






"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional

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


lowerCamelCase_							      = logging.get_logger(__name__)

# TODO Update this
lowerCamelCase_							      = {
    '''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      UpperCamelCase_			(__A	):
	__magic_name__       =							'''esm'''





	def __init__( self   :					Any      ,      lowerCAmelCase_   :					Dict=None      ,      lowerCAmelCase_   :					Optional[Any]=None      ,      lowerCAmelCase_   :					int=None      ,      lowerCAmelCase_   :					Union[str, Any]=768      ,      lowerCAmelCase_   :					List[str]=12      ,      lowerCAmelCase_   :					int=12      ,      lowerCAmelCase_   :					Optional[int]=3_072      ,      lowerCAmelCase_   :					Union[str, Any]=0.1      ,      lowerCAmelCase_   :					Union[str, Any]=0.1      ,      lowerCAmelCase_   :					int=1_026      ,      lowerCAmelCase_   :					List[str]=0.0_2      ,      lowerCAmelCase_   :					List[Any]=1e-12      ,      lowerCAmelCase_   :					Any="absolute"      ,      lowerCAmelCase_   :					int=True      ,      lowerCAmelCase_   :					Union[str, Any]=None      ,      lowerCAmelCase_   :					str=False      ,      lowerCAmelCase_   :					str=False      ,      lowerCAmelCase_   :					List[Any]=None      ,      lowerCAmelCase_   :					int=None      ,      **lowerCAmelCase_   :					Optional[int]      ,      )		->     Optional[Any]:
				super().__init__(pad_token_id=lowerCAmelCase_      ,      mask_token_id=lowerCAmelCase_      ,      **lowerCAmelCase_		)

				UpperCAmelCase_	:					str     	=   vocab_size
				UpperCAmelCase_	:					int     	=   hidden_size
				UpperCAmelCase_	:					List[Any]     	=   num_hidden_layers
				UpperCAmelCase_	:					Any     	=   num_attention_heads
				UpperCAmelCase_	:					Optional[int]     	=   intermediate_size
				UpperCAmelCase_	:					str     	=   hidden_dropout_prob
				UpperCAmelCase_	:					Optional[int]     	=   attention_probs_dropout_prob
				UpperCAmelCase_	:					int     	=   max_position_embeddings
				UpperCAmelCase_	:					Dict     	=   initializer_range
				UpperCAmelCase_	:					Dict     	=   layer_norm_eps
				UpperCAmelCase_	:					Any     	=   position_embedding_type
				UpperCAmelCase_	:					Any     	=   use_cache
				UpperCAmelCase_	:					Union[str, Any]     	=   emb_layer_norm_before
				UpperCAmelCase_	:					List[str]     	=   token_dropout
				UpperCAmelCase_	:					List[str]     	=   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_	:					str     	=   EsmFoldConfig()
							elif isinstance(lowerCAmelCase_      ,      lowerCAmelCase_		):
										UpperCAmelCase_	:					Tuple     	=   EsmFoldConfig(**lowerCAmelCase_		)
							UpperCAmelCase_	:					int     	=   esmfold_config
							if vocab_list is None:
										logger.warning("No vocab_list supplied for folding model, assuming the ESM-2 vocabulary!"		)
										UpperCAmelCase_	:					Dict     	=   get_default_vocab_list()
							else:
										UpperCAmelCase_	:					Optional[int]     	=   vocab_list
				else:
							UpperCAmelCase_	:					Optional[int]     	=   None
							UpperCAmelCase_	:					Union[str, Any]     	=   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 	_SCREAMING_SNAKE_CASE ( self   :					Optional[int]		)		->     str:
				UpperCAmelCase_	:					Optional[Any]     	=   super().to_dict()
				if isinstance(self.esmfold_config      ,      lowerCAmelCase_		):
							UpperCAmelCase_	:					Union[str, Any]     	=   self.esmfold_config.to_dict()
				return output







@dataclass
class      UpperCamelCase_			:
	__magic_name__       =							None
	__magic_name__       =							True
	__magic_name__       =							False
	__magic_name__       =							False
	__magic_name__       =							False
	__magic_name__       =							0

	__magic_name__       =							True
	__magic_name__       =							False

	__magic_name__       =							1_28
	__magic_name__       =							None





	def 	_SCREAMING_SNAKE_CASE ( self   :					Dict		)		->     List[Any]:
				if self.trunk is None:
							UpperCAmelCase_	:					List[str]     	=   TrunkConfig()
				elif isinstance(self.trunk      ,      lowerCAmelCase_		):
							UpperCAmelCase_	:					Dict     	=   TrunkConfig(**self.trunk		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					Tuple		)		->     Tuple:
				UpperCAmelCase_	:					List[Any]     	=   asdict(self		)
				UpperCAmelCase_	:					Dict     	=   self.trunk.to_dict()
				return output







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





	def 	_SCREAMING_SNAKE_CASE ( self   :					List[Any]		)		->     Tuple:
				if self.structure_module is None:
							UpperCAmelCase_	:					int     	=   StructureModuleConfig()
				elif isinstance(self.structure_module      ,      lowerCAmelCase_		):
							UpperCAmelCase_	:					Optional[Any]     	=   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_	:					Dict     	=   self.sequence_state_dim // self.sequence_head_width
				UpperCAmelCase_	:					Tuple     	=   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 	_SCREAMING_SNAKE_CASE ( self   :					Dict		)		->     Dict:
				UpperCAmelCase_	:					Optional[int]     	=   asdict(self		)
				UpperCAmelCase_	:					int     	=   self.structure_module.to_dict()
				return output







@dataclass
class      UpperCamelCase_			:
	__magic_name__       =							3_84
	__magic_name__       =							1_28
	__magic_name__       =							16
	__magic_name__       =							1_28
	__magic_name__       =							12
	__magic_name__       =							4
	__magic_name__       =							8
	__magic_name__       =							0.1
	__magic_name__       =							8
	__magic_name__       =							1
	__magic_name__       =							2
	__magic_name__       =							7
	__magic_name__       =							10
	__magic_name__       =							1e-8
	__magic_name__       =							1e5





	def 	_SCREAMING_SNAKE_CASE ( self   :					Dict		)		->     Dict:
				return asdict(self		)





def 							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>",
			)











"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowerCamelCase_							      = logging.get_logger(__name__)


lowerCamelCase_							      = {
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

lowerCamelCase_							      = {
    '''vocab_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'''
    },
    '''merges_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'''
    },
    '''tokenizer_config_file''': {
        '''facebook/blenderbot_small-90M''': (
            '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'''
        )
    },
}

lowerCamelCase_							      = {'''facebook/blenderbot_small-90M''': 512}

def 							snake_case (  A__		):
			UpperCAmelCase_	:					str     	=   set()
			UpperCAmelCase_	:					int     	=   word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)		)
						UpperCAmelCase_	:					Dict     	=   char

			UpperCAmelCase_	:					List[Any]     	=   set(A__		)
			return pairs







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





	def __init__( self   :					Optional[int]      ,      lowerCAmelCase_   :					Dict      ,      lowerCAmelCase_   :					List[str]      ,      lowerCAmelCase_   :					Optional[int]="__start__"      ,      lowerCAmelCase_   :					str="__end__"      ,      lowerCAmelCase_   :					Union[str, Any]="__unk__"      ,      lowerCAmelCase_   :					Union[str, Any]="__null__"      ,      **lowerCAmelCase_   :					List[Any]      ,      )		->     str:
				super().__init__(unk_token=lowerCAmelCase_      ,      bos_token=lowerCAmelCase_      ,      eos_token=lowerCAmelCase_      ,      pad_token=lowerCAmelCase_      ,      **lowerCAmelCase_		)

				with open(lowerCAmelCase_      ,      encoding="utf-8"		) as vocab_handle:
							UpperCAmelCase_	:					str     	=   json.load(lowerCAmelCase_		)
				UpperCAmelCase_	:					Union[str, Any]     	=   {v: k for k, v in self.encoder.items()}
				with open(lowerCAmelCase_      ,      encoding="utf-8"		) as merges_handle:
							UpperCAmelCase_	:					Optional[Any]     	=   merges_handle.read().split("\n"		)[1:-1]
				UpperCAmelCase_	:					str     	=   [tuple(merge.split()		) for merge in merges]
				UpperCAmelCase_	:					Any     	=   dict(zip(lowerCAmelCase_      ,      range(len(lowerCAmelCase_		)		)		)		)
				UpperCAmelCase_	:					Any     	=   {}





	@property
	def 	_SCREAMING_SNAKE_CASE ( self   :					str		)		->     int:
				return len(self.encoder		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					List[Any]		)		->     Dict:
				return dict(self.encoder      ,      **self.added_tokens_encoder		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					List[str]      ,      lowerCAmelCase_   :					str		)		->     str:
				if token in self.cache:
							return self.cache[token]
				UpperCAmelCase_	:					Dict     	=   re.sub("([.,!?()])"      ,      R" \1"      ,      lowerCAmelCase_		)
				UpperCAmelCase_	:					int     	=   re.sub("(')"      ,      R" \1 "      ,      lowerCAmelCase_		)
				UpperCAmelCase_	:					List[str]     	=   re.sub(R"\s{2,}"      ,      " "      ,      lowerCAmelCase_		)
				if "\n" in token:
							UpperCAmelCase_	:					Tuple     	=   token.replace("\n"      ,      " __newln__"		)

				UpperCAmelCase_	:					Tuple     	=   token.split(" "		)
				UpperCAmelCase_	:					int     	=   []
				for token in tokens:
							if not len(lowerCAmelCase_		):
										continue

							UpperCAmelCase_	:					Any     	=   token.lower()
							UpperCAmelCase_	:					List[str]     	=   tuple(lowerCAmelCase_		)
							UpperCAmelCase_	:					List[str]     	=   tuple(list(word[:-1]		) + [word[-1] + "</w>"]		)
							UpperCAmelCase_	:					List[Any]     	=   get_pairs(lowerCAmelCase_		)

							if not pairs:
										words.append(lowerCAmelCase_		)
										continue

							while True:
										UpperCAmelCase_	:					Union[str, Any]     	=   min(lowerCAmelCase_      ,      key=lambda lowerCAmelCase_		: self.bpe_ranks.get(lowerCAmelCase_      ,      float("inf"		)		)		)
										if bigram not in self.bpe_ranks:
													break
										UpperCAmelCase_	,      UpperCAmelCase_	:					Dict     	=   bigram
										UpperCAmelCase_	:					Dict     	=   []
										UpperCAmelCase_	:					Dict     	=   0

										while i < len(lowerCAmelCase_		):
													try:
																UpperCAmelCase_	:					int     	=   word.index(lowerCAmelCase_      ,      lowerCAmelCase_		)
																new_word.extend(word[i:j]		)
																UpperCAmelCase_	:					Any     	=   j
													except ValueError:
																new_word.extend(word[i:]		)
																break

													if word[i] == first and i < len(lowerCAmelCase_		) - 1 and word[i + 1] == second:
																new_word.append(first + second		)
																i += 2
													else:
																new_word.append(word[i]		)
																i += 1
										UpperCAmelCase_	:					Dict     	=   tuple(lowerCAmelCase_		)
										UpperCAmelCase_	:					Any     	=   new_word
										if len(lowerCAmelCase_		) == 1:
													break
										else:
													UpperCAmelCase_	:					Union[str, Any]     	=   get_pairs(lowerCAmelCase_		)
							UpperCAmelCase_	:					Optional[int]     	=   "@@ ".join(lowerCAmelCase_		)
							UpperCAmelCase_	:					List[str]     	=   word[:-4]

							UpperCAmelCase_	:					Optional[Any]     	=   word
							words.append(lowerCAmelCase_		)
				return " ".join(lowerCAmelCase_		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					Tuple      ,      lowerCAmelCase_   :					str		)		->     List[str]:
				UpperCAmelCase_	:					Union[str, Any]     	=   []

				UpperCAmelCase_	:					List[Any]     	=   re.findall(R"\S+\n?"      ,      lowerCAmelCase_		)

				for token in words:
							split_tokens.extend(list(self.bpe(lowerCAmelCase_		).split(" "		)		)		)
				return split_tokens





	def 	_SCREAMING_SNAKE_CASE ( self   :					Dict      ,      lowerCAmelCase_   :					str		)		->     int:
				UpperCAmelCase_	:					List[Any]     	=   token.lower()
				return self.encoder.get(lowerCAmelCase_      ,      self.encoder.get(self.unk_token		)		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					Optional[int]      ,      lowerCAmelCase_   :					int		)		->     str:
				return self.decoder.get(lowerCAmelCase_      ,      self.unk_token		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					Tuple      ,      lowerCAmelCase_   :					List[str]		)		->     str:
				UpperCAmelCase_	:					List[str]     	=   " ".join(lowerCAmelCase_		).replace("@@ "      ,      ""		).strip()
				return out_string





	def 	_SCREAMING_SNAKE_CASE ( self   :					Union[str, Any]      ,      lowerCAmelCase_   :					str      ,      lowerCAmelCase_   :					Optional[str] = None		)		->     Tuple[str]:
				if not os.path.isdir(lowerCAmelCase_		):
							logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""		)
							return
				UpperCAmelCase_	:					Dict     	=   os.path.join(
				    lowerCAmelCase_      ,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)
				UpperCAmelCase_	:					Union[str, Any]     	=   os.path.join(
				    lowerCAmelCase_      ,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]		)

				with open(lowerCAmelCase_      ,      "w"      ,      encoding="utf-8"		) as f:
							f.write(json.dumps(self.encoder      ,      indent=2      ,      sort_keys=lowerCAmelCase_      ,      ensure_ascii=lowerCAmelCase_		) + "\n"		)

				UpperCAmelCase_	:					Any     	=   0
				with open(lowerCAmelCase_      ,      "w"      ,      encoding="utf-8"		) as writer:
							writer.write("#version: 0.2\n"		)
							for bpe_tokens, token_index in sorted(self.bpe_ranks.items()      ,      key=lambda lowerCAmelCase_		: kv[1]		):
										if index != token_index:
													logger.warning(
													    f"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
													    " Please check that the tokenizer is not corrupted!"		)
													UpperCAmelCase_	:					List[Any]     	=   token_index
										writer.write(" ".join(lowerCAmelCase_		) + "\n"		)
										index += 1

				return vocab_file, merge_file



