

import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					{}
							snake_case_           =					tokenizer(example['content']     ,							truncation=UpperCamelCase__   )['input_ids']
							snake_case_           =					len(example['content']   ) / len(output['input_ids']   )
							return output


_UpperCAmelCase	:     str		       = HfArgumentParser(PretokenizationArguments)
_UpperCAmelCase	:     Optional[int]		       = parser.parse_args()
if args.num_workers is None:
					_UpperCAmelCase	:     str		       = multiprocessing.cpu_count()
_UpperCAmelCase	:     Dict		       = AutoTokenizer.from_pretrained(args.tokenizer_dir)

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

_UpperCAmelCase	:     List[Any]		       = time.time()
_UpperCAmelCase	:     Dict		       = 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''')

_UpperCAmelCase	:     List[Any]		       = time.time()
ds.push_to_hub(args.tokenized_data_repo)


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







import warnings

from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor


_UpperCAmelCase	:     Any		       = logging.get_logger(__name__)







class 				lowercase       ( lowercase_    ):




				def __init__(      self   ,     *snake_case   ,     **snake_case ):
											warnings.warn(
											    'The class DeformableDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
											    ' Please use DeformableDetrImageProcessor instead.'   ,     snake_case   ,     )
											super().__init__(*snake_case   ,     **snake_case )




