






"""simple docstring"""





import sys

from transformers import AutoTokenizer


_SCREAMING_SNAKE_CASE :    str    =						sys.argv[1]
_SCREAMING_SNAKE_CASE :    int    =						sys.argv[2]
_SCREAMING_SNAKE_CASE :    str    =						int(sys.argv[3])

_SCREAMING_SNAKE_CASE :    List[Any]    =						0

_SCREAMING_SNAKE_CASE :    Union[str, Any]    =						AutoTokenizer.from_pretrained(model_name_or_path)
max_len -= tokenizer.num_special_tokens_to_add()

with open(dataset, '''rt''') as f_p:
  for line in f_p:
    _SCREAMING_SNAKE_CASE :    List[str]    =						line.rstrip()

    if not line:
      print(line)
      _SCREAMING_SNAKE_CASE :    List[Any]    =						0
      continue

    _SCREAMING_SNAKE_CASE :    List[Any]    =						line.split()[0]

    _SCREAMING_SNAKE_CASE :    Union[str, Any]    =						len(tokenizer.tokenize(token))

    # Token contains strange control characters like \x96 or \x95
    # Just filter out the complete line
    if current_subwords_len == 0:
      continue

    if (subword_len_counter + current_subwords_len) > max_len:
      print('''''')
      print(line)
      _SCREAMING_SNAKE_CASE :    Any    =						current_subwords_len
      continue

    subword_len_counter += current_subwords_len

    print(line)












"""simple docstring"""





from __future__ import annotations







def 					lowerCamelCase__	(							_lowerCamelCase	:		list[int]		,    _lowerCamelCase	:		int			)				->    int:
  lowerCamelCase_					,     lowerCamelCase_   					=						0, len(_lowerCamelCase			) - 1
  while start_ind <= end_ind:
    if array[start_ind] == search_item:
      return start_ind
    elif array[end_ind] == search_item:
      return end_ind
    else:
      start_ind += 1
      end_ind -= 1
    # returns -1 if search_item is not found in array
  return -1


if __name__ == "__main__":
  print(double_linear_search(list(range(100)), 40))




