

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case							:     Optional[int] 						=	{"""configuration_sew_d""": ["""SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWDConfig"""]}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case							:     Tuple 						=	[
	    """SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """SEWDForCTC""",
	    """SEWDForSequenceClassification""",
	    """SEWDModel""",
	    """SEWDPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_sew_d import (
		    SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
		    SEWDForCTC,
		    SEWDForSequenceClassification,
		    SEWDModel,
		    SEWDPreTrainedModel,
		)


else:
	import sys

	__snake_case							:     Dict 						=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





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)


