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

import requests
def  lowerCAmelCase__			(  SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_=None     )				->		Optional[Any]:
			lowerCAmelCase__      :      Tuple         =		None
			if token is not None:
						lowerCAmelCase__      :      int         =		{'Accept': 'application/vnd.github+json', 'Authorization': F'''Bearer {token}'''}

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

			try:
						job_links.update({job['name']: job['html_url'] for job in result['jobs']}     )
						lowerCAmelCase__      :      Optional[int]         =		math.ceil((result['total_count'] - 100) / 100     )

						for i in range(_SCREAMING_SNAKE_CASE     ):
									lowerCAmelCase__      :      int         =		requests.get(url + F'''&page={i + 2}'''       ,							headers=_SCREAMING_SNAKE_CASE     ).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__			(  SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_=None     )				->		Optional[int]:
			lowerCAmelCase__      :      List[str]         =		None
			if token is not None:
						lowerCAmelCase__      :      Union[str, Any]         =		{'Accept': 'application/vnd.github+json', 'Authorization': F'''Bearer {token}'''}

			lowerCAmelCase__      :      Union[str, Any]         =		F'''https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100'''
			lowerCAmelCase__      :      Dict         =		requests.get(_SCREAMING_SNAKE_CASE       ,							headers=_SCREAMING_SNAKE_CASE     ).json()
			lowerCAmelCase__      :      Union[str, Any]         =		{}

			try:
						artifacts.update({artifact['name']: artifact['archive_download_url'] for artifact in result['artifacts']}     )
						lowerCAmelCase__      :      int         =		math.ceil((result['total_count'] - 100) / 100     )

						for i in range(_SCREAMING_SNAKE_CASE     ):
									lowerCAmelCase__      :      Any         =		requests.get(url + F'''&page={i + 2}'''       ,							headers=_SCREAMING_SNAKE_CASE     ).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__			(  SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_     )				->		Any:
			lowerCAmelCase__      :      List[Any]         =		None
			if token is not None:
						lowerCAmelCase__      :      int         =		{'Accept': 'application/vnd.github+json', 'Authorization': F'''Bearer {token}'''}

			lowerCAmelCase__      :      str         =		requests.get(_SCREAMING_SNAKE_CASE       ,							headers=_SCREAMING_SNAKE_CASE       ,							allow_redirects=_SCREAMING_SNAKE_CASE     )
			lowerCAmelCase__      :      Optional[int]         =		result.headers['Location']
			lowerCAmelCase__      :      Optional[Any]         =		requests.get(_SCREAMING_SNAKE_CASE       ,							allow_redirects=_SCREAMING_SNAKE_CASE     )
			lowerCAmelCase__      :      List[str]         =		os.path.join(_SCREAMING_SNAKE_CASE       ,							F'''{artifact_name}.zip'''     )
			with open(_SCREAMING_SNAKE_CASE       ,							'wb'     ) as fp:
						fp.write(response.content     )
def  lowerCAmelCase__			(  SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_=None     )				->		Union[str, Any]:
			lowerCAmelCase__      :      List[str]         =		[]
			lowerCAmelCase__      :      int         =		[]
			lowerCAmelCase__      :      int         =		None

			with zipfile.ZipFile(_SCREAMING_SNAKE_CASE     ) as z:
						for filename in z.namelist():
									if not os.path.isdir(_SCREAMING_SNAKE_CASE     ):
												# read the file
												if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
															with z.open(_SCREAMING_SNAKE_CASE     ) as f:
																		for line in f:
																					lowerCAmelCase__      :      List[Any]         =		line.decode('UTF-8'     ).strip()
																					if filename == "failures_line.txt":
																								try:
																											# `error_line` is the place where `error` occurs
																											lowerCAmelCase__      :      Tuple         =		line[: line.index(': '     )]
																											lowerCAmelCase__      :      Union[str, 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
																								lowerCAmelCase__      :      Tuple         =		line[len('FAILED '     ) :]
																								failed_tests.append(_SCREAMING_SNAKE_CASE     )
																					elif filename == "job_name.txt":
																								lowerCAmelCase__      :      List[str]         =		line

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

			lowerCAmelCase__      :      Optional[Any]         =		None
			if job_name and job_links:
						lowerCAmelCase__      :      Tuple         =		job_links.get(_SCREAMING_SNAKE_CASE       ,							_SCREAMING_SNAKE_CASE     )

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

			return result
def  lowerCAmelCase__			(  SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_=None     )				->		List[Any]:
			lowerCAmelCase__      :      Optional[int]         =		[]

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

			return errors
def  lowerCAmelCase__			(  SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_=None     )				->		List[Any]:
			lowerCAmelCase__      :      List[Any]         =		Counter()
			counter.update([x[1] for x in logs]     )
			lowerCAmelCase__      :      Dict         =		counter.most_common()
			lowerCAmelCase__      :      str         =		{}
			for error, count in counts:
						if error_filter is None or error not in error_filter:
									lowerCAmelCase__      :      Union[str, Any]         =		{'count': count, 'failed_tests': [(x[2], x[0]) for x in logs if x[1] == error]}

			lowerCAmelCase__      :      List[str]         =		dict(sorted(r.items()       ,							key=lambda SCREAMING_SNAKE_CASE_     : item[1]["count"]       ,							reverse=_SCREAMING_SNAKE_CASE     )     )
			return r
def  lowerCAmelCase__			(  SCREAMING_SNAKE_CASE_     )				->		Optional[int]:
			lowerCAmelCase__      :      Any         =		test.split('::'     )[0]
			if test.startswith('tests/models/'     ):
						lowerCAmelCase__      :      Tuple         =		test.split('/'     )[2]
			else:
						lowerCAmelCase__      :      Union[str, Any]         =		None

			return test
def  lowerCAmelCase__			(  SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_=None     )				->		Tuple:
			lowerCAmelCase__      :      Optional[Any]         =		[(x[0], x[1], get_model(x[2]     )) for x in logs]
			lowerCAmelCase__      :      Dict         =		[x for x in logs if x[2] is not None]
			lowerCAmelCase__      :      Any         =		{x[2] for x in logs}

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

			lowerCAmelCase__      :      Optional[Any]         =		dict(sorted(r.items()       ,							key=lambda SCREAMING_SNAKE_CASE_     : item[1]["count"]       ,							reverse=_SCREAMING_SNAKE_CASE     )     )
			return r
def  lowerCAmelCase__			(  SCREAMING_SNAKE_CASE_     )				->		Any:
			lowerCAmelCase__      :      Any         =		'| no. | error | status |'
			lowerCAmelCase__      :      Optional[int]         =		'|-:|:-|:-|'
			lowerCAmelCase__      :      Any         =		[header, sep]
			for error in reduced_by_error:
						lowerCAmelCase__      :      Union[str, Any]         =		reduced_by_error[error]['count']
						lowerCAmelCase__      :      Union[str, Any]         =		F'''| {count} | {error[:100]} |  |'''
						lines.append(_SCREAMING_SNAKE_CASE     )

			return "\n".join(_SCREAMING_SNAKE_CASE     )
def  lowerCAmelCase__			(  SCREAMING_SNAKE_CASE_     )				->		int:
			lowerCAmelCase__      :      Union[str, Any]         =		'| model | no. of errors | major error | count |'
			lowerCAmelCase__      :      Union[str, Any]         =		'|-:|-:|-:|-:|'
			lowerCAmelCase__      :      Any         =		[header, sep]
			for model in reduced_by_model:
						lowerCAmelCase__      :      Optional[int]         =		reduced_by_model[model]['count']
						lowerCAmelCase__      :      Any         =		list(reduced_by_model[model]['errors'].items()     )[0]
						lowerCAmelCase__      :      Optional[int]         =		F'''| {model} | {count} | {error[:60]} | {_count} |'''
						lines.append(_SCREAMING_SNAKE_CASE     )

			return "\n".join(_SCREAMING_SNAKE_CASE     )


if __name__ == "__main__":
					lowerCamelCase__          =		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.""")
					lowerCamelCase__          =		parser.parse_args()

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

					lowerCamelCase__          =		get_job_links(args.workflow_run_id, token=args.token)
					lowerCamelCase__          =		{}
					# 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:
																				lowerCamelCase__          =		k.find(""" / """)
																				lowerCamelCase__          =		k[index + len(""" / """) :]
															lowerCamelCase__          =		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)

					lowerCamelCase__          =		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)

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

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

					# print the top 30 most common test errors
					lowerCamelCase__          =		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)

					lowerCamelCase__          =		reduce_by_error(errors)
					lowerCamelCase__          =		reduce_by_model(errors)

					lowerCamelCase__          =		make_github_table(reduced_by_error)
					lowerCamelCase__          =		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)



'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


__lowercase	:						str       =	{
    'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
    'configuration_data2vec_text': [
        'DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Data2VecTextConfig',
        'Data2VecTextOnnxConfig',
    ],
    'configuration_data2vec_vision': [
        'DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Data2VecVisionConfig',
        'Data2VecVisionOnnxConfig',
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowercase	:						str       =	[
	    'DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'Data2VecAudioForAudioFrameClassification',
	    'Data2VecAudioForCTC',
	    'Data2VecAudioForSequenceClassification',
	    'Data2VecAudioForXVector',
	    'Data2VecAudioModel',
	    'Data2VecAudioPreTrainedModel',
	]
	__lowercase	:						Tuple       =	[
	    'DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'Data2VecTextForCausalLM',
	    'Data2VecTextForMaskedLM',
	    'Data2VecTextForMultipleChoice',
	    'Data2VecTextForQuestionAnswering',
	    'Data2VecTextForSequenceClassification',
	    'Data2VecTextForTokenClassification',
	    'Data2VecTextModel',
	    'Data2VecTextPreTrainedModel',
	]
	__lowercase	:						Dict       =	[
	    'DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'Data2VecVisionForImageClassification',
	    'Data2VecVisionForMaskedImageModeling',
	    'Data2VecVisionForSemanticSegmentation',
	    'Data2VecVisionModel',
	    'Data2VecVisionPreTrainedModel',
	]

if is_tf_available():
	__lowercase	:						Optional[Any]       =	[
	    'TFData2VecVisionForImageClassification',
	    'TFData2VecVisionForSemanticSegmentation',
	    'TFData2VecVisionModel',
	    'TFData2VecVisionPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_dataavec_audio import DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP, DataaVecAudioConfig
	from .configuration_dataavec_text import (
	    DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    DataaVecTextConfig,
	    DataaVecTextOnnxConfig,
	)
	from .configuration_dataavec_vision import (
	    DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    DataaVecVisionConfig,
	    DataaVecVisionOnnxConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_dataavec_audio import (
		    DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DataaVecAudioForAudioFrameClassification,
		    DataaVecAudioForCTC,
		    DataaVecAudioForSequenceClassification,
		    DataaVecAudioForXVector,
		    DataaVecAudioModel,
		    DataaVecAudioPreTrainedModel,
		)
		from .modeling_dataavec_text import (
		    DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DataaVecTextForCausalLM,
		    DataaVecTextForMaskedLM,
		    DataaVecTextForMultipleChoice,
		    DataaVecTextForQuestionAnswering,
		    DataaVecTextForSequenceClassification,
		    DataaVecTextForTokenClassification,
		    DataaVecTextModel,
		    DataaVecTextPreTrainedModel,
		)
		from .modeling_dataavec_vision import (
		    DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DataaVecVisionForImageClassification,
		    DataaVecVisionForMaskedImageModeling,
		    DataaVecVisionForSemanticSegmentation,
		    DataaVecVisionModel,
		    DataaVecVisionPreTrainedModel,
		)
	if is_tf_available():
		from .modeling_tf_dataavec_vision import (
		    TFDataaVecVisionForImageClassification,
		    TFDataaVecVisionForSemanticSegmentation,
		    TFDataaVecVisionModel,
		    TFDataaVecVisionPreTrainedModel,
		)

else:
	import sys

	__lowercase	:						int       =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



