



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)





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


UpperCAmelCase__  =			{
    "configuration_align": [
        "ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "AlignConfig",
        "AlignTextConfig",
        "AlignVisionConfig",
    ],
    "processing_align": ["AlignProcessor"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__  =			[
							    "ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "AlignModel",
							    "AlignPreTrainedModel",
							    "AlignTextModel",
							    "AlignVisionModel",
							]

if TYPE_CHECKING:
							from .configuration_align import (
							    ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    AlignConfig,
							    AlignTextConfig,
							    AlignVisionConfig,
							)
							from .processing_align import AlignProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_align import (
														    ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
														    AlignModel,
														    AlignPreTrainedModel,
														    AlignTextModel,
														    AlignVisionModel,
														)

else:
							import sys

							UpperCAmelCase__  =			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
