



'''simple docstring'''






import sys

from transformers import AutoTokenizer


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

lowerCamelCase__	  =		0

lowerCamelCase__	  =		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:
												lowerCamelCase__	  =		line.rstrip()

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

												lowerCamelCase__	  =		line.split()[0]

												lowerCamelCase__	  =		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)
																		lowerCamelCase__	  =		current_subwords_len
																		continue

												subword_len_counter += current_subwords_len

												print(line)








'''simple docstring'''






import abc
import copy
import dataclasses
from dataclasses import dataclass
from typing import ClassVar, Dict, Type, TypeVar

from ..features import Features


lowerCamelCase__	  =		TypeVar('T', bound='TaskTemplate')

@dataclass(frozen=__A       )
class 	_lowerCAmelCase     (    abc.ABC       ):






		'''simple docstring'''
		# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
		snake_case_							= 42
		snake_case_							= 42
		snake_case_							= 42
		def 						__lowercase      (						self							:       T      ,		UpperCamelCase_							:       Features		)      ->			T:







									'''simple docstring'''





									return copy.deepcopy(self		)
		@property
		def 						__lowercase      (						self							:       int		)      ->			Features:







									'''simple docstring'''





									return Features(**self.input_schema      ,		**self.label_schema		)
		@property
		@abc.abstractmethod
		def 						__lowercase      (						self							:       List[str]		)      ->			Dict[str, str]:







									'''simple docstring'''





									raise NotImplementedError





		@classmethod
		def 						__lowercase      (						cls							:       Type[T]      ,		UpperCamelCase_							:       dict		)      ->			T:







									'''simple docstring'''





									_lowercase							:		List[str]				=   {f.name for f in dataclasses.fields(cls		)}
									return cls(**{k: v for k, v in template_dict.items() if k in field_names}		)



