes(11				)				)


if __name__ == "__main__":
     print(F'''{sum(compute_truncated_primes(11)) = }''')



