




import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests




def 						SCREAMING_SNAKE_CASE__ (   lowercase					)  ->       Tuple:
   snake_case				:    Dict           =	{}

   snake_case				:    Union[str, Any]           =	job["""started_at"""]
   snake_case				:    Optional[int]           =	job["""completed_at"""]

   snake_case				:    Tuple           =	date_parser.parse(lowercase					)
   snake_case				:    Tuple           =	date_parser.parse(lowercase					)

   snake_case				:    int           =	round((end_datetime - start_datetime).total_seconds() / 60.0					)

   snake_case				:    str           =	start
   snake_case				:    str           =	end
   snake_case				:    List[str]           =	duration_in_min

   return job_info




def 						SCREAMING_SNAKE_CASE__ (   lowercase						,lowercase=None					)  ->       Dict:
   snake_case				:    Any           =	None
   if token is not None:
      snake_case				:    Optional[Any]           =	{"""Accept""": """application/vnd.github+json""", """Authorization""": f"""Bearer {token}"""}

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

   try:
      job_time.update({job["""name"""]: extract_time_from_single_job(lowercase					) for job in result["""jobs"""]}					)
      snake_case				:    Dict           =	math.ceil((result["""total_count"""] - 100) / 100					)

      for i in range(lowercase					):
         snake_case				:    Optional[Any]           =	requests.get(url + f"""&page={i + 2}"""						,headers=lowercase					).json()
         job_time.update({job["""name"""]: extract_time_from_single_job(lowercase					) 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__":
       lowerCamelCase	:	Optional[int]				=   argparse.ArgumentParser()
       # Required parameters
       parser.add_argument('--workflow_run_id', type=str, required=True, help='A GitHub Actions workflow run id.')
       lowerCamelCase	:	Optional[int]				=   parser.parse_args()

       lowerCamelCase	:	int				=   get_job_time(args.workflow_run_id)
       lowerCamelCase	:	Any				=   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"]}""")











from typing import List

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase	:	Optional[int]				=   logging.get_logger(__name__)

lowerCamelCase	:	Tuple				=   {
    'snap-research/efficientformer-l1-300': (
        'https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json'
    ),
}




class 						__lowercase		(UpperCamelCase__							):




      """simple docstring"""





      _snake_case												=						"""efficientformer"""

      def __init__(				self    ,				A = [3, 2, 6, 4]    ,				A = [4_8, 9_6, 2_2_4, 4_4_8]    ,				A = [True, True, True, True]    ,				A = 4_4_8    ,				A = 3_2    ,				A = 4    ,				A = 7    ,				A = 5    ,				A = 8    ,				A = 4    ,				A = 0.0    ,				A = 1_6    ,				A = 3    ,				A = 3    ,				A = 3    ,				A = 2    ,				A = 1    ,				A = 0.0    ,				A = 1    ,				A = True    ,				A = True    ,				A = 1e-5    ,				A = "gelu"    ,				A = 0.02    ,				A = 1e-1_2    ,				A = 2_2_4    ,				A = 1e-0_5    ,				**A    ,				)		->    None:
         super().__init__(**A     )

         snake_case				:    Dict           =	hidden_act
         snake_case				:    int           =	hidden_dropout_prob
         snake_case				:    Any           =	hidden_sizes
         snake_case				:    Optional[Any]           =	num_hidden_layers
         snake_case				:    List[Any]           =	num_attention_heads
         snake_case				:    List[Any]           =	initializer_range
         snake_case				:    str           =	layer_norm_eps
         snake_case				:    Dict           =	patch_size
         snake_case				:    Optional[int]           =	num_channels
         snake_case				:    int           =	depths
         snake_case				:    Optional[int]           =	mlp_expansion_ratio
         snake_case				:    Any           =	downsamples
         snake_case				:    Dict           =	dim
         snake_case				:    Optional[int]           =	key_dim
         snake_case				:    Union[str, Any]           =	attention_ratio
         snake_case				:    Any           =	resolution
         snake_case				:    Dict           =	pool_size
         snake_case				:    Any           =	downsample_patch_size
         snake_case				:    Tuple           =	downsample_stride
         snake_case				:    Any           =	downsample_pad
         snake_case				:    Union[str, Any]           =	drop_path_rate
         snake_case				:    List[str]           =	num_metaad_blocks
         snake_case				:    Union[str, Any]           =	distillation
         snake_case				:    List[str]           =	use_layer_scale
         snake_case				:    int           =	layer_scale_init_value
         snake_case				:    Union[str, Any]           =	image_size
         snake_case				:    Dict           =	batch_norm_eps





