

import sys

from transformers import AutoTokenizer


_a:      List[Any]								=     sys.argv[1]
_a:      List[str]								=     sys.argv[2]
_a:      List[str]								=     int(sys.argv[3])

_a:      Optional[Any]								=     0

_a:      List[str]								=     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:
								_a:      Dict								=     line.rstrip()

								if not line:
												print(line)
												_a:      Any								=     0
												continue

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

								_a:      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)
												_a:      Optional[Any]								=     current_subwords_len
												continue

								subword_len_counter += current_subwords_len

								print(line)


def  __lowerCAmelCase (  A      ):
	UpperCAmelCase_    			=     len(A      )

	# Set the gap value to be decreased by a factor of 1.3
	# after each iteration
	UpperCAmelCase_    			=     1.3

	# Continue sorting until the gap is 1
	while gap > 1:
		# Decrease the gap value
		UpperCAmelCase_    			=     int(gap / shrink      )

		# Sort the elements using insertion sort
		for i in range(A    ,       len(A      )      ):
			UpperCAmelCase_    			=     collection[i]
			UpperCAmelCase_    			=     i
			while j >= gap and collection[j - gap] > temp:
				UpperCAmelCase_    			=     collection[j - gap]
				j -= gap
			UpperCAmelCase_    			=     temp

	return collection


if __name__ == "__main__":
				import doctest

				doctest.testmod()