



"""simple docstring"""







import copy
import inspect
import unittest

from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available

from ...test_backbone_common import BackboneTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor


if is_torch_available():
							import torch

							from transformers import TimmBackbone, TimmBackboneConfig

from ...test_pipeline_mixin import PipelineTesterMixin
class        __A       :







		'''simple docstring'''





		def __init__(	self						:  Dict			,_snake_case						:  Dict			,_snake_case						:  str=None			,_snake_case						:  Optional[Any]=None			,_snake_case						:  Union[str, Any]=None			,_snake_case						:  Dict="resnet50"			,_snake_case						:  Dict=3			,_snake_case						:  Union[str, Any]=32			,_snake_case						:  int=3			,_snake_case						:  List[Any]=True			,_snake_case						:  Optional[int]=True			,)					->		Any:






				"""simple docstring"""



				lowercase__   :    Optional[int]				=			parent
				lowercase__   :    List[str]				=			out_indices if out_indices is not None else [4]
				lowercase__   :    Optional[int]				=			stage_names
				lowercase__   :    Optional[int]				=			out_features
				lowercase__   :    int				=			backbone
				lowercase__   :    List[str]				=			batch_size
				lowercase__   :    List[str]				=			image_size
				lowercase__   :    int				=			num_channels
				lowercase__   :    Any				=			use_pretrained_backbone
				lowercase__   :    Any				=			is_training







		def 					UpperCAmelCase    (	self						:  int						)					->		Dict:






				"""simple docstring"""



				lowercase__   :    List[Any]				=			floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]						)
				lowercase__   :    Union[str, Any]				=			self.get_config()

				return config, pixel_values







		def 					UpperCAmelCase    (	self						:  List[str]						)					->		str:






				"""simple docstring"""



				return TimmBackboneConfig(
				    image_size=self.image_size			,num_channels=self.num_channels			,out_features=self.out_features			,out_indices=self.out_indices			,stage_names=self.stage_names			,use_pretrained_backbone=self.use_pretrained_backbone			,backbone=self.backbone			,)







		def 					UpperCAmelCase    (	self						:  str			,_snake_case						:  Any			,_snake_case						:  List[str]						)					->		Any:






				"""simple docstring"""



				lowercase__   :    List[Any]				=			TimmBackbone(config=_snake_case						)
				model.to(_snake_case						)
				model.eval()
				with torch.no_grad():
						lowercase__   :    str				=			model(_snake_case						)
				self.parent.assertEqual(
				    result.feature_map[-1].shape			,(self.batch_size, model.channels[-1], 14, 14)			,)







		def 					UpperCAmelCase    (	self						:  Optional[Any]						)					->		Optional[Any]:






				"""simple docstring"""



				lowercase__   :    List[str]				=			self.prepare_config_and_inputs()
				lowercase__		,			lowercase__   :    str				=			config_and_inputs
				lowercase__   :    str				=			{'''pixel_values''': pixel_values}
				return config, inputs_dict





@require_torch
@require_timm
class        __A       (	A_     ,A_     ,A_     ,unittest.TestCase    ):







		'''simple docstring'''





		lowerCAmelCase			:					Optional[Any]   	=				(TimmBackbone,) if is_torch_available() else ()
		lowerCAmelCase			:					List[Any]   	=				{"feature-extraction": TimmBackbone} if is_torch_available() else {}
		lowerCAmelCase			:					int   	=				False
		lowerCAmelCase			:					List[str]   	=				False
		lowerCAmelCase			:					Tuple   	=				False
		lowerCAmelCase			:					int   	=				False







		def 					UpperCAmelCase    (	self						:  Any						)					->		int:






				"""simple docstring"""



				lowercase__   :    Optional[Any]				=			TimmBackboneModelTester(self						)
				lowercase__   :    Optional[Any]				=			ConfigTester(self			,config_class=_snake_case			,has_text_modality=_snake_case						)







		def 					UpperCAmelCase    (	self						:  Union[str, Any]						)					->		List[Any]:






				"""simple docstring"""



				self.config_tester.create_and_test_config_to_json_string()
				self.config_tester.create_and_test_config_to_json_file()
				self.config_tester.create_and_test_config_from_and_save_pretrained()
				self.config_tester.create_and_test_config_with_num_labels()
				self.config_tester.check_config_can_be_init_without_params()
				self.config_tester.check_config_arguments_init()







		def 					UpperCAmelCase    (	self						:  Optional[Any]						)					->		Union[str, Any]:






				"""simple docstring"""



				lowercase__   :    str				=			'''resnet18'''
				lowercase__   :    List[Any]				=			'''microsoft/resnet-18'''

				lowercase__   :    str				=			AutoBackbone.from_pretrained(_snake_case			,use_timm_backbone=_snake_case						)
				lowercase__   :    List[str]				=			AutoBackbone.from_pretrained(_snake_case						)

				self.assertEqual(len(timm_model.out_features						)			,len(transformers_model.out_features						)						)
				self.assertEqual(len(timm_model.stage_names						)			,len(transformers_model.stage_names						)						)
				self.assertEqual(timm_model.channels			,transformers_model.channels						)
				# Out indices are set to the last layer by default. For timm models, we don't know
				# the number of layers in advance, so we set it to (-1,), whereas for transformers
				# models, we set it to [len(stage_names) - 1] (kept for backward compatibility).
				self.assertEqual(timm_model.out_indices			,(-1,)						)
				self.assertEqual(transformers_model.out_indices			,[len(timm_model.stage_names						) - 1]						)

				lowercase__   :    Optional[Any]				=			AutoBackbone.from_pretrained(_snake_case			,use_timm_backbone=_snake_case			,out_indices=[1, 2, 3]						)
				lowercase__   :    int				=			AutoBackbone.from_pretrained(_snake_case			,out_indices=[1, 2, 3]						)

				self.assertEqual(timm_model.out_indices			,transformers_model.out_indices						)
				self.assertEqual(len(timm_model.out_features						)			,len(transformers_model.out_features						)						)
				self.assertEqual(timm_model.channels			,transformers_model.channels						)







		@unittest.skip('''TimmBackbone doesn\'t support feed forward chunking'''						)
		def 					UpperCAmelCase    (	self						:  Tuple						)					->		Union[str, Any]:






				"""simple docstring"""



				pass







		@unittest.skip('''TimmBackbone doesn\'t have num_hidden_layers attribute'''						)
		def 					UpperCAmelCase    (	self						:  Union[str, Any]						)					->		Dict:






				"""simple docstring"""



				pass







		@unittest.skip('''TimmBackbone initialization is managed on the timm side'''						)
		def 					UpperCAmelCase    (	self						:  str						)					->		List[Any]:






				"""simple docstring"""



				pass







		@unittest.skip('''TimmBackbone models doesn\'t have inputs_embeds'''						)
		def 					UpperCAmelCase    (	self						:  int						)					->		Any:






				"""simple docstring"""



				pass







		@unittest.skip('''TimmBackbone models doesn\'t have inputs_embeds'''						)
		def 					UpperCAmelCase    (	self						:  str						)					->		List[Any]:






				"""simple docstring"""



				pass







		@unittest.skip('''TimmBackbone model cannot be created without specifying a backbone checkpoint'''						)
		def 					UpperCAmelCase    (	self						:  str						)					->		int:






				"""simple docstring"""



				pass







		@unittest.skip('''Only checkpoints on timm can be loaded into TimmBackbone'''						)
		def 					UpperCAmelCase    (	self						:  Tuple						)					->		Tuple:






				"""simple docstring"""



				pass







		@unittest.skip('''model weights aren\'t tied in TimmBackbone.'''						)
		def 					UpperCAmelCase    (	self						:  Any						)					->		int:






				"""simple docstring"""



				pass







		@unittest.skip('''model weights aren\'t tied in TimmBackbone.'''						)
		def 					UpperCAmelCase    (	self						:  Optional[Any]						)					->		Any:






				"""simple docstring"""



				pass







		@unittest.skip('''Only checkpoints on timm can be loaded into TimmBackbone'''						)
		def 					UpperCAmelCase    (	self						:  Optional[Any]						)					->		Tuple:






				"""simple docstring"""



				pass







		@unittest.skip('''Only checkpoints on timm can be loaded into TimmBackbone'''						)
		def 					UpperCAmelCase    (	self						:  Union[str, Any]						)					->		Any:






				"""simple docstring"""



				pass







		@unittest.skip('''TimmBackbone doesn\'t have hidden size info in its configuration.'''						)
		def 					UpperCAmelCase    (	self						:  Optional[Any]						)					->		Union[str, Any]:






				"""simple docstring"""



				pass







		@unittest.skip('''TimmBackbone doesn\'t support output_attentions.'''						)
		def 					UpperCAmelCase    (	self						:  Union[str, Any]						)					->		Union[str, Any]:






				"""simple docstring"""



				pass







		@unittest.skip('''Safetensors is not supported by timm.'''						)
		def 					UpperCAmelCase    (	self						:  int						)					->		Optional[int]:






				"""simple docstring"""



				pass







		@unittest.skip('''Will be fixed soon by reducing the size of the model used for common tests.'''						)
		def 					UpperCAmelCase    (	self						:  List[Any]						)					->		int:






				"""simple docstring"""



				pass







		def 					UpperCAmelCase    (	self						:  List[str]						)					->		Optional[Any]:






				"""simple docstring"""



				lowercase__		,			lowercase__   :    Union[str, Any]				=			self.model_tester.prepare_config_and_inputs_for_common()

				for model_class in self.all_model_classes:
						lowercase__   :    str				=			model_class(_snake_case						)
						lowercase__   :    Optional[int]				=			inspect.signature(model.forward						)
						# signature.parameters is an OrderedDict => so arg_names order is deterministic
						lowercase__   :    Optional[int]				=			[*signature.parameters.keys()]

						lowercase__   :    Union[str, Any]				=			['''pixel_values''']
						self.assertListEqual(arg_names[:1]			,_snake_case						)







		def 					UpperCAmelCase    (	self						:  Any						)					->		Optional[Any]:






				"""simple docstring"""



				lowercase__		,			lowercase__   :    Union[str, Any]				=			self.model_tester.prepare_config_and_inputs_for_common()
				lowercase__   :    int				=			True
				lowercase__   :    List[Any]				=			self.has_attentions

				# no need to test all models as different heads yield the same functionality
				lowercase__   :    Union[str, Any]				=			self.all_model_classes[0]
				lowercase__   :    Optional[int]				=			model_class(_snake_case						)
				model.to(_snake_case						)

				lowercase__   :    List[str]				=			self._prepare_for_class(_snake_case			,_snake_case						)
				lowercase__   :    Optional[Any]				=			model(**_snake_case						)
				lowercase__   :    Optional[int]				=			outputs[0][-1]

				# Encoder-/Decoder-only models
				lowercase__   :    Optional[Any]				=			outputs.hidden_states[0]
				hidden_states.retain_grad()

				if self.has_attentions:
						lowercase__   :    str				=			outputs.attentions[0]
						attentions.retain_grad()

				output.flatten()[0].backward(retain_graph=_snake_case						)

				self.assertIsNotNone(hidden_states.grad						)

				if self.has_attentions:
						self.assertIsNotNone(attentions.grad						)







		def 					UpperCAmelCase    (	self						:  Optional[Any]						)					->		Optional[int]:






				"""simple docstring"""



				lowercase__		,			lowercase__   :    Optional[Any]				=			self.model_tester.prepare_config_and_inputs_for_common()

				for model_class in self.all_model_classes:
						lowercase__   :    Tuple				=			model_class(_snake_case						)
						model.to(_snake_case						)
						model.eval()
						lowercase__   :    Optional[Any]				=			model(**_snake_case						)

						self.assertEqual(len(result.feature_maps						)			,len(config.out_indices						)						)
						self.assertEqual(len(model.channels						)			,len(config.out_indices						)						)

						# Check output of last stage is taken if out_features=None, out_indices=None
						lowercase__   :    Optional[int]				=			copy.deepcopy(_snake_case						)
						lowercase__   :    Union[str, Any]				=			None
						lowercase__   :    Optional[int]				=			model_class(_snake_case						)
						model.to(_snake_case						)
						model.eval()
						lowercase__   :    Any				=			model(**_snake_case						)

						self.assertEqual(len(result.feature_maps						)			,1						)
						self.assertEqual(len(model.channels						)			,1						)

						# Check backbone can be initialized with fresh weights
						lowercase__   :    List[Any]				=			copy.deepcopy(_snake_case						)
						lowercase__   :    List[Any]				=			False
						lowercase__   :    Dict				=			model_class(_snake_case						)
						model.to(_snake_case						)
						model.eval()
						lowercase__   :    List[str]				=			model(**_snake_case						)





import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter

import requests

def        a						(      _UpperCAmelCase							:					Any ,   _UpperCAmelCase							:					Any=None						):







		'''simple docstring'''





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

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

		try:
				job_links.update({job['''name''']: job['''html_url'''] for job in result['''jobs''']}						)
				__UpperCAmelCase    :     List[Any]													=	math.ceil((result['''total_count'''] - 1_00) / 1_00						)

				for i in range(_UpperCAmelCase						):
						__UpperCAmelCase    :     Optional[Any]													=	requests.get(url + f'&page={i + 2}' ,   headers=_UpperCAmelCase						).json()
						job_links.update({job['''name''']: job['''html_url'''] for job in result['''jobs''']}						)

				return job_links
		except Exception:
				print(f'Unknown error, could not fetch links:\n{traceback.format_exc()}'						)

		return {}

def        a						(      _UpperCAmelCase							:					List[str] ,   _UpperCAmelCase							:					List[str]=None						):







		'''simple docstring'''





		__UpperCAmelCase    :     List[Any]													=	None
		if token is not None:
				__UpperCAmelCase    :     Tuple													=	{'''Accept''': '''application/vnd.github+json''', '''Authorization''': f'Bearer {token}'}

		__UpperCAmelCase    :     int													=	f'https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100'
		__UpperCAmelCase    :     str													=	requests.get(_UpperCAmelCase ,   headers=_UpperCAmelCase						).json()
		__UpperCAmelCase    :     List[Any]													=	{}

		try:
				artifacts.update({artifact['''name''']: artifact['''archive_download_url'''] for artifact in result['''artifacts''']}						)
				__UpperCAmelCase    :     str													=	math.ceil((result['''total_count'''] - 1_00) / 1_00						)

				for i in range(_UpperCAmelCase						):
						__UpperCAmelCase    :     Dict													=	requests.get(url + f'&page={i + 2}' ,   headers=_UpperCAmelCase						).json()
						artifacts.update({artifact['''name''']: artifact['''archive_download_url'''] for artifact in result['''artifacts''']}						)

				return artifacts
		except Exception:
				print(f'Unknown error, could not fetch links:\n{traceback.format_exc()}'						)

		return {}

def        a						(      _UpperCAmelCase							:					Optional[Any] ,   _UpperCAmelCase							:					Optional[int] ,   _UpperCAmelCase							:					List[str] ,   _UpperCAmelCase							:					int						):







		'''simple docstring'''





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

		__UpperCAmelCase    :     int													=	requests.get(_UpperCAmelCase ,   headers=_UpperCAmelCase ,   allow_redirects=_UpperCAmelCase						)
		__UpperCAmelCase    :     Optional[int]													=	result.headers['''Location''']
		__UpperCAmelCase    :     Optional[int]													=	requests.get(_UpperCAmelCase ,   allow_redirects=_UpperCAmelCase						)
		__UpperCAmelCase    :     int													=	os.path.join(_UpperCAmelCase ,   f'{artifact_name}.zip'						)
		with open(_UpperCAmelCase ,   '''wb'''						) as fp:
				fp.write(response.content						)

def        a						(      _UpperCAmelCase							:					Dict ,   _UpperCAmelCase							:					List[str]=None						):







		'''simple docstring'''





		__UpperCAmelCase    :     Union[str, Any]													=	[]
		__UpperCAmelCase    :     int													=	[]
		__UpperCAmelCase    :     List[Any]													=	None

		with zipfile.ZipFile(_UpperCAmelCase						) as z:
				for filename in z.namelist():
						if not os.path.isdir(_UpperCAmelCase						):
								# read the file
								if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
										with z.open(_UpperCAmelCase						) as f:
												for line in f:
														__UpperCAmelCase    :     Tuple													=	line.decode('''UTF-8'''						).strip()
														if filename == "failures_line.txt":
																try:
																		# `error_line` is the place where `error` occurs
																		__UpperCAmelCase    :     int													=	line[: line.index(''': '''						)]
																		__UpperCAmelCase    :     Any													=	line[line.index(''': '''						) + len(''': '''						) :]
																		errors.append([error_line, error]						)
																except Exception:
																		# skip un-related lines
																		pass
														elif filename == "summary_short.txt" and line.startswith('''FAILED '''						):
																# `test` is the test method that failed
																__UpperCAmelCase    :     str													=	line[len('''FAILED '''						) :]
																failed_tests.append(_UpperCAmelCase						)
														elif filename == "job_name.txt":
																__UpperCAmelCase    :     Tuple													=	line

		if len(_UpperCAmelCase						) != len(_UpperCAmelCase						):
				raise ValueError(
				    f'`errors` and `failed_tests` should have the same number of elements. Got {len(_UpperCAmelCase						)} for `errors` '
				    f'and {len(_UpperCAmelCase						)} for `failed_tests` instead. The test reports in {artifact_zip_path} have some'
				    ''' problem.'''						)

		__UpperCAmelCase    :     str													=	None
		if job_name and job_links:
				__UpperCAmelCase    :     Any													=	job_links.get(_UpperCAmelCase ,   _UpperCAmelCase						)

		# A list with elements of the form (line of error, error, failed test)
		__UpperCAmelCase    :     Dict													=	[x + [y] + [job_link] for x, y in zip(_UpperCAmelCase ,   _UpperCAmelCase						)]

		return result

def        a						(      _UpperCAmelCase							:					Dict ,   _UpperCAmelCase							:					Tuple=None						):







		'''simple docstring'''





		__UpperCAmelCase    :     str													=	[]

		__UpperCAmelCase    :     str													=	[os.path.join(_UpperCAmelCase ,   _UpperCAmelCase						) for p in os.listdir(_UpperCAmelCase						) if p.endswith('''.zip'''						)]
		for p in paths:
				errors.extend(get_errors_from_single_artifact(_UpperCAmelCase ,   job_links=_UpperCAmelCase						)						)

		return errors

def        a						(      _UpperCAmelCase							:					str ,   _UpperCAmelCase							:					Optional[Any]=None						):







		'''simple docstring'''





		__UpperCAmelCase    :     Union[str, Any]													=	Counter()
		counter.update([x[1] for x in logs]						)
		__UpperCAmelCase    :     Dict													=	counter.most_common()
		__UpperCAmelCase    :     int													=	{}
		for error, count in counts:
				if error_filter is None or error not in error_filter:
						__UpperCAmelCase    :     Tuple													=	{'''count''': count, '''failed_tests''': [(x[2], x[0]) for x in logs if x[1] == error]}

		__UpperCAmelCase    :     Union[str, Any]													=	dict(sorted(r.items() ,   key=lambda _UpperCAmelCase						: item[1]["count"] ,   reverse=_UpperCAmelCase						)						)
		return r

def        a						(      _UpperCAmelCase							:					Dict						):







		'''simple docstring'''





		__UpperCAmelCase    :     List[str]													=	test.split('''::'''						)[0]
		if test.startswith('''tests/models/'''						):
				__UpperCAmelCase    :     Optional[int]													=	test.split('''/'''						)[2]
		else:
				__UpperCAmelCase    :     Optional[Any]													=	None

		return test

def        a						(      _UpperCAmelCase							:					Optional[int] ,   _UpperCAmelCase							:					int=None						):







		'''simple docstring'''





		__UpperCAmelCase    :     Dict													=	[(x[0], x[1], get_model(x[2]						)) for x in logs]
		__UpperCAmelCase    :     int													=	[x for x in logs if x[2] is not None]
		__UpperCAmelCase    :     Tuple													=	{x[2] for x in logs}

		__UpperCAmelCase    :     List[str]													=	{}
		for test in tests:
				__UpperCAmelCase    :     List[str]													=	Counter()
				# count by errors in `test`
				counter.update([x[1] for x in logs if x[2] == test]						)
				__UpperCAmelCase    :     Tuple													=	counter.most_common()
				__UpperCAmelCase    :     Any													=	{error: count for error, count in counts if (error_filter is None or error not in error_filter)}
				__UpperCAmelCase    :     List[Any]													=	sum(error_counts.values()						)
				if n_errors > 0:
						__UpperCAmelCase    :     Tuple													=	{'''count''': n_errors, '''errors''': error_counts}

		__UpperCAmelCase    :     Optional[int]													=	dict(sorted(r.items() ,   key=lambda _UpperCAmelCase						: item[1]["count"] ,   reverse=_UpperCAmelCase						)						)
		return r

def        a						(      _UpperCAmelCase							:					Union[str, Any]						):







		'''simple docstring'''





		__UpperCAmelCase    :     Any													=	'''| no. | error | status |'''
		__UpperCAmelCase    :     List[str]													=	'''|-:|:-|:-|'''
		__UpperCAmelCase    :     Union[str, Any]													=	[header, sep]
		for error in reduced_by_error:
				__UpperCAmelCase    :     Tuple													=	reduced_by_error[error]['''count''']
				__UpperCAmelCase    :     int													=	f'| {count} | {error[:1_00]} |  |'
				lines.append(_UpperCAmelCase						)

		return "\n".join(_UpperCAmelCase						)

def        a						(      _UpperCAmelCase							:					Dict						):







		'''simple docstring'''





		__UpperCAmelCase    :     Union[str, Any]													=	'''| model | no. of errors | major error | count |'''
		__UpperCAmelCase    :     List[Any]													=	'''|-:|-:|-:|-:|'''
		__UpperCAmelCase    :     Tuple													=	[header, sep]
		for model in reduced_by_model:
				__UpperCAmelCase    :     List[Any]													=	reduced_by_model[model]['''count''']
				__UpperCAmelCase							,					__UpperCAmelCase    :     int													=	list(reduced_by_model[model]['''errors'''].items()						)[0]
				__UpperCAmelCase    :     Dict													=	f'| {model} | {count} | {error[:60]} | {_count} |'
				lines.append(_UpperCAmelCase						)

		return "\n".join(_UpperCAmelCase						)


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.")
				parser.add_argument(
				    "--output_dir",
				    type=str,
				    required=True,
				    help="Where to store the downloaded artifacts and other result files.",
				)
				parser.add_argument("--token", default=None, type=str, help="A token that has actions:read permission.")
				__A   			=parser.parse_args()

				os.makedirs(args.output_dir, exist_ok=True)

				__A   			=get_job_links(args.workflow_run_id, token=args.token)
				__A   			={}
				# To deal with `workflow_call` event, where a job name is the combination of the job names in the caller and callee.
				# For example, `PyTorch 1.11 / Model tests (models/albert, single-gpu)`.
				if _job_links:
								for k, v in _job_links.items():
												# This is how GitHub actions combine job names.
												if " / " in k:
																__A   			=k.find(" / ")
																__A   			=k[index + len(" / ") :]
												__A   			=v
				with open(os.path.join(args.output_dir, "job_links.json"), "w", encoding="UTF-8") as fp:
								json.dump(job_links, fp, ensure_ascii=False, indent=4)

				__A   			=get_artifacts_links(args.workflow_run_id, token=args.token)
				with open(os.path.join(args.output_dir, "artifacts.json"), "w", encoding="UTF-8") as fp:
								json.dump(artifacts, fp, ensure_ascii=False, indent=4)

				for idx, (name, url) in enumerate(artifacts.items()):
								download_artifact(name, url, args.output_dir, args.token)
								# Be gentle to GitHub
								time.sleep(1)

				__A   			=get_all_errors(args.output_dir, job_links=job_links)

				# `e[1]` is the error
				__A   			=Counter()
				counter.update([e[1] for e in errors])

				# print the top 30 most common test errors
				__A   			=counter.most_common(3_0)
				for item in most_common:
								print(item)

				with open(os.path.join(args.output_dir, "errors.json"), "w", encoding="UTF-8") as fp:
								json.dump(errors, fp, ensure_ascii=False, indent=4)

				__A   			=reduce_by_error(errors)
				__A   			=reduce_by_model(errors)

				__A   			=make_github_table(reduced_by_error)
				__A   			=make_github_table_per_model(reduced_by_model)

				with open(os.path.join(args.output_dir, "reduced_by_error.txt"), "w", encoding="UTF-8") as fp:
								fp.write(sa)
				with open(os.path.join(args.output_dir, "reduced_by_model.txt"), "w", encoding="UTF-8") as fp:
								fp.write(sa)





