






import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests







def       A__				(   _a	:       Union[str, Any]						):





 '''simple docstring'''







 snake_case__	:     int											={}

 snake_case__	:     List[str]											=job["""started_at"""]
 snake_case__	:     List[Any]											=job["""completed_at"""]

 snake_case__	:     Optional[Any]											=date_parser.parse(_UpperCamelCase						)
 snake_case__	:     Union[str, Any]											=date_parser.parse(_UpperCamelCase						)

 snake_case__	:     List[Any]											=round((end_datetime - start_datetime).total_seconds() / 6_0.0						)

 snake_case__	:     Union[str, Any]											=start
 snake_case__	:     List[str]											=end
 snake_case__	:     str											=duration_in_min

 return job_info







def       A__				(   _a	:       Optional[Any]		,	_a	:       Tuple=None						):





 '''simple docstring'''







 snake_case__	:     int											=None
 if token is not None:
  snake_case__	:     Optional[Any]											={"""Accept""": """application/vnd.github+json""", """Authorization""": f"Bearer {token}"}

 snake_case__	:     str											=f"https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"
 snake_case__	:     int											=requests.get(_UpperCamelCase		,	headers=_UpperCamelCase						).json()
 snake_case__	:     Dict											={}

 try:
  job_time.update({job["""name"""]: extract_time_from_single_job(_UpperCamelCase						) for job in result["""jobs"""]}						)
  snake_case__	:     Optional[Any]											=math.ceil((result["""total_count"""] - 100) / 100						)

  for i in range(_UpperCamelCase						):
   snake_case__	:     Any											=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__":
       __lowerCamelCase						:		List[Any]				      = argparse.ArgumentParser()
       # Required parameters
       parser.add_argument("""--workflow_run_id""", type=str, required=True, help="""A GitHub Actions workflow run id.""")
       __lowerCamelCase						:		Optional[Any]				      = parser.parse_args()

       __lowerCamelCase						:		Tuple				      = get_job_time(args.workflow_run_id)
       __lowerCamelCase						:		List[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 Mapping

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


a_								=       logging.get_logger(__name__)

a_								=       {
    """t5-small""": """https://huggingface.co/t5-small/resolve/main/config.json""",
    """t5-base""": """https://huggingface.co/t5-base/resolve/main/config.json""",
    """t5-large""": """https://huggingface.co/t5-large/resolve/main/config.json""",
    """t5-3b""": """https://huggingface.co/t5-3b/resolve/main/config.json""",
    """t5-11b""": """https://huggingface.co/t5-11b/resolve/main/config.json""",
}



class 			__lowerCAmelCase  (						lowerCAmelCase__ ):
 lowerCAmelCase__							       =	"""t5"""
 lowerCAmelCase__							       =	["""past_key_values"""]
 lowerCAmelCase__							       =	{"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}




 def __init__(    self						,					__UpperCAmelCase=32128						,					__UpperCAmelCase=512						,					__UpperCAmelCase=64						,					__UpperCAmelCase=2048						,					__UpperCAmelCase=6						,					__UpperCAmelCase=None						,					__UpperCAmelCase=8						,					__UpperCAmelCase=32						,					__UpperCAmelCase=128						,					__UpperCAmelCase=0.1						,					__UpperCAmelCase=1E-6						,					__UpperCAmelCase=1.0						,					__UpperCAmelCase="relu"						,					__UpperCAmelCase=True						,					__UpperCAmelCase=True						,					__UpperCAmelCase=0						,					__UpperCAmelCase=1						,					**__UpperCAmelCase						,					):



    '''simple docstring'''
    __lowerCamelCase    				=     vocab_size
    __lowerCamelCase    				=     d_model
    __lowerCamelCase    				=     d_kv
    __lowerCamelCase    				=     d_ff
    __lowerCamelCase    				=     num_layers
    __lowerCamelCase    				=     (
        num_decoder_layers if num_decoder_layers is not None else self.num_layers
    )  # default = symmetry
    __lowerCamelCase    				=     num_heads
    __lowerCamelCase    				=     relative_attention_num_buckets
    __lowerCamelCase    				=     relative_attention_max_distance
    __lowerCamelCase    				=     dropout_rate
    __lowerCamelCase    				=     layer_norm_epsilon
    __lowerCamelCase    				=     initializer_factor
    __lowerCamelCase    				=     feed_forward_proj
    __lowerCamelCase    				=     use_cache

    __lowerCamelCase    				=     self.feed_forward_proj.split('''-'''					)
    __lowerCamelCase    				=     act_info[-1]
    __lowerCamelCase    				=     act_info[0] == '''gated'''

    if len(__UpperCAmelCase					) > 1 and act_info[0] != "gated" or len(__UpperCAmelCase					) > 2:
       raise ValueError(
           F"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
           '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
           '''\'gated-gelu\' or \'relu\''''					)

    # for backwards compatibility
    if feed_forward_proj == "gated-gelu":
       __lowerCamelCase    				=     '''gelu_new'''

    super().__init__(
        pad_token_id=__UpperCAmelCase						,					eos_token_id=__UpperCAmelCase						,					is_encoder_decoder=__UpperCAmelCase						,					**__UpperCAmelCase						,					)



class 			__lowerCAmelCase  (						lowerCAmelCase__ ):




 @property
 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     {
        '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
        '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
    }
    if self.use_past:
       __lowerCamelCase    				=     '''past_encoder_sequence + sequence'''
       __lowerCamelCase    				=     {0: '''batch'''}
       __lowerCamelCase    				=     {0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
    else:
       __lowerCamelCase    				=     {0: '''batch''', 1: '''decoder_sequence'''}
       __lowerCamelCase    				=     {0: '''batch''', 1: '''decoder_sequence'''}

    if self.use_past:
       self.fill_with_past_key_values_(__UpperCAmelCase						,					direction='''inputs'''					)

    return common_inputs




 @property
 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    return 13






