






'''simple docstring'''







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     _a						(			UpperCamelCase_				):
       __a       :  List[Any]            =      """t5"""
       __a       :  List[str]            =      ["""past_key_values"""]
       __a       :  Any            =      {"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}
       def __init__(			self		:			Dict     ,       lowercase		:			Optional[Any]=32_128     ,       lowercase		:			Union[str, Any]=512     ,       lowercase		:			Optional[int]=64     ,       lowercase		:			List[str]=2_048     ,       lowercase		:			int=6     ,       lowercase		:			Optional[int]=None     ,       lowercase		:			Any=8     ,       lowercase		:			List[Any]=32     ,       lowercase		:			Dict=128     ,       lowercase		:			Tuple=0.1     ,       lowercase		:			Dict=1E-6     ,       lowercase		:			Optional[Any]=1.0     ,       lowercase		:			Tuple="relu"     ,       lowercase		:			Optional[int]=True     ,       lowercase		:			List[Any]=True     ,       lowercase		:			Union[str, Any]=0     ,       lowercase		:			Optional[int]=1     ,       **lowercase		:			Optional[Any]     ,       ):



           '''simple docstring'''

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

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

           if len(_a       ) > 1 and act_info[0] != "gated" or len(_a       ) > 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":
               UpperCAmelCase     =	"""gelu_new"""

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






class     _a						(			UpperCamelCase_				):
       @property
       def 					A   (			self		:			int       ):



           '''simple docstring'''

           UpperCAmelCase     =	{
               """input_ids""": {0: """batch""", 1: """encoder_sequence"""},
               """attention_mask""": {0: """batch""", 1: """encoder_sequence"""},
           }
           if self.use_past:
               UpperCAmelCase     =	"""past_encoder_sequence + sequence"""
               UpperCAmelCase     =	{0: """batch"""}
               UpperCAmelCase     =	{0: """batch""", 1: """past_decoder_sequence + sequence"""}
           else:
               UpperCAmelCase     =	{0: """batch""", 1: """decoder_sequence"""}
               UpperCAmelCase     =	{0: """batch""", 1: """decoder_sequence"""}

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

           return common_inputs







       @property
       def 					A   (			self		:			List[Any]       ):



           '''simple docstring'''

           return 13










'''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"]}""")




