"""simple docstring"""





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

import requests





def        a_  (   _lowerCAmelCase						:				Dict     ,				_lowerCAmelCase						:				List[str]=None  ):





       '''simple docstring'''

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

       lowercase__    :	Dict     					=			f"""https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"""
       lowercase__    :	List[Any]     					=			requests.get(_lowerCAmelCase     ,				headers=_lowerCAmelCase  ).json()
       lowercase__    :	Optional[Any]     					=			{}

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

              for i in range(_lowerCAmelCase  ):
                     lowercase__    :	Optional[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        a_  (   _lowerCAmelCase						:				Union[str, Any]     ,				_lowerCAmelCase						:				Tuple=None  ):





       '''simple docstring'''

       lowercase__    :	int     					=			None
       if token is not None:
              lowercase__    :	List[str]     					=			{'Accept': 'application/vnd.github+json', 'Authorization': f"""Bearer {token}"""}

       lowercase__    :	Union[str, Any]     					=			f"""https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100"""
       lowercase__    :	Any     					=			requests.get(_lowerCAmelCase     ,				headers=_lowerCAmelCase  ).json()
       lowercase__    :	str     					=			{}

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

              for i in range(_lowerCAmelCase  ):
                     lowercase__    :	int     					=			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        a_  (   _lowerCAmelCase						:				Optional[Any]     ,				_lowerCAmelCase						:				Optional[Any]     ,				_lowerCAmelCase						:				str     ,				_lowerCAmelCase						:				List[Any]  ):





       '''simple docstring'''

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

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





def        a_  (   _lowerCAmelCase						:				Union[str, Any]     ,				_lowerCAmelCase						:				Optional[int]=None  ):





       '''simple docstring'''

       lowercase__    :	Optional[int]     					=			[]
       lowercase__    :	List[Any]     					=			[]
       lowercase__    :	List[str]     					=			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:
                                                 lowercase__    :	Optional[Any]     					=			line.decode('UTF-8'  ).strip()
                                                 if filename == "failures_line.txt":
                                                        try:
                                                               # `error_line` is the place where `error` occurs
                                                               lowercase__    :	Union[str, Any]     					=			line[: line.index(': '  )]
                                                               lowercase__    :	List[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
                                                        lowercase__    :	str     					=			line[len('FAILED '  ) :]
                                                        failed_tests.append(_lowerCAmelCase  )
                                                 elif filename == "job_name.txt":
                                                        lowercase__    :	str     					=			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.'  )

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

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

       return result





def        a_  (   _lowerCAmelCase						:				str     ,				_lowerCAmelCase						:				str=None  ):





       '''simple docstring'''

       lowercase__    :	Any     					=			[]

       lowercase__    :	Optional[Any]     					=			[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        a_  (   _lowerCAmelCase						:				Dict     ,				_lowerCAmelCase						:				Tuple=None  ):





       '''simple docstring'''

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

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





def        a_  (   _lowerCAmelCase						:				List[Any]  ):





       '''simple docstring'''

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

       return test





def        a_  (   _lowerCAmelCase						:				Union[str, Any]     ,				_lowerCAmelCase						:				Tuple=None  ):





       '''simple docstring'''

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

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

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





def        a_  (   _lowerCAmelCase						:				List[Any]  ):





       '''simple docstring'''

       lowercase__    :	Optional[int]     					=			'| no. | error | status |'
       lowercase__    :	Any     					=			'|-:|:-|:-|'
       lowercase__    :	Optional[int]     					=			[header, sep]
       for error in reduced_by_error:
              lowercase__    :	List[Any]     					=			reduced_by_error[error]['count']
              lowercase__    :	Any     					=			f"""| {count} | {error[:100]} |  |"""
              lines.append(_lowerCAmelCase  )

       return "\n".join(_lowerCAmelCase  )





def        a_  (   _lowerCAmelCase						:				Any  ):





       '''simple docstring'''

       lowercase__    :	Optional[Any]     					=			'| model | no. of errors | major error | count |'
       lowercase__    :	Dict     					=			'|-:|-:|-:|-:|'
       lowercase__    :	List[Any]     					=			[header, sep]
       for model in reduced_by_model:
              lowercase__    :	Optional[Any]     					=			reduced_by_model[model]['count']
              lowercase__					,   lowercase__    :	List[Any]     					=			list(reduced_by_model[model]['errors'].items()  )[0]
              lowercase__    :	Optional[Any]     					=			f"""| {model} | {count} | {error[:60]} | {_count} |"""
              lines.append(_lowerCAmelCase  )

       return "\n".join(_lowerCAmelCase  )


if __name__ == "__main__":
       _UpperCamelCase     :		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.")
       _UpperCamelCase     :		str											=					parser.parse_args()

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

       _UpperCamelCase     :		Tuple											=					get_job_links(args.workflow_run_id, token=args.token)
       _UpperCamelCase     :		str											=					{}
       # 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     :		List[str]											=					k.find(" / ")
                            _UpperCamelCase     :		int											=					k[index + len(" / ") :]
                     _UpperCamelCase     :		Any											=					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     :		Tuple											=					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     :		Union[str, Any]											=					get_all_errors(args.output_dir, job_links=job_links)

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

       # print the top 30 most common test errors
       _UpperCamelCase     :		Union[str, Any]											=					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     :		List[str]											=					reduce_by_error(errors)
       _UpperCamelCase     :		int											=					reduce_by_model(errors)

       _UpperCamelCase     :		List[str]											=					make_github_table(reduced_by_error)
       _UpperCamelCase     :		List[Any]											=					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_flax_available, is_torch_available


_UpperCamelCase     :		str											=					{
    "configuration_gpt_neo": ["GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoConfig", "GPTNeoOnnxConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _UpperCamelCase     :		Tuple											=					[
           "GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST",
           "GPTNeoForCausalLM",
           "GPTNeoForQuestionAnswering",
           "GPTNeoForSequenceClassification",
           "GPTNeoForTokenClassification",
           "GPTNeoModel",
           "GPTNeoPreTrainedModel",
           "load_tf_weights_in_gpt_neo",
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _UpperCamelCase     :		Dict											=					[
           "FlaxGPTNeoForCausalLM",
           "FlaxGPTNeoModel",
           "FlaxGPTNeoPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_gpt_neo import GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoConfig, GPTNeoOnnxConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_gpt_neo import (
                  GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST,
                  GPTNeoForCausalLM,
                  GPTNeoForQuestionAnswering,
                  GPTNeoForSequenceClassification,
                  GPTNeoForTokenClassification,
                  GPTNeoModel,
                  GPTNeoPreTrainedModel,
                  load_tf_weights_in_gpt_neo,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel


else:
       import sys

       _UpperCamelCase     :		List[str]											=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

