






'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A									=logging.get_logger(__name__)

A									={
    'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/config.json',
    'umberto-commoncrawl-cased-v1': (
        'https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'
    ),
    'umberto-wikipedia-uncased-v1': (
        'https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'
    ),
}


class     _a						(			lowerCAmelCase__				):
       __a       :  Dict            =      "camembert"
       def __init__(			self		:			str     ,       lowercase		:			str=30_522     ,       lowercase		:			List[str]=768     ,       lowercase		:			List[Any]=12     ,       lowercase		:			List[Any]=12     ,       lowercase		:			List[str]=3_072     ,       lowercase		:			Optional[Any]="gelu"     ,       lowercase		:			List[Any]=0.1     ,       lowercase		:			int=0.1     ,       lowercase		:			Union[str, Any]=512     ,       lowercase		:			Optional[int]=2     ,       lowercase		:			Optional[int]=0.02     ,       lowercase		:			str=1E-12     ,       lowercase		:			List[Any]=1     ,       lowercase		:			List[Any]=0     ,       lowercase		:			int=2     ,       lowercase		:			List[Any]="absolute"     ,       lowercase		:			Optional[int]=True     ,       lowercase		:			List[Any]=None     ,       **lowercase		:			int     ,       ):



           '''simple docstring'''

           super().__init__(pad_token_id=_lowerCamelCase     ,       bos_token_id=_lowerCamelCase     ,       eos_token_id=_lowerCamelCase     ,       **_lowerCamelCase       )

           UpperCAmelCase     =	vocab_size
           UpperCAmelCase     =	hidden_size
           UpperCAmelCase     =	num_hidden_layers
           UpperCAmelCase     =	num_attention_heads
           UpperCAmelCase     =	hidden_act
           UpperCAmelCase     =	intermediate_size
           UpperCAmelCase     =	hidden_dropout_prob
           UpperCAmelCase     =	attention_probs_dropout_prob
           UpperCAmelCase     =	max_position_embeddings
           UpperCAmelCase     =	type_vocab_size
           UpperCAmelCase     =	initializer_range
           UpperCAmelCase     =	layer_norm_eps
           UpperCAmelCase     =	position_embedding_type
           UpperCAmelCase     =	use_cache
           UpperCAmelCase     =	classifier_dropout






class     _a						(			lowerCAmelCase__				):
       @property
       def 					A   (			self		:			List[str]       ):



           '''simple docstring'''

           if self.task == "multiple-choice":
               UpperCAmelCase     =	{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
           else:
               UpperCAmelCase     =	{0: '''batch''', 1: '''sequence'''}
           return OrderedDict(
               [
                   ('''input_ids''', dynamic_axis),
                   ('''attention_mask''', dynamic_axis),
               ]       )










'''simple docstring'''







import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests





def 		snake_case_							(_a			:							List[str]  ):
    UpperCAmelCase     =	{}

    UpperCAmelCase     =	job['''started_at''']
    UpperCAmelCase     =	job['''completed_at''']

    UpperCAmelCase     =	date_parser.parse(_a  )
    UpperCAmelCase     =	date_parser.parse(_a  )

    UpperCAmelCase     =	round((end_datetime - start_datetime).total_seconds() / 60.0  )

    UpperCAmelCase     =	start
    UpperCAmelCase     =	end
    UpperCAmelCase     =	duration_in_min

    return job_info





def 		snake_case_							(_a			:							str					,     _a			:							List[str]=None  ):
    UpperCAmelCase     =	None
    if token is not None:
        UpperCAmelCase     =	{'''Accept''': '''application/vnd.github+json''', '''Authorization''': F"Bearer {token}"}

    UpperCAmelCase     =	F"https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"
    UpperCAmelCase     =	requests.get(_a					,     headers=_a  ).json()
    UpperCAmelCase     =	{}

    try:
        job_time.update({job['''name''']: extract_time_from_single_job(_a  ) for job in result['''jobs''']}  )
        UpperCAmelCase     =	math.ceil((result['''total_count'''] - 1_0_0) / 1_0_0  )

        for i in range(_a  ):
            UpperCAmelCase     =	requests.get(url + F"&page={i + 2}"					,     headers=_a  ).json()
            job_time.update({job['''name''']: extract_time_from_single_job(_a  ) 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"]}""")




