

from dataclasses import asdict, dataclass
from typing import Optional

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


__UpperCAmelCase						=					logging.get_logger(__name__)

# TODO Update this
__UpperCAmelCase						=					{
    "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__					):
  """simple docstring"""






  lowerCamelCase       :     Optional[Any]		 ="esm"







  def __init__(     self					:       List[Any]			,				lowerCAmelCase					:       int=None			,				lowerCAmelCase					:       List[Any]=None			,				lowerCAmelCase					:       Tuple=None			,				lowerCAmelCase					:       List[str]=7_68			,				lowerCAmelCase					:       str=12			,				lowerCAmelCase					:       int=12			,				lowerCAmelCase					:       str=30_72			,				lowerCAmelCase					:       int=0.1			,				lowerCAmelCase					:       Optional[Any]=0.1			,				lowerCAmelCase					:       Optional[Any]=10_26			,				lowerCAmelCase					:       Dict=0.02			,				lowerCAmelCase					:       List[str]=1e-12			,				lowerCAmelCase					:       Any="absolute"			,				lowerCAmelCase					:       Tuple=True			,				lowerCAmelCase					:       Any=None			,				lowerCAmelCase					:       Dict=False			,				lowerCAmelCase					:       List[str]=False			,				lowerCAmelCase					:       Tuple=None			,				lowerCAmelCase					:       List[str]=None			,				**lowerCAmelCase					:       Any			,				)				->      str:






     """simple docstring"""







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

     __lowerCAmelCase    :     Dict          =		vocab_size
     __lowerCAmelCase    :     Optional[Any]          =		hidden_size
     __lowerCAmelCase    :     Any          =		num_hidden_layers
     __lowerCAmelCase    :     int          =		num_attention_heads
     __lowerCAmelCase    :     Any          =		intermediate_size
     __lowerCAmelCase    :     List[Any]          =		hidden_dropout_prob
     __lowerCAmelCase    :     str          =		attention_probs_dropout_prob
     __lowerCAmelCase    :     Union[str, Any]          =		max_position_embeddings
     __lowerCAmelCase    :     List[str]          =		initializer_range
     __lowerCAmelCase    :     Optional[Any]          =		layer_norm_eps
     __lowerCAmelCase    :     Optional[int]          =		position_embedding_type
     __lowerCAmelCase    :     int          =		use_cache
     __lowerCAmelCase    :     Any          =		emb_layer_norm_before
     __lowerCAmelCase    :     List[str]          =		token_dropout
     __lowerCAmelCase    :     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."""       )
           __lowerCAmelCase    :     Tuple          =		EsmFoldConfig()
        elif isinstance(__snake_case			,				__snake_case       ):
           __lowerCAmelCase    :     Any          =		EsmFoldConfig(**__snake_case       )
        __lowerCAmelCase    :     Dict          =		esmfold_config
        if vocab_list is None:
           logger.warning("""No vocab_list supplied for folding model, assuming the ESM-2 vocabulary!"""       )
           __lowerCAmelCase    :     List[Any]          =		get_default_vocab_list()
        else:
           __lowerCAmelCase    :     Any          =		vocab_list
     else:
        __lowerCAmelCase    :     Optional[Any]          =		None
        __lowerCAmelCase    :     Optional[Any]          =		None
     if self.esmfold_config is not None and getattr(self.esmfold_config			,				"""use_esm_attn_map"""			,				__snake_case       ):
        raise ValueError("""The HuggingFace port of ESMFold does not support use_esm_attn_map at this time!"""       )







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






     """simple docstring"""







     __lowerCAmelCase    :     Optional[Any]          =		super().to_dict()
     if isinstance(self.esmfold_config			,				__snake_case       ):
        __lowerCAmelCase    :     str          =		self.esmfold_config.to_dict()
     return output






@dataclass
class SCREAMING_SNAKE_CASE      :
  """simple docstring"""






  lowerCamelCase       :     int		 =None
  lowerCamelCase       :     List[str]		 =True
  lowerCamelCase       :     Union[str, Any]		 =False
  lowerCamelCase       :     Optional[int]		 =False
  lowerCamelCase       :     str		 =False
  lowerCamelCase       :     Union[str, Any]		 =0

  lowerCamelCase       :     List[str]		 =True
  lowerCamelCase       :     str		 =False

  lowerCamelCase       :     List[Any]		 =128
  lowerCamelCase       :     str		 =None







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






     """simple docstring"""







     if self.trunk is None:
        __lowerCAmelCase    :     Dict          =		TrunkConfig()
     elif isinstance(self.trunk			,				__snake_case       ):
        __lowerCAmelCase    :     Optional[int]          =		TrunkConfig(**self.trunk       )







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






     """simple docstring"""







     __lowerCAmelCase    :     List[Any]          =		asdict(self       )
     __lowerCAmelCase    :     str          =		self.trunk.to_dict()
     return output






@dataclass
class SCREAMING_SNAKE_CASE      :
  """simple docstring"""






  lowerCamelCase       :     Union[str, Any]		 =48
  lowerCamelCase       :     Any		 =1024
  lowerCamelCase       :     Tuple		 =128
  lowerCamelCase       :     Dict		 =32
  lowerCamelCase       :     Any		 =32
  lowerCamelCase       :     List[str]		 =32
  lowerCamelCase       :     Optional[int]		 =0
  lowerCamelCase       :     Tuple		 =0
  lowerCamelCase       :     Union[str, Any]		 =False
  lowerCamelCase       :     Union[str, Any]		 =4
  lowerCamelCase       :     str		 =128
  lowerCamelCase       :     str		 =None







  def 			SCREAMING_SNAKE_CASE       (     self					:       Optional[Any]       )				->      int:






     """simple docstring"""







     if self.structure_module is None:
        __lowerCAmelCase    :     Dict          =		StructureModuleConfig()
     elif isinstance(self.structure_module			,				__snake_case       ):
        __lowerCAmelCase    :     int          =		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}.'''       )

     __lowerCAmelCase    :     Union[str, Any]          =		self.sequence_state_dim // self.sequence_head_width
     __lowerCAmelCase    :     str          =		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					:       Optional[int]       )				->      List[str]:






     """simple docstring"""







     __lowerCAmelCase    :     Dict          =		asdict(self       )
     __lowerCAmelCase    :     Union[str, Any]          =		self.structure_module.to_dict()
     return output






@dataclass
class SCREAMING_SNAKE_CASE      :
  """simple docstring"""






  lowerCamelCase       :     Union[str, Any]		 =384
  lowerCamelCase       :     Union[str, Any]		 =128
  lowerCamelCase       :     List[Any]		 =16
  lowerCamelCase       :     Optional[int]		 =128
  lowerCamelCase       :     List[Any]		 =12
  lowerCamelCase       :     int		 =4
  lowerCamelCase       :     List[Any]		 =8
  lowerCamelCase       :     Optional[int]		 =0.1
  lowerCamelCase       :     Any		 =8
  lowerCamelCase       :     str		 =1
  lowerCamelCase       :     List[Any]		 =2
  lowerCamelCase       :     str		 =7
  lowerCamelCase       :     Dict		 =10
  lowerCamelCase       :     Tuple		 =1e-8
  lowerCamelCase       :     Union[str, Any]		 =1e5







  def 			SCREAMING_SNAKE_CASE       (     self					:       Optional[int]       )				->      str:






     """simple docstring"""







     return asdict(self       )






def       snake_case_ ()     ->      Optional[int]:
   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 pathlib import Path

import fire
from tqdm import tqdm




def 		lowerCAmelCase_ (						lowerCamelCase="ro"						,  lowerCamelCase="en"						,  lowerCamelCase="wmt16"						,  lowerCamelCase=None ):
				try:
								import datasets
				except (ModuleNotFoundError, ImportError):
								raise ImportError("""run pip install datasets""" )
				__magic_name__						:						Dict										=F"{src_lang}-{tgt_lang}"
				print(F"Converting {dataset}-{pair}" )
				__magic_name__						:						Dict										=datasets.load_dataset(lowerCamelCase						,  lowerCamelCase )
				if save_dir is None:
								__magic_name__						:						Optional[int]										=F"{dataset}-{pair}"
				__magic_name__						:						int										=Path(lowerCamelCase )
				save_dir.mkdir(exist_ok=lowerCamelCase )

				for split in ds.keys():
								print(F"Splitting {split} with {ds[split].num_rows} records" )

								# to save to val.source, val.target like summary datasets
								__magic_name__						:						Dict										="""val""" if split == """validation""" else split
								__magic_name__						:						List[Any]										=save_dir.joinpath(F"{fn}.source" )
								__magic_name__						:						Optional[int]										=save_dir.joinpath(F"{fn}.target" )
								__magic_name__						:						Optional[Any]										=src_path.open("""w+""" )
								__magic_name__						:						List[Any]										=tgt_path.open("""w+""" )

								# reader is the bottleneck so writing one record at a time doesn't slow things down
								for x in tqdm(ds[split] ):
												__magic_name__						:						str										=x["""translation"""]
												src_fp.write(ex[src_lang] + """\n""" )
												tgt_fp.write(ex[tgt_lang] + """\n""" )

				print(F"Saved {dataset} dataset to {save_dir}" )


if __name__ == "__main__":
							fire.Fire(download_wmt_dataset)




