






"""simple docstring"""



import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests




def      _lowerCAmelCase		(							UpperCAmelCase__       :					Optional[int]      )		->Tuple:
      A__						:  Optional[int]		  =  {}

      A__						:  int		  =  job["""started_at"""]
      A__						:  Any		  =  job["""completed_at"""]

      A__						:  Optional[int]		  =  date_parser.parse(UpperCAmelCase__      )
      A__						:  Optional[Any]		  =  date_parser.parse(UpperCAmelCase__      )

      A__						:  Any		  =  round((end_datetime - start_datetime).total_seconds() / 60.0      )

      A__						:  List[str]		  =  start
      A__						:  Optional[int]		  =  end
      A__						:  Optional[int]		  =  duration_in_min

      return job_info




def      _lowerCAmelCase		(							UpperCAmelCase__       :					Dict,						UpperCAmelCase__       :					Optional[int]=None      )		->Optional[int]:
      A__						:  List[Any]		  =  None
      if token is not None:
            A__						:  Optional[Any]		  =  {"""Accept""": """application/vnd.github+json""", """Authorization""": f'Bearer {token}'}

      A__						:  Any		  =  f'https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100'
      A__						:  Any		  =  requests.get(UpperCAmelCase__,						headers=UpperCAmelCase__      ).json()
      A__						:  int		  =  {}

      try:
            job_time.update({job["""name"""]: extract_time_from_single_job(UpperCAmelCase__      ) for job in result["""jobs"""]}      )
            A__						:  str		  =  math.ceil((result["""total_count"""] - 1_0_0) / 1_0_0      )

            for i in range(UpperCAmelCase__      ):
                  A__						:  Dict		  =  requests.get(url + f'&page={i + 2}',						headers=UpperCAmelCase__      ).json()
                  job_time.update({job["""name"""]: extract_time_from_single_job(UpperCAmelCase__      ) for job in result["""jobs"""]}      )

            return job_time
      except Exception:
            print(f'Unknown error, could not fetch links:\n{traceback.format_exc()}'      )

      return {}


if __name__ == "__main__":
      A_    =							argparse.ArgumentParser()
      # Required parameters
      parser.add_argument('''--workflow_run_id''', type=str, required=True, help='''A GitHub Actions workflow run id.''')
      A_    =							parser.parse_args()

      A_    =							get_job_time(args.workflow_run_id)
      A_    =							dict(sorted(job_time.items(), key=lambda item: item[1]["duration"], reverse=True))

      for k, v in job_time.items():
            print(F'{k}: {v["duration"]}')














"""simple docstring"""



import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser




def      _lowerCAmelCase		(							UpperCAmelCase__       :					List[str]      )		->str:
						A__						:  Tuple		  =  {}
						A__						:  Union[str, Any]		  =  tokenizer(example["""content"""],						truncation=UpperCAmelCase__      )["""input_ids"""]
						A__						:  Any		  =  len(example["""content"""]      ) / len(output["""input_ids"""]      )
						return output


A_    =							HfArgumentParser(PretokenizationArguments)
A_    =							parser.parse_args()
if args.num_workers is None:
						A_    =							multiprocessing.cpu_count()
A_    =							AutoTokenizer.from_pretrained(args.tokenizer_dir)

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

A_    =							time.time()
A_    =							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')

A_    =							time.time()
ds.push_to_hub(args.tokenized_data_repo)

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






