




import sys

from transformers import AutoTokenizer


lowercase_     :    Tuple      =			sys.argv[1]
lowercase_     :    Union[str, Any]      =			sys.argv[2]
lowercase_     :    Optional[Any]      =			int(sys.argv[3])

lowercase_     :    Union[str, Any]      =			0

lowercase_     :    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:
								lowercase_     :    List[str]      =			line.rstrip()

								if not line:
												print(line)
												lowercase_     :    Optional[int]      =			0
												continue

								lowercase_     :    List[str]      =			line.split()[0]

								lowercase_     :    int      =			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)
												lowercase_     :    Optional[Any]      =			current_subwords_len
												continue

								subword_len_counter += current_subwords_len

								print(line)










from __future__ import annotations


def 							__SCREAMING_SNAKE_CASE  (      snake_case_     ,   snake_case_						):

						'''simple docstring'''


						_UpperCAmelCase													=					{}
						for index, val in enumerate(snake_case_						):
												_UpperCAmelCase													=					target - val
												if compl in chk_map:
																		return [chk_map[compl], index]
												_UpperCAmelCase													=					index
						return []


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				print(f"""{two_sum([2, 7, 11, 15], 9) = }""")




