




from __future__ import annotations


class     __SCREAMING_SNAKE_CASE							:

					def __init__(    self			,	__lowercase = 0 ):







						'''simple docstring'''




						lowerCamelCase_							:		int							       =							value
						lowerCamelCase_							:		Node | None							       =							None
						lowerCamelCase_							:		Node | None							       =							None






def  snake_case       (							A						,       A      )							->							Node | None:




	'''simple docstring'''


	if treea is None:
		return treea
	if treea is None:
		return treea

	lowerCamelCase_							:		Tuple							       =							treea.value + treea.value
	lowerCamelCase_							:		Tuple							       =							merge_two_binary_trees(treea.left						,       treea.left      )
	lowerCamelCase_							:		Union[str, Any]							       =							merge_two_binary_trees(treea.right						,       treea.right      )
	return treea






def  snake_case       (							A      )							->							None:




	'''simple docstring'''


	if root:
		print(root.value      )
		print_preorder(root.left      )
		print_preorder(root.right      )


if __name__ == "__main__":
							UpperCamelCase__		=						Node(1)
							UpperCamelCase__		=						Node(2)
							UpperCamelCase__		=						Node(3)
							UpperCamelCase__		=						Node(4)

							UpperCamelCase__		=						Node(2)
							UpperCamelCase__		=						Node(4)
							UpperCamelCase__		=						Node(6)
							UpperCamelCase__		=						Node(9)
							UpperCamelCase__		=						Node(5)

							print('Tree1 is: ')
							print_preorder(treea)
							print('Tree2 is: ')
							print_preorder(treea)
							UpperCamelCase__		=						merge_two_binary_trees(treea, treea)
							print('Merged Tree is: ')
							print_preorder(merged_tree)






import sys

from transformers import AutoTokenizer


UpperCamelCase__		=						sys.argv[1]
UpperCamelCase__		=						sys.argv[2]
UpperCamelCase__		=						int(sys.argv[3])

UpperCamelCase__		=						0

UpperCamelCase__		=						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:
														UpperCamelCase__		=						line.rstrip()

														if not line:
																					print(line)
																					UpperCamelCase__		=						0
																					continue

														UpperCamelCase__		=						line.split()[0]

														UpperCamelCase__		=						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)
																					UpperCamelCase__		=						current_subwords_len
																					continue

														subword_len_counter += current_subwords_len

														print(line)
