






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

import requests




def      lowercase__      (     __snake_case    :							Tuple     ,       __snake_case    :							Tuple=None  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[int]            =						None
					if token is not None:
										UpperCAmelCase_    :      Tuple            =						{'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_    :      Any            =						requests.get(__snake_case     ,       headers=__snake_case  ).json()
					UpperCAmelCase_    :      List[str]            =						{}

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

										for i in range(__snake_case  ):
															UpperCAmelCase_    :      Union[str, Any]            =						requests.get(url + F"&page={i + 2}"     ,       headers=__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      lowercase__      (     __snake_case    :							Optional[int]     ,       __snake_case    :							Tuple=None  ):


					'''simple docstring'''


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

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

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

										for i in range(__snake_case  ):
															UpperCAmelCase_    :      Dict            =						requests.get(url + F"&page={i + 2}"     ,       headers=__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      lowercase__      (     __snake_case    :							str     ,       __snake_case    :							str     ,       __snake_case    :							int     ,       __snake_case    :							Dict  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Any            =						None
					if token is not None:
										UpperCAmelCase_    :      Any            =						{'Accept': 'application/vnd.github+json', 'Authorization': F"Bearer {token}"}

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




def      lowercase__      (     __snake_case    :							Any     ,       __snake_case    :							Any=None  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Union[str, Any]            =						[]
					UpperCAmelCase_    :      List[Any]            =						[]
					UpperCAmelCase_    :      List[str]            =						None

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

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

					UpperCAmelCase_    :      List[str]            =						None
					if job_name and job_links:
										UpperCAmelCase_    :      Optional[int]            =						job_links.get(__snake_case     ,       __snake_case  )

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

					return result




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


					'''simple docstring'''


					UpperCAmelCase_    :      List[str]            =						[]

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

					return errors




def      lowercase__      (     __snake_case    :							int     ,       __snake_case    :							str=None  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Union[str, Any]            =						Counter()
					counter.update([x[1] for x in logs]  )
					UpperCAmelCase_    :      List[str]            =						counter.most_common()
					UpperCAmelCase_    :      int            =						{}
					for error, count in counts:
										if error_filter is None or error not in error_filter:
															UpperCAmelCase_    :      List[str]            =						{'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 __snake_case  : item[1]["count"]     ,       reverse=__snake_case  )  )
					return r




def      lowercase__      (     __snake_case    :							Optional[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Tuple            =						test.split('::'  )[0]
					if test.startswith('tests/models/'  ):
										UpperCAmelCase_    :      Optional[int]            =						test.split('/'  )[2]
					else:
										UpperCAmelCase_    :      Tuple            =						None

					return test




def      lowercase__      (     __snake_case    :							Optional[Any]     ,       __snake_case    :							int=None  ):


					'''simple docstring'''


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

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

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




def      lowercase__      (     __snake_case    :							Dict  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[Any]            =						'| no. | error | status |'
					UpperCAmelCase_    :      str            =						'|-:|:-|:-|'
					UpperCAmelCase_    :      Optional[int]            =						[header, sep]
					for error in reduced_by_error:
										UpperCAmelCase_    :      Union[str, Any]            =						reduced_by_error[error]['count']
										UpperCAmelCase_    :      Optional[Any]            =						F"| {count} | {error[:100]} |  |"
										lines.append(__snake_case  )

					return "\n".join(__snake_case  )




def      lowercase__      (     __snake_case    :							str  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Dict            =						'| model | no. of errors | major error | count |'
					UpperCAmelCase_    :      Union[str, Any]            =						'|-:|-:|-:|-:|'
					UpperCAmelCase_    :      Any            =						[header, sep]
					for model in reduced_by_model:
										UpperCAmelCase_    :      Tuple            =						reduced_by_model[model]['count']
										UpperCAmelCase_       ,  UpperCAmelCase_    :      Optional[Any]            =						list(reduced_by_model[model]['errors'].items()  )[0]
										UpperCAmelCase_    :      Any            =						F"| {model} | {count} | {error[:60]} | {_count} |"
										lines.append(__snake_case  )

					return "\n".join(__snake_case  )


if __name__ == "__main__":
		__UpperCAmelCase								=						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.')
		__UpperCAmelCase								=						parser.parse_args()

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

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

		__UpperCAmelCase								=						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)

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

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

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

		__UpperCAmelCase								=						reduce_by_error(errors)
		__UpperCAmelCase								=						reduce_by_model(errors)

		__UpperCAmelCase								=						make_github_table(reduced_by_error)
		__UpperCAmelCase								=						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 typing import TYPE_CHECKING

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


UpperCAmelCase	:	Any		     =       {
    """configuration_convbert""": ["""CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ConvBertConfig""", """ConvBertOnnxConfig"""],
    """tokenization_convbert""": ["""ConvBertTokenizer"""],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase	:	List[Any]		     =       ["""ConvBertTokenizerFast"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase	:	List[str]		     =       [
         """CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """ConvBertForMaskedLM""",
         """ConvBertForMultipleChoice""",
         """ConvBertForQuestionAnswering""",
         """ConvBertForSequenceClassification""",
         """ConvBertForTokenClassification""",
         """ConvBertLayer""",
         """ConvBertModel""",
         """ConvBertPreTrainedModel""",
         """load_tf_weights_in_convbert""",
     ]


try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase	:	Union[str, Any]		     =       [
         """TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """TFConvBertForMaskedLM""",
         """TFConvBertForMultipleChoice""",
         """TFConvBertForQuestionAnswering""",
         """TFConvBertForSequenceClassification""",
         """TFConvBertForTokenClassification""",
         """TFConvBertLayer""",
         """TFConvBertModel""",
         """TFConvBertPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_convbert import CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvBertConfig, ConvBertOnnxConfig
     from .tokenization_convbert import ConvBertTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_convbert_fast import ConvBertTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_convbert import (
              CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              ConvBertForMaskedLM,
              ConvBertForMultipleChoice,
              ConvBertForQuestionAnswering,
              ConvBertForSequenceClassification,
              ConvBertForTokenClassification,
              ConvBertLayer,
              ConvBertModel,
              ConvBertPreTrainedModel,
              load_tf_weights_in_convbert,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_convbert import (
              TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFConvBertForMaskedLM,
              TFConvBertForMultipleChoice,
              TFConvBertForQuestionAnswering,
              TFConvBertForSequenceClassification,
              TFConvBertForTokenClassification,
              TFConvBertLayer,
              TFConvBertModel,
              TFConvBertPreTrainedModel,
          )


else:
     import sys

     UpperCAmelCase	:	Union[str, Any]		     =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






