




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

import requests







def 		lowercase__   (		__A:	str							,__A:	Union[str, Any]=None				):





					'''simple docstring'''






					__magic_name__							:	Union[str, Any]    							=							None
					if token is not None:
										__magic_name__							:	Any    							=							{'''Accept''': '''application/vnd.github+json''', '''Authorization''': F'''Bearer {token}'''}

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

					try:
										job_links.update({job['''name''']: job['''html_url'''] for job in result['''jobs''']}				)
										__magic_name__							:	Union[str, Any]    							=							math.ceil((result['''total_count'''] - 1_0_0) / 1_0_0				)

										for i in range(lowerCAmelCase__				):
															__magic_name__							:	Any    							=							requests.get(url + F'''&page={i + 2}'''							,headers=lowerCAmelCase__				).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 		lowercase__   (		__A:	List[Any]							,__A:	int=None				):





					'''simple docstring'''






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

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

					try:
										artifacts.update({artifact['''name''']: artifact['''archive_download_url'''] for artifact in result['''artifacts''']}				)
										__magic_name__							:	List[Any]    							=							math.ceil((result['''total_count'''] - 1_0_0) / 1_0_0				)

										for i in range(lowerCAmelCase__				):
															__magic_name__							:	Tuple    							=							requests.get(url + F'''&page={i + 2}'''							,headers=lowerCAmelCase__				).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 		lowercase__   (		__A:	List[Any]							,__A:	Union[str, Any]							,__A:	List[Any]							,__A:	Optional[Any]				):





					'''simple docstring'''






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

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







def 		lowercase__   (		__A:	Dict							,__A:	List[str]=None				):





					'''simple docstring'''






					__magic_name__							:	str    							=							[]
					__magic_name__							:	List[Any]    							=							[]
					__magic_name__							:	Dict    							=							None

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

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

					__magic_name__							:	Union[str, Any]    							=							None
					if job_name and job_links:
										__magic_name__							:	List[Any]    							=							job_links.get(lowerCAmelCase__							,lowerCAmelCase__				)

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

					return result







def 		lowercase__   (		__A:	Union[str, Any]							,__A:	Any=None				):





					'''simple docstring'''






					__magic_name__							:	Optional[Any]    							=							[]

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

					return errors







def 		lowercase__   (		__A:	Tuple							,__A:	Union[str, Any]=None				):





					'''simple docstring'''






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

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







def 		lowercase__   (		__A:	Optional[Any]				):





					'''simple docstring'''






					__magic_name__							:	int    							=							test.split('''::'''				)[0]
					if test.startswith('''tests/models/'''				):
										__magic_name__							:	Dict    							=							test.split('''/'''				)[2]
					else:
										__magic_name__							:	str    							=							None

					return test







def 		lowercase__   (		__A:	Any							,__A:	Union[str, Any]=None				):





					'''simple docstring'''






					__magic_name__							:	Optional[int]    							=							[(x[0], x[1], get_model(x[2]				)) for x in logs]
					__magic_name__							:	List[str]    							=							[x for x in logs if x[2] is not None]
					__magic_name__							:	Any    							=							{x[2] for x in logs}

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

					__magic_name__							:	Tuple    							=							dict(sorted(r.items()							,key=lambda __A				: item[1]["count"]							,reverse=lowerCAmelCase__				)				)
					return r







def 		lowercase__   (		__A:	Optional[Any]				):





					'''simple docstring'''






					__magic_name__							:	Any    							=							'''| no. | error | status |'''
					__magic_name__							:	List[str]    							=							'''|-:|:-|:-|'''
					__magic_name__							:	List[Any]    							=							[header, sep]
					for error in reduced_by_error:
										__magic_name__							:	str    							=							reduced_by_error[error]['''count''']
										__magic_name__							:	Dict    							=							F'''| {count} | {error[:1_0_0]} |  |'''
										lines.append(lowerCAmelCase__				)

					return "\n".join(lowerCAmelCase__				)







def 		lowercase__   (		__A:	Tuple				):





					'''simple docstring'''






					__magic_name__							:	str    							=							'''| model | no. of errors | major error | count |'''
					__magic_name__							:	List[str]    							=							'''|-:|-:|-:|-:|'''
					__magic_name__							:	Dict    							=							[header, sep]
					for model in reduced_by_model:
										__magic_name__							:	Union[str, Any]    							=							reduced_by_model[model]['''count''']
										__magic_name__							,    __magic_name__							:	Dict    							=							list(reduced_by_model[model]['''errors'''].items()				)[0]
										__magic_name__							:	Tuple    							=							F'''| {model} | {count} | {error[:6_0]} | {_count} |'''
										lines.append(lowerCAmelCase__				)

					return "\n".join(lowerCAmelCase__				)


if __name__ == "__main__":
	__lowerCamelCase   :						Optional[Any]				=			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   :						int				=			parser.parse_args()

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

	__lowerCamelCase   :						Any				=			get_job_links(args.workflow_run_id, token=args.token)
	__lowerCamelCase   :						Optional[Any]				=			{}
	# 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   :						Tuple				=			k.find(''' / ''')
				__lowerCamelCase   :						Any				=			k[index + len(''' / ''') :]
			__lowerCamelCase   :						int				=			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   :						int				=			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   :						Any				=			get_all_errors(args.output_dir, job_links=job_links)

	# `e[1]` is the error
	__lowerCamelCase   :						Optional[Any]				=			Counter()
	counter.update([e[1] for e in errors])

	# print the top 30 most common test errors
	__lowerCamelCase   :						Tuple				=			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   :						Any				=			reduce_by_error(errors)
	__lowerCamelCase   :						int				=			reduce_by_model(errors)

	__lowerCamelCase   :						Optional[int]				=			make_github_table(reduced_by_error)
	__lowerCamelCase   :						Tuple				=			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)








from sklearn.metrics import mean_squared_error

import datasets


__lowerCamelCase   :						List[str]				=			'''\
@article{scikit-learn,
 title={Scikit-learn: Machine Learning in {P}ython},
 author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
         and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
         and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
         Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
 journal={Journal of Machine Learning Research},
 volume={12},
 pages={2825--2830},
 year={2011}
}
'''

__lowerCamelCase   :						Optional[int]				=			'''\
Mean Squared Error(MSE) is the average of the square of difference between the predicted
and actual values.
'''


__lowerCamelCase   :						str				=			'''
Args:
    predictions: array-like of shape (n_samples,) or (n_samples, n_outputs)
        Estimated target values.
    references: array-like of shape (n_samples,) or (n_samples, n_outputs)
        Ground truth (correct) target values.
    sample_weight: array-like of shape (n_samples,), default=None
        Sample weights.
    multioutput: {"raw_values", "uniform_average"} or array-like of shape (n_outputs,), default="uniform_average"
        Defines aggregating of multiple output values. Array-like value defines weights used to average errors.

        "raw_values" : Returns a full set of errors in case of multioutput input.

        "uniform_average" : Errors of all outputs are averaged with uniform weight.

    squared : bool, default=True
        If True returns MSE value, if False returns RMSE (Root Mean Squared Error) value.

Returns:
    mse : mean squared error.
Examples:

    >>> mse_metric = datasets.load_metric("mse")
    >>> predictions = [2.5, 0.0, 2, 8]
    >>> references = [3, -0.5, 2, 7]
    >>> results = mse_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'mse\': 0.375}
    >>> rmse_result = mse_metric.compute(predictions=predictions, references=references, squared=False)
    >>> print(rmse_result)
    {\'mse\': 0.6123724356957945}

    If you\'re using multi-dimensional lists, then set the config as follows :

    >>> mse_metric = datasets.load_metric("mse", "multilist")
    >>> predictions = [[0.5, 1], [-1, 1], [7, -6]]
    >>> references = [[0, 2], [-1, 2], [8, -5]]
    >>> results = mse_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'mse\': 0.7083333333333334}
    >>> results = mse_metric.compute(predictions=predictions, references=references, multioutput=\'raw_values\')
    >>> print(results) # doctest: +NORMALIZE_WHITESPACE
    {\'mse\': array([0.41666667, 1. ])}
'''


@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION				,_KWARGS_DESCRIPTION						)
class    lowerCamelCase    (		datasets.Metric						):






			'''simple docstring'''





			def 							UpperCAmelCase__       ( self			:   Dict  )						->   Tuple:
								return datasets.MetricInfo(
								    description=_DESCRIPTION       ,						citation=_CITATION       ,						inputs_description=_KWARGS_DESCRIPTION       ,						features=datasets.Features(self._get_feature_types()  )       ,						reference_urls=[
								        '''https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html'''
								    ]       ,						)

			def 							UpperCAmelCase__       ( self			:   List[Any]  )						->   Any:
								if self.config_name == "multilist":
													return {
													    "predictions": datasets.Sequence(datasets.Value('''float'''  )  ),
													    "references": datasets.Sequence(datasets.Value('''float'''  )  ),
													}
								else:
													return {
													    "predictions": datasets.Value('''float'''  ),
													    "references": datasets.Value('''float'''  ),
													}


			def 							UpperCAmelCase__       ( self			:   Union[str, Any]       ,						lowerCamelCase_			:   Optional[Any]       ,						lowerCamelCase_			:   int       ,						lowerCamelCase_			:   int=None       ,						lowerCamelCase_			:   List[Any]="uniform_average"       ,						lowerCamelCase_			:   List[str]=True  )						->   List[str]:
								__magic_name__							:	Tuple    							=							mean_squared_error(
								    lowerCamelCase_       ,						lowerCamelCase_       ,						sample_weight=lowerCamelCase_       ,						multioutput=lowerCamelCase_       ,						squared=lowerCamelCase_  )

								return {"mse": mse}



