




'''simple docstring'''



import os
from collections import deque

import torch
from torch.utils.data import Dataset






class 							_a				(			SCREAMING_SNAKE_CASE ):





       '''simple docstring'''






       def __init__(      self,							A="",							A="train"  ):







             '''simple docstring'''







             assert os.path.isdir(A  )

             SCREAMING_SNAKE_CASE   :      Optional[int]    					=						[]
             SCREAMING_SNAKE_CASE   :      str    					=						os.listdir(A  )
             for story_filename in story_filenames_list:
                   if "summary" in story_filename:
                         continue
                   SCREAMING_SNAKE_CASE   :      Tuple    					=						os.path.join(A,							A  )
                   if not os.path.isfile(A  ):
                         continue
                   self.documents.append(A  )







       def __len__(      self  ):







             '''simple docstring'''







             return len(self.documents  )







       def __getitem__(      self,							A  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Dict    					=						self.documents[idx]
             SCREAMING_SNAKE_CASE   :      List[str]    					=						document_path.split('/'  )[-1]
             with open(A,							encoding='utf-8'  ) as source:
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						source.read()
                   SCREAMING_SNAKE_CASE					,    SCREAMING_SNAKE_CASE   :      int    					=						process_story(A  )
             return document_name, story_lines, summary_lines




def   lowercase__(			__UpperCamelCase:					Optional[Any]    ):

      """simple docstring"""






      SCREAMING_SNAKE_CASE   :      Any    					=						list(filter(lambda __UpperCamelCase    : len(__UpperCamelCase    ) != 0      ,[line.strip() for line in raw_story.split('\n'    )]    )    )

      # for some unknown reason some lines miss a period, add it
      SCREAMING_SNAKE_CASE   :      List[str]    					=						[_add_missing_period(__UpperCamelCase    ) for line in nonempty_lines]

      # gather article lines
      SCREAMING_SNAKE_CASE   :      Tuple    					=						[]
      SCREAMING_SNAKE_CASE   :      int    					=						deque(__UpperCamelCase    )
      while True:
            try:
                  SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						lines.popleft()
                  if element.startswith('@highlight'    ):
                        break
                  story_lines.append(__UpperCamelCase    )
            except IndexError:
                  # if "@highlight" is absent from the file we pop
                  # all elements until there is None, raising an exception.
                  return story_lines, []

    # gather summary lines
      SCREAMING_SNAKE_CASE   :      int    					=						list(filter(lambda __UpperCamelCase    : not t.startswith('@highlight'    )      ,__UpperCamelCase    )    )

      return story_lines, summary_lines




def   lowercase__(			__UpperCamelCase:					Dict    ):

      """simple docstring"""






      SCREAMING_SNAKE_CASE   :      Any    					=						['.', '!', '?', '...', '\'', '`', '"', '\u2019', '\u2019', ')']
      if line.startswith('@highlight'    ):
            return line
      if line[-1] in END_TOKENS:
            return line
      return line + "."




def   lowercase__(			__UpperCamelCase:					List[Any]      ,__UpperCamelCase:					Any      ,__UpperCamelCase:					Optional[Any]    ):

      """simple docstring"""






      if len(__UpperCamelCase    ) > block_size:
            return sequence[:block_size]
      else:
            sequence.extend([pad_token_id] * (block_size - len(__UpperCamelCase    ))    )
            return sequence




def   lowercase__(			__UpperCamelCase:					Optional[int]      ,__UpperCamelCase:					Dict    ):

      """simple docstring"""






      SCREAMING_SNAKE_CASE   :      List[Any]    					=						torch.ones_like(__UpperCamelCase    )
      SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						sequence == pad_token_id
      SCREAMING_SNAKE_CASE   :      List[Any]    					=						0
      return mask




def   lowercase__(			__UpperCamelCase:					str      ,__UpperCamelCase:					Any      ,__UpperCamelCase:					Union[str, Any]    ):

      """simple docstring"""






      SCREAMING_SNAKE_CASE   :      Dict    					=						[tokenizer.encode(__UpperCamelCase    ) for line in story_lines]
      SCREAMING_SNAKE_CASE   :      Optional[int]    					=						[token for sentence in story_lines_token_ids for token in sentence]
      SCREAMING_SNAKE_CASE   :      str    					=						[tokenizer.encode(__UpperCamelCase    ) for line in summary_lines]
      SCREAMING_SNAKE_CASE   :      Dict    					=						[token for sentence in summary_lines_token_ids for token in sentence]

      return story_token_ids, summary_token_ids





def   lowercase__(			__UpperCamelCase:					str      ,__UpperCamelCase:					Union[str, Any]    ):

      """simple docstring"""






      SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						[]
      for sequence in batch:
            SCREAMING_SNAKE_CASE   :      Dict    					=						-1
            SCREAMING_SNAKE_CASE   :      List[Any]    					=						[]
            for s in sequence:
                  if s == separator_token_id:
                        sentence_num += 1
                  embeddings.append(sentence_num % 2    )
            batch_embeddings.append(__UpperCamelCase    )
      return torch.tensor(__UpperCamelCase    )








'''simple docstring'''



import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


UpperCamelCase_    	=				logging.get_logger(__name__)

UpperCamelCase_    	=				{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

UpperCamelCase_    	=				{
    "vocab_file": {
        "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt",
        "distilbert-base-uncased-distilled-squad": (
            "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt"
        ),
        "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt",
        "distilbert-base-cased-distilled-squad": (
            "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt"
        ),
        "distilbert-base-german-cased": "https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt",
        "distilbert-base-multilingual-cased": (
            "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json",
        "distilbert-base-uncased-distilled-squad": (
            "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json"
        ),
        "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json",
        "distilbert-base-cased-distilled-squad": (
            "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json"
        ),
        "distilbert-base-german-cased": (
            "https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json"
        ),
        "distilbert-base-multilingual-cased": (
            "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json"
        ),
    },
}

UpperCamelCase_    	=				{
    "distilbert-base-uncased": 5_1_2,
    "distilbert-base-uncased-distilled-squad": 5_1_2,
    "distilbert-base-cased": 5_1_2,
    "distilbert-base-cased-distilled-squad": 5_1_2,
    "distilbert-base-german-cased": 5_1_2,
    "distilbert-base-multilingual-cased": 5_1_2,
}


UpperCamelCase_    	=				{
    "distilbert-base-uncased": {"do_lower_case": True},
    "distilbert-base-uncased-distilled-squad": {"do_lower_case": True},
    "distilbert-base-cased": {"do_lower_case": False},
    "distilbert-base-cased-distilled-squad": {"do_lower_case": False},
    "distilbert-base-german-cased": {"do_lower_case": False},
    "distilbert-base-multilingual-cased": {"do_lower_case": False},
}






class 							_a				(			SCREAMING_SNAKE_CASE ):





       '''simple docstring'''






       A						:				List[Any]        =						VOCAB_FILES_NAMES
       A						:				Dict        =						PRETRAINED_VOCAB_FILES_MAP
       A						:				Optional[int]        =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       A						:				Optional[Any]        =						PRETRAINED_INIT_CONFIGURATION
       A						:				Optional[int]        =						['''input_ids''', '''attention_mask''']
       A						:				List[Any]        =						DistilBertTokenizer







       def __init__(      self,							A=None,							A=None,							A=True,							A="[UNK]",							A="[SEP]",							A="[PAD]",							A="[CLS]",							A="[MASK]",							A=True,							A=None,							**A,							):







             '''simple docstring'''







             super().__init__(
                 A,							tokenizer_file=A,							do_lower_case=A,							unk_token=A,							sep_token=A,							pad_token=A,							cls_token=A,							mask_token=A,							tokenize_chinese_chars=A,							strip_accents=A,							**A,							)

             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						json.loads(self.backend_tokenizer.normalizer.__getstate__()  )
             if (
                 normalizer_state.get('lowercase',							A  ) != do_lower_case
                 or normalizer_state.get('strip_accents',							A  ) != strip_accents
                 or normalizer_state.get('handle_chinese_chars',							A  ) != tokenize_chinese_chars
             ):
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						getattr(A,							normalizer_state.pop('type'  )  )
                   SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						do_lower_case
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						strip_accents
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						tokenize_chinese_chars
                   SCREAMING_SNAKE_CASE   :      Dict    					=						normalizer_class(**A  )

             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						do_lower_case







       def        UpperCamelCase_							(      self,							A,							A=None  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Any    					=						[self.cls_token_id] + token_ids_a + [self.sep_token_id]

             if token_ids_a:
                   output += token_ids_a + [self.sep_token_id]

             return output







       def        UpperCamelCase_							(      self,							A,							A = None  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      List[str]    					=						[self.sep_token_id]
             SCREAMING_SNAKE_CASE   :      str    					=						[self.cls_token_id]
             if token_ids_a is None:
                   return len(cls + token_ids_a + sep  ) * [0]
             return len(cls + token_ids_a + sep  ) * [0] + len(token_ids_a + sep  ) * [1]







       def        UpperCamelCase_							(      self,							A,							A = None  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      List[str]    					=						self._tokenizer.model.save(A,							name=A  )
             return tuple(A  )


