






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

import requests


def 	lowerCamelCase__      (  lowercase    ,  lowercase=None					):

  """simple docstring"""






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

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

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

    for i in range(lowercase					):
      SCREAMING_SNAKE_CASE							:   Dict						    =     requests.get(url + F'''&page={i + 2}'''    ,  headers=lowercase					).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__      (  lowercase    ,  lowercase=None					):

  """simple docstring"""






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

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

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

    for i in range(lowercase					):
      SCREAMING_SNAKE_CASE							:   Dict						    =     requests.get(url + F'''&page={i + 2}'''    ,  headers=lowercase					).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__      (  lowercase    ,  lowercase    ,  lowercase    ,  lowercase					):

  """simple docstring"""






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

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


def 	lowerCamelCase__      (  lowercase    ,  lowercase=None					):

  """simple docstring"""






  SCREAMING_SNAKE_CASE							:   List[Any]						    =     []
  SCREAMING_SNAKE_CASE							:   Any						    =     []
  SCREAMING_SNAKE_CASE							:   Any						    =     None

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

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

  SCREAMING_SNAKE_CASE							:   Union[str, Any]						    =     None
  if job_name and job_links:
    SCREAMING_SNAKE_CASE							:   Tuple						    =     job_links.get(lowercase    ,  lowercase					)

  # A list with elements of the form (line of error, error, failed test)
  SCREAMING_SNAKE_CASE							:   List[Any]						    =     [x + [y] + [job_link] for x, y in zip(lowercase    ,  lowercase					)]

  return result


def 	lowerCamelCase__      (  lowercase    ,  lowercase=None					):

  """simple docstring"""






  SCREAMING_SNAKE_CASE							:   List[Any]						    =     []

  SCREAMING_SNAKE_CASE							:   Optional[int]						    =     [os.path.join(lowercase    ,  lowercase					) for p in os.listdir(lowercase					) if p.endswith(".zip"					)]
  for p in paths:
    errors.extend(get_errors_from_single_artifact(lowercase    ,  job_links=lowercase					)					)

  return errors


def 	lowerCamelCase__      (  lowercase    ,  lowercase=None					):

  """simple docstring"""






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

  SCREAMING_SNAKE_CASE							:   Union[str, Any]						    =     dict(sorted(r.items()    ,  key=lambda lowercase					: item[1]["count"]    ,  reverse=lowercase					)					)
  return r


def 	lowerCamelCase__      (  lowercase					):

  """simple docstring"""






  SCREAMING_SNAKE_CASE							:   List[Any]						    =     test.split("::"					)[0]
  if test.startswith("tests/models/"					):
    SCREAMING_SNAKE_CASE							:   Dict						    =     test.split("/"					)[2]
  else:
    SCREAMING_SNAKE_CASE							:   Optional[int]						    =     None

  return test


def 	lowerCamelCase__      (  lowercase    ,  lowercase=None					):

  """simple docstring"""






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

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

  SCREAMING_SNAKE_CASE							:   List[Any]						    =     dict(sorted(r.items()    ,  key=lambda lowercase					: item[1]["count"]    ,  reverse=lowercase					)					)
  return r


def 	lowerCamelCase__      (  lowercase					):

  """simple docstring"""






  SCREAMING_SNAKE_CASE							:   Dict						    =     "| no. | error | status |"
  SCREAMING_SNAKE_CASE							:   Tuple						    =     "|-:|:-|:-|"
  SCREAMING_SNAKE_CASE							:   int						    =     [header, sep]
  for error in reduced_by_error:
    SCREAMING_SNAKE_CASE							:   Optional[int]						    =     reduced_by_error[error]["count"]
    SCREAMING_SNAKE_CASE							:   str						    =     F'''| {count} | {error[:100]} |  |'''
    lines.append(lowercase					)

  return "\n".join(lowercase					)


def 	lowerCamelCase__      (  lowercase					):

  """simple docstring"""






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

  return "\n".join(lowercase					)


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

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

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

   snake_case     					=		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)

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

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

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

   snake_case     					=		reduce_by_error(errors)
   snake_case     					=		reduce_by_model(errors)

   snake_case     					=		make_github_table(reduced_by_error)
   snake_case     					=		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)














import argparse

import torch

from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert


logging.set_verbosity_info()






def      _snake_case     (__lowercase     ,   __lowercase     ,   __lowercase):
   # Initialise PyTorch model
   UpperCamelCase_						=  AlbertConfig.from_json_file(__lowercase)
   print(f"""Building PyTorch model from configuration: {config}""")
   UpperCamelCase_						=  AlbertForPreTraining(__lowercase)

   # Load weights from tf checkpoint
   load_tf_weights_in_albert(__lowercase     ,   __lowercase     ,   __lowercase)

   # Save pytorch-model
   print(f"""Save PyTorch model to {pytorch_dump_path}""")
   torch.save(model.state_dict()     ,   __lowercase)


if __name__ == "__main__":
 snake_case__   :						Tuple													=   argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     """--tf_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
 )
 parser.add_argument(
     """--albert_config_file""",
     default=None,
     type=str,
     required=True,
     help=(
         """The config json file corresponding to the pre-trained ALBERT model. \n"""
         """This specifies the model architecture."""
     ),
 )
 parser.add_argument(
     """--pytorch_dump_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
 )
 snake_case__   :						str													=   parser.parse_args()
 convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)





