"""simple docstring"""







import sys

from transformers import AutoTokenizer


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

SCREAMING_SNAKE_CASE						=    0

SCREAMING_SNAKE_CASE						=    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:
												SCREAMING_SNAKE_CASE						=    line.rstrip()

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

												SCREAMING_SNAKE_CASE						=    line.split()[0]

												SCREAMING_SNAKE_CASE						=    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)
																		SCREAMING_SNAKE_CASE						=    current_subwords_len
																		continue

												subword_len_counter += current_subwords_len

												print(line)




"""simple docstring"""







from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE						=    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE						=    {
    'facebook/regnet-y-040': 'https://huggingface.co/facebook/regnet-y-040/blob/main/config.json',
}



class 			_lowerCamelCase      (__lowerCamelCase  ):
				_snake_case  =	"regnet"
				_snake_case  =	["x", "y"]







				def __init__(			self     :							Any      ,       lowerCamelCase_     :							Optional[Any]=3      ,       lowerCamelCase_     :							List[str]=3_2      ,       lowerCamelCase_     :							str=[1_2_8, 1_9_2, 5_1_2, 1_0_8_8]      ,       lowerCamelCase_     :							int=[2, 6, 1_2, 2]      ,       lowerCamelCase_     :							Union[str, Any]=6_4      ,       lowerCamelCase_     :							int="y"      ,       lowerCamelCase_     :							Optional[Any]="relu"      ,       **lowerCamelCase_     :							Optional[Any]      ,       ):

					"""simple docstring"""






					super().__init__(**lowerCamelCase_    )
					if layer_type not in self.layer_types:
						raise ValueError(F'''layer_type={layer_type} is not one of {','.join(self.layer_types    )}'''    )
					_lowercase			:     str      					=				num_channels
					_lowercase			:     Optional[Any]      					=				embedding_size
					_lowercase			:     Union[str, Any]      					=				hidden_sizes
					_lowercase			:     Optional[int]      					=				depths
					_lowercase			:     Optional[int]      					=				groups_width
					_lowercase			:     Tuple      					=				layer_type
					_lowercase			:     Union[str, Any]      					=				hidden_act
					# always downsample in the first stage
					_lowercase			:     Optional[int]      					=				True



