

import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests







def       A_				(   _UpperCAmelCase   ):
						SCREAMING_SNAKE_CASE_:			Dict  		=	{}

						SCREAMING_SNAKE_CASE_:			List[str]  		=	job["started_at"]
						SCREAMING_SNAKE_CASE_:			Optional[int]  		=	job["completed_at"]

						SCREAMING_SNAKE_CASE_:			str  		=	date_parser.parse(_UpperCAmelCase   )
						SCREAMING_SNAKE_CASE_:			Optional[int]  		=	date_parser.parse(_UpperCAmelCase   )

						SCREAMING_SNAKE_CASE_:			Dict  		=	round((end_datetime - start_datetime).total_seconds() / 60.0   )

						SCREAMING_SNAKE_CASE_:			Optional[int]  		=	start
						SCREAMING_SNAKE_CASE_:			int  		=	end
						SCREAMING_SNAKE_CASE_:			str  		=	duration_in_min

						return job_info







def       A_				(   _UpperCAmelCase    ,     _UpperCAmelCase=None   ):
						SCREAMING_SNAKE_CASE_:			List[str]  		=	None
						if token is not None:
												SCREAMING_SNAKE_CASE_:			str  		=	{"Accept": "application/vnd.github+json", "Authorization": f"Bearer {token}"}

						SCREAMING_SNAKE_CASE_:			str  		=	f"https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"
						SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	requests.get(_UpperCAmelCase    ,     headers=_UpperCAmelCase   ).json()
						SCREAMING_SNAKE_CASE_:			List[str]  		=	{}

						try:
												job_time.update({job["name"]: extract_time_from_single_job(_UpperCAmelCase   ) for job in result["jobs"]}   )
												SCREAMING_SNAKE_CASE_:			List[Any]  		=	math.ceil((result["total_count"] - 1_00) / 1_00   )

												for i in range(_UpperCAmelCase   ):
																		SCREAMING_SNAKE_CASE_:			Tuple  		=	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							:  Optional[int]            =						argparse.ArgumentParser()
						# Required parameters
						parser.add_argument("""--workflow_run_id""", type=str, required=True, help="""A GitHub Actions workflow run id.""")
						lowerCAmelCase							:  Union[str, Any]            =						parser.parse_args()

						lowerCAmelCase							:  Any            =						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 ...configuration_utils import PretrainedConfig
from ...utils import logging


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

lowerCAmelCase							:  int            =						{
    """google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
    """google/fnet-large""": """https://huggingface.co/google/fnet-large/resolve/main/config.json"""
    # See all FNet models at https://huggingface.co/models?filter=fnet
}



class   __lowercase    (			UpperCAmelCase_     ):




			"""simple docstring"""







			_UpperCAmelCase       :							int      							=					'''fnet'''



			def __init__(			self  :					Optional[Any]       ,						lowerCAmelCase__  :					List[str]=3_2000       ,						lowerCAmelCase__  :					Union[str, Any]=768       ,						lowerCAmelCase__  :					Optional[Any]=12       ,						lowerCAmelCase__  :					Tuple=3072       ,						lowerCAmelCase__  :					Any="gelu_new"       ,						lowerCAmelCase__  :					Union[str, Any]=0.1       ,						lowerCAmelCase__  :					Optional[Any]=512       ,						lowerCAmelCase__  :					int=4       ,						lowerCAmelCase__  :					List[Any]=0.02       ,						lowerCAmelCase__  :					Union[str, Any]=1E-12       ,						lowerCAmelCase__  :					Optional[int]=False       ,						lowerCAmelCase__  :					Any=512       ,						lowerCAmelCase__  :					Optional[int]=3       ,						lowerCAmelCase__  :					int=1       ,						lowerCAmelCase__  :					List[Any]=2       ,						**lowerCAmelCase__  :					Optional[int]       ,						):
									super().__init__(pad_token_id=lowerCAmelCase__       ,						bos_token_id=lowerCAmelCase__       ,						eos_token_id=lowerCAmelCase__       ,						**lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_:			str  		=	vocab_size
									SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	max_position_embeddings
									SCREAMING_SNAKE_CASE_:			Tuple  		=	hidden_size
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	num_hidden_layers
									SCREAMING_SNAKE_CASE_:			Optional[int]  		=	intermediate_size
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	hidden_act
									SCREAMING_SNAKE_CASE_:			Any  		=	hidden_dropout_prob
									SCREAMING_SNAKE_CASE_:			int  		=	initializer_range
									SCREAMING_SNAKE_CASE_:			Optional[int]  		=	type_vocab_size
									SCREAMING_SNAKE_CASE_:			int  		=	layer_norm_eps
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	use_tpu_fourier_optimizations
									SCREAMING_SNAKE_CASE_:			int  		=	tpu_short_seq_length






