

import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser

def  A_	(				a	):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_					:	List[Any]     							=  {}
      SCREAMING_SNAKE_CASE_					:	Any     							=  tokenizer(example['content']       , truncation=__a	)['input_ids']
      SCREAMING_SNAKE_CASE_					:	List[Any]     							=  len(example['content']	) / len(output['input_ids']	)
      return output


lowerCAmelCase  : Union[str, Any]      =	HfArgumentParser(PretokenizationArguments)
lowerCAmelCase  : str      =	parser.parse_args()
if args.num_workers is None:
    lowerCAmelCase  : Any      =	multiprocessing.cpu_count()
lowerCAmelCase  : int      =	AutoTokenizer.from_pretrained(args.tokenizer_dir)

lowerCAmelCase  : Optional[int]      =	time.time()
lowerCAmelCase  : int      =	load_dataset(args.dataset_name, split='train')
print(F'Dataset loaded in {time.time()-t_start:.2f}s')

lowerCAmelCase  : Optional[Any]      =	time.time()
lowerCAmelCase  : int      =	ds.map(
    tokenize,
    num_proc=args.num_workers,
    remove_columns=[
        'repo_name',
        'path',
        'copies',
        'size',
        'content',
        'license',
        'hash',
        'line_mean',
        'line_max',
        'alpha_frac',
        'autogenerated',
    ],
)
print(F'Dataset tokenized in {time.time()-t_start:.2f}s')

lowerCAmelCase  : Tuple      =	time.time()
ds.push_to_hub(args.tokenized_data_repo)



print(F'Data pushed to the hub in {time.time()-t_start:.2f}s')













from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


A       :   Dict					= {'''processing_layoutxlm''': ['''LayoutXLMProcessor''']}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A       :   Dict					= ['''LayoutXLMTokenizer''']

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A       :   Dict					= ['''LayoutXLMTokenizerFast''']

if TYPE_CHECKING:
					from .processing_layoutxlm import LayoutXLMProcessor

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_layoutxlm import LayoutXLMTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_layoutxlm_fast import LayoutXLMTokenizerFast

else:
					import sys

					A       :   int					= _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



