




import numpy as np
import torch
from torch.utils.data import Dataset

from utils import logger




class       __lowerCAmelCase				(							lowerCAmelCase):






       def __init__(      self:    Union[str, Any]				,    _lowerCAmelCase:    str				,    _lowerCAmelCase:    Any ):
         lowercase			:Union[str, Any]							=  params

         lowercase			:Tuple							=  np.array(_lowerCAmelCase )
         lowercase			:Tuple							=  np.array([len(_lowerCAmelCase ) for t in data] )

         self.check()
         self.remove_long_sequences()
         self.remove_empty_sequences()
         self.remove_unknown_sequences()
         self.check()
         self.print_statistics()






       def __getitem__(      self:    Any				,    _lowerCAmelCase:    Union[str, Any] ):
         return (self.token_ids[index], self.lengths[index])






       def __len__(      self:    int ):
         return len(self.lengths )






       def     SCREAMING_SNAKE_CASE			(      self:    Tuple ):
         assert len(self.token_ids ) == len(self.lengths )
         assert all(self.lengths[i] == len(self.token_ids[i] ) for i in range(len(self.lengths ) ) )






       def     SCREAMING_SNAKE_CASE			(      self:    Optional[Any] ):
         lowercase			:str							=  self.params.max_model_input_size
         lowercase			:Optional[Any]							=  self.lengths > max_len
         logger.info(F"Splitting {sum(_lowerCAmelCase )} too long sequences." )

         def divide_chunks(_lowerCAmelCase:    Any				,    _lowerCAmelCase:    List[Any] ):
           return [l[i : i + n] for i in range(0				,    len(_lowerCAmelCase )				,    _lowerCAmelCase )]

         lowercase			:List[Any]							=  []
         lowercase			:List[str]							=  []
         if self.params.mlm:
           lowercase		,			lowercase			:int							=  self.params.special_tok_ids["cls_token"], self.params.special_tok_ids["sep_token"]
         else:
           lowercase		,			lowercase			:Any							=  self.params.special_tok_ids["bos_token"], self.params.special_tok_ids["eos_token"]

         for seq_, len_ in zip(self.token_ids				,    self.lengths ):
           assert (seq_[0] == cls_id) and (seq_[-1] == sep_id), seq_
           if len_ <= max_len:
             new_tok_ids.append(seq_ )
             new_lengths.append(len_ )
           else:
             lowercase			:Optional[Any]							=  []
             for sub_s in divide_chunks(seq_				,    max_len - 2 ):
               if sub_s[0] != cls_id:
                 lowercase			:Optional[Any]							=  np.insert(_lowerCAmelCase				,    0				,    _lowerCAmelCase )
               if sub_s[-1] != sep_id:
                 lowercase			:Optional[Any]							=  np.insert(_lowerCAmelCase				,    len(_lowerCAmelCase )				,    _lowerCAmelCase )
               assert len(_lowerCAmelCase ) <= max_len
               assert (sub_s[0] == cls_id) and (sub_s[-1] == sep_id), sub_s
               sub_seqs.append(_lowerCAmelCase )

             new_tok_ids.extend(_lowerCAmelCase )
             new_lengths.extend([len(_lowerCAmelCase ) for l in sub_seqs] )

         lowercase			:List[Any]							=  np.array(_lowerCAmelCase )
         lowercase			:Union[str, Any]							=  np.array(_lowerCAmelCase )






       def     SCREAMING_SNAKE_CASE			(      self:    List[str] ):
         lowercase			:int							=  len(self )
         lowercase			:List[Any]							=  self.lengths > 11
         lowercase			:Dict							=  self.token_ids[indices]
         lowercase			:Optional[Any]							=  self.lengths[indices]
         lowercase			:Optional[Any]							=  len(self )
         logger.info(F"Remove {init_size - new_size} too short (<=11 tokens) sequences." )






       def     SCREAMING_SNAKE_CASE			(      self:    List[Any] ):
         if "unk_token" not in self.params.special_tok_ids:
           return
         else:
           lowercase			:Union[str, Any]							=  self.params.special_tok_ids["unk_token"]
         lowercase			:str							=  len(self )
         lowercase			:Dict							=  np.array([np.count_nonzero(a == unk_token_id ) for a in self.token_ids] )
         lowercase			:Optional[int]							=  (unk_occs / self.lengths) < 0.5
         lowercase			:Dict							=  self.token_ids[indices]
         lowercase			:int							=  self.lengths[indices]
         lowercase			:Any							=  len(self )
         logger.info(F"Remove {init_size - new_size} sequences with a high level of unknown tokens (50%)." )






       def     SCREAMING_SNAKE_CASE			(      self:    Optional[Any] ):
         if not self.params.is_master:
           return
         logger.info(F"{len(self )} sequences" )
         # data_len = sum(self.lengths)
         # nb_unique_tokens = len(Counter(list(chain(*self.token_ids))))
         # logger.info(f'{data_len} tokens ({nb_unique_tokens} unique)')

         # unk_idx = self.params.special_tok_ids['unk_token']
         # nb_unknown = sum([(t==unk_idx).sum() for t in self.token_ids])
         # logger.info(f'{nb_unknown} unknown tokens (covering {100*nb_unknown/data_len:.2f}% of the data)')






       def     SCREAMING_SNAKE_CASE			(      self:    List[Any]				,    _lowerCAmelCase:    Union[str, Any] ):
         lowercase			:Optional[Any]							=  [t[0] for t in batch]
         lowercase			:Any							=  [t[1] for t in batch]
         assert len(_lowerCAmelCase ) == len(_lowerCAmelCase )

         # Max for paddings
         lowercase			:Union[str, Any]							=  max(_lowerCAmelCase )

         # Pad token ids
         if self.params.mlm:
           lowercase			:int							=  self.params.special_tok_ids["pad_token"]
         else:
           lowercase			:List[Any]							=  self.params.special_tok_ids["unk_token"]
         lowercase			:List[Any]							=  [list(t.astype(_lowerCAmelCase ) ) + [pad_idx] * (max_seq_len_ - len(_lowerCAmelCase )) for t in token_ids]
         assert len(tk_ ) == len(_lowerCAmelCase )
         assert all(len(_lowerCAmelCase ) == max_seq_len_ for t in tk_ )

         lowercase			:Union[str, Any]							=  torch.tensor(tk_ )  # (bs, max_seq_len_)
         lowercase			:List[str]							=  torch.tensor(_lowerCAmelCase )  # (bs)
         return tk_t, lg_t









def 					UpperCAmelCase__     (   lowerCamelCase,	lowerCamelCase      ):
  lowercase			:List[str]							=  ""
  for word_or_phrase in separated:
    if not isinstance(lowerCamelCase,	lowerCamelCase      ):
      raise Exception("join() accepts only strings to be joined"      )
    joined += word_or_phrase + separator
  return joined.strip(lowerCamelCase      )


if __name__ == "__main__":
     from doctest import testmod

     testmod()



