

import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig



class    A__(a_    ):
						"""simple docstring"""






						_A  :							List[Any]   			=	CustomConfig





						def __init__(  self       ,     _lowercase  )      ->				Any:
									super().__init__(_lowercase  )
									a_		:		Union[str, Any]				    =				torch.nn.Linear(config.hidden_size       ,     config.hidden_size  )





						def 	UpperCamelCase__			(  self       ,     _lowercase  )      ->				Optional[int]:
									return self.linear(_lowercase  )





						def 	UpperCamelCase__			(  self       ,     _lowercase  )      ->				int:
									pass







class    A__(a_    ):
						"""simple docstring"""






						_A  :							Optional[int]   			=	NoSuperInitConfig





						def __init__(  self       ,     _lowercase  )      ->				Union[str, Any]:
									super().__init__(_lowercase  )
									a_		:		Tuple				    =				torch.nn.Linear(config.attribute       ,     config.attribute  )





						def 	UpperCamelCase__			(  self       ,     _lowercase  )      ->				List[Any]:
									return self.linear(_lowercase  )





						def 	UpperCamelCase__			(  self       ,     _lowercase  )      ->				Tuple:
									pass





import sys

from transformers import AutoTokenizer


__snake_case							:     int 						=	sys.argv[1]
__snake_case							:     Dict 						=	sys.argv[2]
__snake_case							:     Dict 						=	int(sys.argv[3])

__snake_case							:     Union[str, Any] 						=	0

__snake_case							:     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:
		__snake_case							:     str 						=	line.rstrip()

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

		__snake_case							:     Dict 						=	line.split()[0]

		__snake_case							:     str 						=	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)
			__snake_case							:     Optional[int] 						=	current_subwords_len
			continue

		subword_len_counter += current_subwords_len

		print(line)


