





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

import requests




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE=None		)    ->       Tuple:
  lowercase__           =  None
  if token is not None:
    lowercase__           =  {'Accept': 'application/vnd.github+json', 'Authorization': F"""Bearer {token}"""}

  lowercase__           =  F"""https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"""
  lowercase__           =  requests.get(lowerCAmelCase__		,						headers=lowerCAmelCase__		).json()
  lowercase__           =  {}

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

    for i in range(lowerCAmelCase__		):
      lowercase__           =  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       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE=None		)    ->       Any:
  lowercase__           =  None
  if token is not None:
    lowercase__           =  {'Accept': 'application/vnd.github+json', 'Authorization': F"""Bearer {token}"""}

  lowercase__           =  F"""https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100"""
  lowercase__           =  requests.get(lowerCAmelCase__		,						headers=lowerCAmelCase__		).json()
  lowercase__           =  {}

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

    for i in range(lowerCAmelCase__		):
      lowercase__           =  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       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)    ->       Optional[Any]:
  lowercase__           =  None
  if token is not None:
    lowercase__           =  {'Accept': 'application/vnd.github+json', 'Authorization': F"""Bearer {token}"""}

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




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE=None		)    ->       Optional[Any]:
  lowercase__           =  []
  lowercase__           =  []
  lowercase__           =  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__           =  line.decode('UTF-8'		).strip()
              if filename == "failures_line.txt":
                try:
                  # `error_line` is the place where `error` occurs
                  lowercase__           =  line[: line.index(': '		)]
                  lowercase__           =  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__           =  line[len('FAILED '		) :]
                failed_tests.append(lowerCAmelCase__		)
              elif filename == "job_name.txt":
                lowercase__           =  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__           =  None
  if job_name and job_links:
    lowercase__           =  job_links.get(lowerCAmelCase__		,						lowerCAmelCase__		)

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

  return result




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE=None		)    ->       Any:
  lowercase__           =  []

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

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




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       int:
  lowercase__           =  test.split('::'		)[0]
  if test.startswith('tests/models/'		):
    lowercase__           =  test.split('/'		)[2]
  else:
    lowercase__           =  None

  return test




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE=None		)    ->       str:
  lowercase__           =  [(x[0], x[1], get_model(x[2]		)) for x in logs]
  lowercase__           =  [x for x in logs if x[2] is not None]
  lowercase__           =  {x[2] for x in logs}

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

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




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       List[str]:
  lowercase__           =  '| no. | error | status |'
  lowercase__           =  '|-:|:-|:-|'
  lowercase__           =  [header, sep]
  for error in reduced_by_error:
    lowercase__           =  reduced_by_error[error]['count']
    lowercase__           =  F"""| {count} | {error[:100]} |  |"""
    lines.append(lowerCAmelCase__		)

  return "\n".join(lowerCAmelCase__		)




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

  return "\n".join(lowerCAmelCase__		)


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

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

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

       lowercase_          =		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)

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

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

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

       lowercase_          =		reduce_by_error(errors)
       lowercase_          =		reduce_by_model(errors)

       lowercase_          =		make_github_table(reduced_by_error)
       lowercase_          =		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 ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase_          =		logging.get_logger(__name__)

lowercase_          =		{
    """transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   _UpperCamelCase   :		Optional[Any]			 =	'transfo-xl'
   _UpperCamelCase   :		Any			 =	['mems']
   _UpperCamelCase   :		Any			 =	{
       'n_token': 'vocab_size',
       'hidden_size': 'd_model',
       'num_attention_heads': 'n_head',
       'num_hidden_layers': 'n_layer',
   }


   def __init__(   self      :    Optional[Any]      ,					a      :    Optional[int]=267_735      ,					a      :    str=[20_000, 40_000, 200_000]      ,					a      :    str=1_024      ,					a      :    str=1_024      ,					a      :    int=16      ,					a      :    Optional[int]=64      ,					a      :    Optional[int]=4_096      ,					a      :    int=4      ,					a      :    Tuple=False      ,					a      :    Any=18      ,					a      :    Tuple=1_600      ,					a      :    Union[str, Any]=1_000      ,					a      :    str=True      ,					a      :    Dict=True      ,					a      :    Any=0      ,					a      :    List[Any]=-1      ,					a      :    List[Any]=True      ,					a      :    Tuple=0.1      ,					a      :    List[Any]=0.0      ,					a      :    Optional[Any]=True      ,					a      :    int="normal"      ,					a      :    Optional[Any]=0.01      ,					a      :    str=0.01      ,					a      :    List[Any]=0.02      ,					a      :    List[Any]=1E-5      ,					a      :    Optional[Any]=0      ,					**a      :    Optional[int]      ,					)->       Optional[int]:





     """simple docstring"""







     lowercase__           =  vocab_size
     lowercase__           =  []
     self.cutoffs.extend(a	)
     if proj_share_all_but_first:
       lowercase__           =  [False] + [True] * len(self.cutoffs	)
     else:
       lowercase__           =  [False] + [False] * len(self.cutoffs	)
     lowercase__           =  d_model
     lowercase__           =  d_embed
     lowercase__           =  d_head
     lowercase__           =  d_inner
     lowercase__           =  div_val
     lowercase__           =  pre_lnorm
     lowercase__           =  n_layer
     lowercase__           =  n_head
     lowercase__           =  mem_len
     lowercase__           =  same_length
     lowercase__           =  attn_type
     lowercase__           =  clamp_len
     lowercase__           =  sample_softmax
     lowercase__           =  adaptive
     lowercase__           =  dropout
     lowercase__           =  dropatt
     lowercase__           =  untie_r
     lowercase__           =  init
     lowercase__           =  init_range
     lowercase__           =  proj_init_std
     lowercase__           =  init_std
     lowercase__           =  layer_norm_epsilon
     super().__init__(eos_token_id=a      ,					**a	)


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[Any]	)->       Union[str, Any]:





     """simple docstring"""







     logger.info(f"""The model {self.model_type} is one of the few models that has no sequence length limit."""	)
     return -1


   @max_position_embeddings.setter
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    Optional[int]	)->       Optional[int]:





     """simple docstring"""







     raise NotImplementedError(
         f"""The model {self.model_type} is one of the few models that has no sequence length limit."""	)


