





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

import requests


def _A       (   __magic_name__  , __magic_name__=None	):
   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(__magic_name__  , headers=__magic_name__	).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(__magic_name__	):
         lowercase__			       =  requests.get(url + f'''&page={i + 2}'''  , headers=__magic_name__	).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       (   __magic_name__  , __magic_name__=None	):
   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(__magic_name__  , headers=__magic_name__	).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(__magic_name__	):
         lowercase__			       =  requests.get(url + f'''&page={i + 2}'''  , headers=__magic_name__	).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       (   __magic_name__  , __magic_name__  , __magic_name__  , __magic_name__	):
   lowercase__			       =  None
   if token is not None:
      lowercase__			       =  {"Accept": "application/vnd.github+json", "Authorization": f'''Bearer {token}'''}

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


def _A       (   __magic_name__  , __magic_name__=None	):
   lowercase__			       =  []
   lowercase__			       =  []
   lowercase__			       =  None

   with zipfile.ZipFile(__magic_name__	) as z:
      for filename in z.namelist():
         if not os.path.isdir(__magic_name__	):
            # read the file
            if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
               with z.open(__magic_name__	) 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(__magic_name__	)
                     elif filename == "job_name.txt":
                        lowercase__			       =  line

   if len(__magic_name__	) != len(__magic_name__	):
      raise ValueError(
          f'''`errors` and `failed_tests` should have the same number of elements. Got {len(__magic_name__	)} for `errors` '''
          f'''and {len(__magic_name__	)} 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(__magic_name__  , __magic_name__	)

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

   return result


def _A       (   __magic_name__  , __magic_name__=None	):
   lowercase__			       =  []

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

   return errors


def _A       (   __magic_name__  , __magic_name__=None	):
   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 __magic_name__	: item[1]["count"]  , reverse=__magic_name__	)	)
   return r


def _A       (   __magic_name__	):
   lowercase__			       =  test.split("::"	)[0]
   if test.startswith("tests/models/"	):
      lowercase__			       =  test.split("/"	)[2]
   else:
      lowercase__			       =  None

   return test


def _A       (   __magic_name__  , __magic_name__=None	):
   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 __magic_name__	: item[1]["count"]  , reverse=__magic_name__	)	)
   return r


def _A       (   __magic_name__	):
   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(__magic_name__	)

   return "\n".join(__magic_name__	)


def _A       (   __magic_name__	):
   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(__magic_name__	)

   return "\n".join(__magic_name__	)


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 time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch

import multiprocess
import numpy as np
import pytest

from datasets.utils.py_utils import (
    NestedDataStructure,
    asdict,
    iflatmap_unordered,
    map_nested,
    temp_seed,
    temporary_assignment,
    zip_dict,
)

from .utils import require_tf, require_torch


def _A       (   __magic_name__	):  # picklable for multiprocessing
   return x.sum()


def _A       (   __magic_name__	):  # picklable for multiprocessing
   return i + 1





@dataclass
class  lowerCAmelCase							:
  __lowerCamelCase		=      42
  __lowerCamelCase		=      42





class  lowerCAmelCase							(       lowercase_ ):







  def   UpperCAmelCase					(      self  :Optional[Any] ):






     '''simple docstring'''





     lowercase__			       =  {}
     lowercase__			       =  []
     lowercase__			       =  1
     lowercase__			       =  [1, 2]
     lowercase__			       =  {"a": 1, "b": 2}
     lowercase__			       =  {"a": [1, 2], "b": [3, 4]}
     lowercase__			       =  {"a": {"1": 1}, "b": 2}
     lowercase__			       =  {"a": 1, "b": 2, "c": 3, "d": 4}
     lowercase__			       =  {}
     lowercase__			       =  []
     lowercase__			       =  2
     lowercase__			       =  [2, 3]
     lowercase__			       =  {"a": 2, "b": 3}
     lowercase__			       =  {"a": [2, 3], "b": [4, 5]}
     lowercase__			       =  {"a": {"1": 2}, "b": 3}
     lowercase__			       =  {"a": 2, "b": 3, "c": 4, "d": 5}
     self.assertEqual(map_nested(_lowercase   ,							_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase )   ,							_lowercase )

     lowercase__			       =  2
     self.assertEqual(map_nested(_lowercase   ,							_lowercase   ,							num_proc=_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase   ,							num_proc=_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase   ,							num_proc=_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase   ,							num_proc=_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase   ,							num_proc=_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase   ,							num_proc=_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase   ,							num_proc=_lowercase )   ,							_lowercase )
     self.assertEqual(map_nested(_lowercase   ,							_lowercase   ,							num_proc=_lowercase )   ,							_lowercase )

     lowercase__			       =  {"a": np.eye(2 ), "b": np.zeros(3 ), "c": np.ones(2 )}
     lowercase__			       =  {"a": 2, "b": 0, "c": 2}
     lowercase__			       =  {
         "a": np.eye(2 ).astype(_lowercase ),
         "b": np.zeros(3 ).astype(_lowercase ),
         "c": np.ones(2 ).astype(_lowercase ),
     }
     self.assertEqual(map_nested(_lowercase   ,							_lowercase   ,							map_numpy=_lowercase )   ,							_lowercase )
     self.assertEqual(
         {k: v.tolist() for k, v in map_nested(_lowercase   ,							_lowercase   ,							map_numpy=_lowercase ).items()}   ,							{k: v.tolist() for k, v in expected_map_nested_sna_int.items()}   ,							)
     self.assertEqual(map_nested(_lowercase   ,							_lowercase   ,							map_numpy=_lowercase   ,							num_proc=_lowercase )   ,							_lowercase )
     self.assertEqual(
         {k: v.tolist() for k, v in map_nested(_lowercase   ,							_lowercase   ,							map_numpy=_lowercase   ,							num_proc=_lowercase ).items()}   ,							{k: v.tolist() for k, v in expected_map_nested_sna_int.items()}   ,							)
     with self.assertRaises(_lowercase ):  # can't pickle a local lambda
        map_nested(lambda _lowercase : x + 1   ,							_lowercase   ,							num_proc=_lowercase )







  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





     lowercase__			       =  {"a": 1, "b": 2}
     lowercase__			       =  {"a": 3, "b": 4}
     lowercase__			       =  {"a": 5, "b": 6}
     lowercase__			       =  sorted([("a", (1, 3, 5)), ("b", (2, 4, 6))] )
     self.assertEqual(sorted(zip_dict(_lowercase   ,							_lowercase   ,							_lowercase ) )   ,							_lowercase )







  def   UpperCAmelCase					(      self  :Union[str, Any] ):






     '''simple docstring'''





     class  lowerCAmelCase							:
       __lowerCamelCase		=      'bar'
     lowercase__			       =  Foo()
     self.assertEqual(foo.my_attr   ,							"bar" )
     with temporary_assignment(_lowercase   ,							"my_attr"   ,							"BAR" ):
        self.assertEqual(foo.my_attr   ,							"BAR" )
     self.assertEqual(foo.my_attr   ,							"bar" )


@pytest.mark.parametrize(
    "iterable_length, num_proc, expected_num_proc"  , [
        (1, None, 1),
        (1, 1, 1),
        (2, None, 1),
        (2, 1, 1),
        (2, 2, 1),
        (2, 3, 1),
        (3, 2, 1),
        (16, 16, 16),
        (16, 17, 16),
        (17, 16, 16),
    ]  , )
def _A       (   __magic_name__  , __magic_name__  , __magic_name__	):
   with patch("datasets.utils.py_utils._single_map_nested"	) as mock_single_map_nested, patch(
       "datasets.parallel.parallel.Pool"	) as mock_multiprocessing_pool:
      lowercase__			       =  {f'''{i}''': i for i in range(__magic_name__	)}
      lowercase__			       =  map_nested(lambda __magic_name__	: x + 10  , __magic_name__  , num_proc=__magic_name__  , parallel_min_length=16	)
      if expected_num_proc == 1:
         assert mock_single_map_nested.called
         assert not mock_multiprocessing_pool.called
      else:
         assert not mock_single_map_nested.called
         assert mock_multiprocessing_pool.called
         assert mock_multiprocessing_pool.call_args[0][0] == expected_num_proc





class  lowerCAmelCase							(       lowercase_ ):







  @require_tf
  def   UpperCAmelCase					(      self  :List[Any] ):






     '''simple docstring'''





     import tensorflow as tf
     from tensorflow.keras import layers

     lowercase__			       =  layers.Dense(2 )

     def gen_random_output():
        lowercase__			       =  tf.random.uniform((1, 3) )
        return model(_lowercase ).numpy()

     with temp_seed(42   ,							set_tensorflow=_lowercase ):
        lowercase__			       =  gen_random_output()
     with temp_seed(42   ,							set_tensorflow=_lowercase ):
        lowercase__			       =  gen_random_output()
     lowercase__			       =  gen_random_output()

     np.testing.assert_equal(_lowercase   ,							_lowercase )
     self.assertGreater(np.abs(outa - outa ).sum()   ,							0 )







  @require_torch
  def   UpperCAmelCase					(      self  :Optional[int] ):






     '''simple docstring'''





     import torch

     def gen_random_output():
        lowercase__			       =  torch.nn.Linear(3   ,							2 )
        lowercase__			       =  torch.rand(1   ,							3 )
        return model(_lowercase ).detach().numpy()

     with temp_seed(42   ,							set_pytorch=_lowercase ):
        lowercase__			       =  gen_random_output()
     with temp_seed(42   ,							set_pytorch=_lowercase ):
        lowercase__			       =  gen_random_output()
     lowercase__			       =  gen_random_output()

     np.testing.assert_equal(_lowercase   ,							_lowercase )
     self.assertGreater(np.abs(outa - outa ).sum()   ,							0 )







  def   UpperCAmelCase					(      self  :str ):






     '''simple docstring'''





     def gen_random_output():
        return np.random.rand(1   ,							3 )

     with temp_seed(42 ):
        lowercase__			       =  gen_random_output()
     with temp_seed(42 ):
        lowercase__			       =  gen_random_output()
     lowercase__			       =  gen_random_output()

     np.testing.assert_equal(_lowercase   ,							_lowercase )
     self.assertGreater(np.abs(outa - outa ).sum()   ,							0 )


@pytest.mark.parametrize("input_data"  , [{}]	)
def _A       (   __magic_name__	):
   lowercase__			       =  NestedDataStructure(__magic_name__	).data
   assert output_data == input_data


@pytest.mark.parametrize(
    "data, expected_output"  , [
        ({}, []),
        ([], []),
        ("foo", ["foo"]),
        (["foo", "bar"], ["foo", "bar"]),
        ([["foo", "bar"]], ["foo", "bar"]),
        ([[["foo"], ["bar"]]], ["foo", "bar"]),
        ([[["foo"], "bar"]], ["foo", "bar"]),
        ({"a": 1, "b": 2}, [1, 2]),
        ({"a": [1, 2], "b": [3, 4]}, [1, 2, 3, 4]),
        ({"a": [[1, 2]], "b": [[3, 4]]}, [1, 2, 3, 4]),
        ({"a": [[1, 2]], "b": [3, 4]}, [1, 2, 3, 4]),
        ({"a": [[[1], [2]]], "b": [[[3], [4]]]}, [1, 2, 3, 4]),
        ({"a": [[[1], [2]]], "b": [[3, 4]]}, [1, 2, 3, 4]),
        ({"a": [[[1], [2]]], "b": [3, 4]}, [1, 2, 3, 4]),
        ({"a": [[[1], [2]]], "b": [3, [4]]}, [1, 2, 3, 4]),
        ({"a": {"1": 1}, "b": 2}, [1, 2]),
        ({"a": {"1": [1]}, "b": 2}, [1, 2]),
        ({"a": {"1": [1]}, "b": [2]}, [1, 2]),
    ]  , )
def _A       (   __magic_name__  , __magic_name__	):
   lowercase__			       =  NestedDataStructure(__magic_name__	).flatten()
   assert output == expected_output


def _A       (   ):
   lowercase__			       =  A(x=1  , y="foobar"	)
   lowercase__			       =  {"x": 1, "y": "foobar"}
   assert asdict(__magic_name__	) == expected_output

   lowercase__			       =  {"a": {"b": A(x=10  , y="foo"	)}, "c": [A(x=20  , y="bar"	)]}
   lowercase__			       =  {"a": {"b": {"x": 10, "y": "foo"}}, "c": [{"x": 20, "y": "bar"}]}
   assert asdict(__magic_name__	) == expected_output

   with pytest.raises(__magic_name__	):
      asdict([1, A(x=10  , y="foo"	)]	)


def _A       (   __magic_name__	):
   return text.split()


def _A       (   __magic_name__	):
   yield (time.time(), content)
   time.sleep(2	)
   yield (time.time(), content)







def _A       (   ):
   with Pool(2	) as pool:
      lowercase__			       =  list(iflatmap_unordered(__magic_name__  , _split_text  , kwargs_iterable=[{"text": "hello there"}] * 10	)	)
      assert out.count("hello"	) == 10
      assert out.count("there"	) == 10
      assert len(__magic_name__	) == 20

   # check multiprocess from pathos (uses dill for pickling)
   with multiprocess.Pool(2	) as pool:
      lowercase__			       =  list(iflatmap_unordered(__magic_name__  , _split_text  , kwargs_iterable=[{"text": "hello there"}] * 10	)	)
      assert out.count("hello"	) == 10
      assert out.count("there"	) == 10
      assert len(__magic_name__	) == 20

   # check that we get items as fast as possible
   with Pool(2	) as pool:
      lowercase__			       =  []
      for yield_time, content in iflatmap_unordered(
          __magic_name__  , _aseconds_generator_of_aitems_with_timing  , kwargs_iterable=[{"content": "a"}, {"content": "b"}]	):
         assert yield_time < time.time() + 0.1, "we should each item directly after it was yielded"
         out.append(__magic_name__	)
      assert out.count("a"	) == 2
      assert out.count("b"	) == 2
      assert len(__magic_name__	) == 4






