"""simple docstring"""





import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests





def 							a_	( _lowerCAmelCase    :					List[Any]	):





       '''simple docstring'''

       lowercase__     :						List[Any]         =      {}

       lowercase__     :						Optional[Any]         =      job['started_at']
       lowercase__     :						str         =      job['completed_at']

       lowercase__     :						Any         =      date_parser.parse(__A	)
       lowercase__     :						str         =      date_parser.parse(__A	)

       lowercase__     :						int         =      round((end_datetime - start_datetime).total_seconds() / 6_0.0	)

       lowercase__     :						List[str]         =      start
       lowercase__     :						Optional[int]         =      end
       lowercase__     :						Union[str, Any]         =      duration_in_min

       return job_info





def 							a_	( _lowerCAmelCase    :					Optional[Any]  ,					_lowerCAmelCase    :					Union[str, Any]=None	):





       '''simple docstring'''

       lowercase__     :						str         =      None
       if token is not None:
              lowercase__     :						str         =      {'Accept': 'application/vnd.github+json', 'Authorization': f"""Bearer {token}"""}

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

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

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

       _UpperCamelCase  :		int           =       get_job_time(args.workflow_run_id)
       _UpperCamelCase  :		str           =       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"]}''')




import os
import re
import shutil
import sys
import tempfile
import unittest

import black


_lowerCamelCase      :					Union[str, Any]					    =      os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))

import check_copies  # noqa: E402


# This is the reference code that will be used in the tests.
# If DDPMSchedulerOutput is changed in scheduling_ddpm.py, this code needs to be manually updated.
_lowerCamelCase      :					str					    =      '''    \"""
    Output class for the scheduler\'s step function output.

    Args:
        prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):
            Computed sample (x_{t-1}) of previous timestep. `prev_sample` should be used as next model input in the
            denoising loop.
        pred_original_sample (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)` for images):
            The predicted denoised sample (x_{0}) based on the model output from the current timestep.
            `pred_original_sample` can be used to preview progress or for guidance.
    \"""

    prev_sample: torch.FloatTensor
    pred_original_sample: Optional[torch.FloatTensor] = None
'''





class        lowerCAmelCase__  (					unittest.TestCase			):



       '''simple docstring'''







       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =tempfile.mkdtemp()
             os.makedirs(os.path.join(self.diffusers_dir ,   '''schedulers/'''     )     )
             __A    =self.diffusers_dir
             shutil.copy(
                 os.path.join(lowercase__ ,   '''src/diffusers/schedulers/scheduling_ddpm.py'''     ) ,   os.path.join(self.diffusers_dir ,   '''schedulers/scheduling_ddpm.py'''     ) ,   )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    ='''src/diffusers'''
             shutil.rmtree(self.diffusers_dir     )

       def     __UpperCamelCase     (							self ,   lowercase__ ,   lowercase__ ,   lowercase__ ,   lowercase__=None     ):







             '''simple docstring'''



             __A    =comment + f'''\nclass {class_name}(nn.Module):\n''' + class_code
             if overwrite_result is not None:
                   __A    =comment + f'''\nclass {class_name}(nn.Module):\n''' + overwrite_result
             __A    =black.Mode(target_versions={black.TargetVersion.PYaa} ,   line_length=1_1_9     )
             __A    =black.format_str(lowercase__ ,   mode=lowercase__     )
             __A    =os.path.join(self.diffusers_dir ,   '''new_code.py'''     )
             with open(lowercase__ ,   '''w''' ,   newline='''\n'''     ) as f:
                   f.write(lowercase__     )
             if overwrite_result is None:
                   self.assertTrue(len(check_copies.is_copy_consistent(lowercase__     )     ) == 0     )
             else:
                   check_copies.is_copy_consistent(f.name ,   overwrite=lowercase__     )
                   with open(lowercase__ ,   '''r'''     ) as f:
                         self.assertTrue(f.read() ,   lowercase__     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =check_copies.find_code_in_diffusers('''schedulers.scheduling_ddpm.DDPMSchedulerOutput'''     )
             self.assertEqual(lowercase__ ,   lowercase__     )


       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             self.check_copy_consistency(
                 '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput''' ,   '''DDPMSchedulerOutput''' ,   REFERENCE_CODE + '''\n''' ,   )

             # With no empty line at the end
             self.check_copy_consistency(
                 '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput''' ,   '''DDPMSchedulerOutput''' ,   lowercase__ ,   )

             # Copy consistency with rename
             self.check_copy_consistency(
                 '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test''' ,   '''TestSchedulerOutput''' ,   re.sub('''DDPM''' ,   '''Test''' ,   lowercase__     ) ,   )

             # Copy consistency with a really long name
             __A    ='''TestClassWithAReallyLongNameBecauseSomePeopleLikeThatForSomeReason'''
             self.check_copy_consistency(
                 f'''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->{long_class_name}''' ,   f'''{long_class_name}SchedulerOutput''' ,   re.sub('''Bert''' ,   lowercase__ ,   lowercase__     ) ,   )

             # Copy consistency with overwrite
             self.check_copy_consistency(
                 '''# Copied from diffusers.schedulers.scheduling_ddpm.DDPMSchedulerOutput with DDPM->Test''' ,   '''TestSchedulerOutput''' ,   lowercase__ ,   overwrite_result=re.sub('''DDPM''' ,   '''Test''' ,   lowercase__     ) ,   )


