

from collections import OrderedDict
from typing import Mapping

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


lowercase_									=   logging.get_logger(__name__)

lowercase_									=   {
    'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json',
    'google/bigbird-roberta-large': 'https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json',
    'google/bigbird-base-trivia-itc': 'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json',
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}





class  __lowerCAmelCase     (					SCREAMING_SNAKE_CASE							):
  _a									=  """big_bird"""




  def __init__(				self							,   lowerCAmelCase=50_358							,   lowerCAmelCase=768							,   lowerCAmelCase=12							,   lowerCAmelCase=12							,   lowerCAmelCase=3_072							,   lowerCAmelCase="gelu_new"							,   lowerCAmelCase=0.1							,   lowerCAmelCase=0.1							,   lowerCAmelCase=4_096							,   lowerCAmelCase=2							,   lowerCAmelCase=0.02							,   lowerCAmelCase=1e-12							,   lowerCAmelCase=True							,   lowerCAmelCase=0							,   lowerCAmelCase=1							,   lowerCAmelCase=2							,   lowerCAmelCase=66							,   lowerCAmelCase="block_sparse"							,   lowerCAmelCase=True							,   lowerCAmelCase=False							,   lowerCAmelCase=64							,   lowerCAmelCase=3							,   lowerCAmelCase=None							,   **lowerCAmelCase							,   )  -> Dict:
        '''simple docstring'''






        super().__init__(
            pad_token_id=lowerCAmelCase							,   bos_token_id=lowerCAmelCase							,   eos_token_id=lowerCAmelCase							,   sep_token_id=lowerCAmelCase							,   **lowerCAmelCase							,   )

        _lowercase	       =vocab_size
        _lowercase	       =max_position_embeddings
        _lowercase	       =hidden_size
        _lowercase	       =num_hidden_layers
        _lowercase	       =num_attention_heads
        _lowercase	       =intermediate_size
        _lowercase	       =hidden_act
        _lowercase	       =hidden_dropout_prob
        _lowercase	       =attention_probs_dropout_prob
        _lowercase	       =initializer_range
        _lowercase	       =type_vocab_size
        _lowercase	       =layer_norm_eps
        _lowercase	       =use_cache

        _lowercase	       =rescale_embeddings
        _lowercase	       =attention_type
        _lowercase	       =use_bias
        _lowercase	       =block_size
        _lowercase	       =num_random_blocks
        _lowercase	       =classifier_dropout





class  __lowerCAmelCase     (					SCREAMING_SNAKE_CASE							):




  @property
  def   A__     (				self					)  -> Mapping[str, Mapping[int, str]]:
        '''simple docstring'''






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





import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests
def      a      (			A__	:   Dict     )    ->      str:





      """simple docstring"""



      _lowercase	       ={}

      _lowercase	       =job['started_at']
      _lowercase	       =job['completed_at']

      _lowercase	       =date_parser.parse(A__     )
      _lowercase	       =date_parser.parse(A__     )

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

      _lowercase	       =start
      _lowercase	       =end
      _lowercase	       =duration_in_min

      return job_info
def      a      (			A__	:   Dict      ,   A__	:   str=None     )    ->      Tuple:





      """simple docstring"""



      _lowercase	       =None
      if token is not None:
            _lowercase	       ={'Accept': 'application/vnd.github+json', 'Authorization': F'''Bearer {token}'''}

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

      try:
            job_time.update({job['name']: extract_time_from_single_job(A__     ) for job in result['jobs']}     )
            _lowercase	       =math.ceil((result['total_count'] - 100) / 100     )

            for i in range(A__     ):
                  _lowercase	       =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__":
  lowercase_									=   argparse.ArgumentParser()
  # Required parameters
  parser.add_argument('--workflow_run_id', type=str, required=True, help='A GitHub Actions workflow run id.')
  lowercase_									=   parser.parse_args()

  lowercase_									=   get_job_time(args.workflow_run_id)
  lowercase_									=   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']}")


