
import argparse
import math
import traceback

import dateutil.parser as date_parser
import requests


def 				A	( lowercase			)       ->  List[str]:
		'''simple docstring'''

		UpperCamelCase          =					{}

		UpperCamelCase          =					job['started_at']
		UpperCamelCase          =					job['completed_at']

		UpperCamelCase          =					date_parser.parse(lowercase			)
		UpperCamelCase          =					date_parser.parse(lowercase			)

		UpperCamelCase          =					round((end_datetime - start_datetime).total_seconds() / 6_0.0			)

		UpperCamelCase          =					start
		UpperCamelCase          =					end
		UpperCamelCase          =					duration_in_min

		return job_info


def 				A	( lowercase   ,	lowercase=None			)       ->  Optional[int]:
		'''simple docstring'''

		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(lowercase   ,	headers=lowercase			).json()
		UpperCamelCase          =					{}

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

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

					_UpperCAmelCase :			Optional[int]              =	get_job_time(args.workflow_run_id)
					_UpperCAmelCase :			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']}''')


import os
import sys
import unittest


_UpperCAmelCase :			str              =	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_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
_UpperCAmelCase :			Tuple              =	os.path.join(git_repo_path, "src", "diffusers")


class     lowercase (		unittest.TestCase       ):



		def __UpperCamelCase			(			self	)  -> Tuple:
				"""simple docstring"""
				UpperCamelCase          =					find_backend('    if not is_torch_available():'	)
				self.assertEqual(A_    ,				'torch'	)

				# backend_with_underscore = find_backend("    if not is_tensorflow_text_available():")
				# self.assertEqual(backend_with_underscore, "tensorflow_text")

				UpperCamelCase          =					find_backend('    if not (is_torch_available() and is_transformers_available()):'	)
				self.assertEqual(A_    ,				'torch_and_transformers'	)

				# double_backend_with_underscore = find_backend(
				#    "    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"
				# )
				# self.assertEqual(double_backend_with_underscore, "sentencepiece_and_tensorflow_text")

				UpperCamelCase          =					find_backend(
				    '    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):'	)
				self.assertEqual(A_    ,				'torch_and_transformers_and_onnx'	)



		def __UpperCamelCase			(			self	)  -> Optional[Any]:
				"""simple docstring"""
				UpperCamelCase          =					read_init()
				# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
				self.assertIn('torch'    ,				A_	)
				self.assertIn('torch_and_transformers'    ,				A_	)
				self.assertIn('flax_and_transformers'    ,				A_	)
				self.assertIn('torch_and_transformers_and_onnx'    ,				A_	)

				# Likewise, we can't assert on the exact content of a key
				self.assertIn('UNet2DModel'    ,				objects['torch']	)
				self.assertIn('FlaxUNet2DConditionModel'    ,				objects['flax']	)
				self.assertIn('StableDiffusionPipeline'    ,				objects['torch_and_transformers']	)
				self.assertIn('FlaxStableDiffusionPipeline'    ,				objects['flax_and_transformers']	)
				self.assertIn('LMSDiscreteScheduler'    ,				objects['torch_and_scipy']	)
				self.assertIn('OnnxStableDiffusionPipeline'    ,				objects['torch_and_transformers_and_onnx']	)



		def __UpperCamelCase			(			self	)  -> Any:
				"""simple docstring"""
				UpperCamelCase          =					create_dummy_object('CONSTANT'    ,				'\'torch\''	)
				self.assertEqual(A_    ,				'\nCONSTANT = None\n'	)

				UpperCamelCase          =					create_dummy_object('function'    ,				'\'torch\''	)
				self.assertEqual(
				    A_    ,				'\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n'	)

				UpperCamelCase          =					'\nclass FakeClass(metaclass=DummyObject):\n    _backends = \'torch\'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, \'torch\')\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, \'torch\')\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, \'torch\')\n'
				UpperCamelCase          =					create_dummy_object('FakeClass'    ,				'\'torch\''	)
				self.assertEqual(A_    ,				A_	)



		def __UpperCamelCase			(			self	)  -> List[str]:
				"""simple docstring"""
				UpperCamelCase          =					'# This file is autogenerated by the command `make fix-copies`, do not edit.\nfrom ..utils import DummyObject, requires_backends\n\n\nCONSTANT = None\n\n\ndef function(*args, **kwargs):\n    requires_backends(function, ["torch"])\n\n\nclass FakeClass(metaclass=DummyObject):\n    _backends = ["torch"]\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, ["torch"])\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, ["torch"])\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, ["torch"])\n'
				UpperCamelCase          =					create_dummy_files({'torch': ['CONSTANT', 'function', 'FakeClass']}	)
				self.assertEqual(dummy_files['torch']    ,				A_	)
