






"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


A_    =							{
    '''configuration_convnext''': ['''CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ConvNextConfig''', '''ConvNextOnnxConfig''']
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A_    =							['''ConvNextFeatureExtractor''']
		A_    =							['''ConvNextImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A_    =							[
		    '''CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ConvNextForImageClassification''',
		    '''ConvNextModel''',
		    '''ConvNextPreTrainedModel''',
		    '''ConvNextBackbone''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A_    =							[
		    '''TFConvNextForImageClassification''',
		    '''TFConvNextModel''',
		    '''TFConvNextPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_convnext import ConvNextFeatureExtractor
				from .image_processing_convnext import ConvNextImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_convnext import (
				    CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ConvNextBackbone,
				    ConvNextForImageClassification,
				    ConvNextModel,
				    ConvNextPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
		import sys

		A_    =							_LazyModule(__name__, globals()['''__file__'''], _import_structure)














"""simple docstring"""



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

import requests




def      _lowerCAmelCase		(							UpperCAmelCase__       :					Tuple,						UpperCAmelCase__       :					Union[str, Any]=None      )		->Tuple:
						A__						:  Dict		  =  None
						if token is not None:
												A__						:  str		  =  {"""Accept""": """application/vnd.github+json""", """Authorization""": f'Bearer {token}'}

						A__						:  Dict		  =  f'https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100'
						A__						:  Any		  =  requests.get(UpperCAmelCase__,						headers=UpperCAmelCase__      ).json()
						A__						:  Tuple		  =  {}

						try:
												job_links.update({job["""name"""]: job["""html_url"""] for job in result["""jobs"""]}      )
												A__						:  Optional[Any]		  =  math.ceil((result["""total_count"""] - 1_0_0) / 1_0_0      )

												for i in range(UpperCAmelCase__      ):
																		A__						:  str		  =  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      _lowerCAmelCase		(							UpperCAmelCase__       :					Union[str, Any],						UpperCAmelCase__       :					str=None      )		->List[str]:
						A__						:  Optional[Any]		  =  None
						if token is not None:
												A__						:  Any		  =  {"""Accept""": """application/vnd.github+json""", """Authorization""": f'Bearer {token}'}

						A__						:  str		  =  f'https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100'
						A__						:  Dict		  =  requests.get(UpperCAmelCase__,						headers=UpperCAmelCase__      ).json()
						A__						:  Any		  =  {}

						try:
												artifacts.update({artifact["""name"""]: artifact["""archive_download_url"""] for artifact in result["""artifacts"""]}      )
												A__						:  Union[str, Any]		  =  math.ceil((result["""total_count"""] - 1_0_0) / 1_0_0      )

												for i in range(UpperCAmelCase__      ):
																		A__						:  Union[str, Any]		  =  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      _lowerCAmelCase		(							UpperCAmelCase__       :					Dict,						UpperCAmelCase__       :					Optional[Any],						UpperCAmelCase__       :					Union[str, Any],						UpperCAmelCase__       :					Any      )		->Tuple:
						A__						:  Tuple		  =  None
						if token is not None:
												A__						:  List[Any]		  =  {"""Accept""": """application/vnd.github+json""", """Authorization""": f'Bearer {token}'}

						A__						:  Tuple		  =  requests.get(UpperCAmelCase__,						headers=UpperCAmelCase__,						allow_redirects=UpperCAmelCase__      )
						A__						:  Dict		  =  result.headers["""Location"""]
						A__						:  Union[str, Any]		  =  requests.get(UpperCAmelCase__,						allow_redirects=UpperCAmelCase__      )
						A__						:  int		  =  os.path.join(UpperCAmelCase__,						f'{artifact_name}.zip'      )
						with open(UpperCAmelCase__,						"""wb"""      ) as fp:
												fp.write(response.content      )




def      _lowerCAmelCase		(							UpperCAmelCase__       :					Optional[int],						UpperCAmelCase__       :					Tuple=None      )		->Tuple:
						A__						:  int		  =  []
						A__						:  Union[str, Any]		  =  []
						A__						:  Optional[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:
																																										A__						:  int		  =  line.decode("""UTF-8"""      ).strip()
																																										if filename == "failures_line.txt":
																																																try:
																																																						# `error_line` is the place where `error` occurs
																																																						A__						:  List[str]		  =  line[: line.index(""": """      )]
																																																						A__						:  str		  =  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
																																																A__						:  Any		  =  line[len("""FAILED """      ) :]
																																																failed_tests.append(UpperCAmelCase__      )
																																										elif filename == "job_name.txt":
																																																A__						:  Any		  =  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."""      )

						A__						:  List[str]		  =  None
						if job_name and job_links:
												A__						:  Any		  =  job_links.get(UpperCAmelCase__,						UpperCAmelCase__      )

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

						return result




def      _lowerCAmelCase		(							UpperCAmelCase__       :					Optional[Any],						UpperCAmelCase__       :					int=None      )		->str:
						A__						:  List[Any]		  =  []

						A__						:  Dict		  =  [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      _lowerCAmelCase		(							UpperCAmelCase__       :					Dict,						UpperCAmelCase__       :					Dict=None      )		->List[Any]:
						A__						:  Dict		  =  Counter()
						counter.update([x[1] for x in logs]      )
						A__						:  str		  =  counter.most_common()
						A__						:  Dict		  =  {}
						for error, count in counts:
												if error_filter is None or error not in error_filter:
																		A__						:  Optional[int]		  =  {"""count""": count, """failed_tests""": [(x[2], x[0]) for x in logs if x[1] == error]}

						A__						:  List[str]		  =  dict(sorted(r.items(),						key=lambda UpperCAmelCase__      : item[1]["count"],						reverse=UpperCAmelCase__      )      )
						return r




def      _lowerCAmelCase		(							UpperCAmelCase__       :					Optional[Any]      )		->str:
						A__						:  List[str]		  =  test.split("""::"""      )[0]
						if test.startswith("""tests/models/"""      ):
												A__						:  Union[str, Any]		  =  test.split("""/"""      )[2]
						else:
												A__						:  int		  =  None

						return test




def      _lowerCAmelCase		(							UpperCAmelCase__       :					str,						UpperCAmelCase__       :					str=None      )		->Optional[Any]:
						A__						:  Any		  =  [(x[0], x[1], get_model(x[2]      )) for x in logs]
						A__						:  List[Any]		  =  [x for x in logs if x[2] is not None]
						A__						:  Union[str, Any]		  =  {x[2] for x in logs}

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

						A__						:  Dict		  =  dict(sorted(r.items(),						key=lambda UpperCAmelCase__      : item[1]["count"],						reverse=UpperCAmelCase__      )      )
						return r




def      _lowerCAmelCase		(							UpperCAmelCase__       :					Dict      )		->List[Any]:
						A__						:  List[Any]		  =  """| no. | error | status |"""
						A__						:  Union[str, Any]		  =  """|-:|:-|:-|"""
						A__						:  Dict		  =  [header, sep]
						for error in reduced_by_error:
												A__						:  List[Any]		  =  reduced_by_error[error]["""count"""]
												A__						:  List[Any]		  =  f'| {count} | {error[:1_0_0]} |  |'
												lines.append(UpperCAmelCase__      )

						return "\n".join(UpperCAmelCase__      )




def      _lowerCAmelCase		(							UpperCAmelCase__       :					int      )		->int:
						A__						:  str		  =  """| model | no. of errors | major error | count |"""
						A__						:  Optional[int]		  =  """|-:|-:|-:|-:|"""
						A__						:  Tuple		  =  [header, sep]
						for model in reduced_by_model:
												A__						:  Optional[Any]		  =  reduced_by_model[model]["""count"""]
												A__  ,  A__						:  Optional[Any]		  =  list(reduced_by_model[model]["""errors"""].items()      )[0]
												A__						:  Optional[int]		  =  f'| {model} | {count} | {error[:6_0]} | {_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(30)
						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)






