






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

import requests





def  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase=None       ) ->			str:

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

     UpperCAmelCase__      :  Dict				      =			F"https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"
     UpperCAmelCase__      :  List[str]				      =			requests.get(__lowerCamelCase ,							headers=__lowerCamelCase       ).json()
     UpperCAmelCase__      :  str				      =			{}

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

          for i in range(__lowerCamelCase       ):
               UpperCAmelCase__      :  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  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase=None       ) ->			List[Any]:

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

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

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

          for i in range(__lowerCamelCase       ):
               UpperCAmelCase__      :  str				      =			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  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase       ) ->			Union[str, Any]:

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

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





def  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase=None       ) ->			Optional[Any]:

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

     UpperCAmelCase__      :  Union[str, Any]				      =			None
     if job_name and job_links:
          UpperCAmelCase__      :  Optional[Any]				      =			job_links.get(__lowerCamelCase ,							__lowerCamelCase       )

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

     return result





def  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase=None       ) ->			List[str]:

     '''simple docstring'''
     UpperCAmelCase__      :  List[Any]				      =			[]

     UpperCAmelCase__      :  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  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase=None       ) ->			List[str]:

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

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





def  _lowerCamelCase						(						__lowerCamelCase       ) ->			Tuple:

     '''simple docstring'''
     UpperCAmelCase__      :  List[Any]				      =			test.split("""::"""       )[0]
     if test.startswith("""tests/models/"""       ):
          UpperCAmelCase__      :  Optional[Any]				      =			test.split("""/"""       )[2]
     else:
          UpperCAmelCase__      :  List[Any]				      =			None

     return test





def  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase=None       ) ->			Optional[int]:

     '''simple docstring'''
     UpperCAmelCase__      :  Tuple				      =			[(x[0], x[1], get_model(x[2]       )) for x in logs]
     UpperCAmelCase__      :  List[Any]				      =			[x for x in logs if x[2] is not None]
     UpperCAmelCase__      :  int				      =			{x[2] for x in logs}

     UpperCAmelCase__      :  str				      =			{}
     for test in tests:
          UpperCAmelCase__      :  Optional[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__      :  Optional[int]				      =			{error: count for error, count in counts if (error_filter is None or error not in error_filter)}
          UpperCAmelCase__      :  str				      =			sum(error_counts.values()       )
          if n_errors > 0:
               UpperCAmelCase__      :  Tuple				      =			{"""count""": n_errors, """errors""": error_counts}

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





def  _lowerCamelCase						(						__lowerCamelCase       ) ->			Optional[int]:

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

     return "\n".join(__lowerCamelCase       )





def  _lowerCamelCase						(						__lowerCamelCase       ) ->			int:

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

     return "\n".join(__lowerCamelCase       )


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE__		:							Dict 				=				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.""")
      SCREAMING_SNAKE_CASE__		:							Optional[int] 				=				parser.parse_args()

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

      SCREAMING_SNAKE_CASE__		:							List[str] 				=				get_job_links(args.workflow_run_id, token=args.token)
      SCREAMING_SNAKE_CASE__		:							Optional[int] 				=				{}
      # 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:
                        SCREAMING_SNAKE_CASE__		:							Tuple 				=				k.find(""" / """)
                        SCREAMING_SNAKE_CASE__		:							Optional[int] 				=				k[index + len(""" / """) :]
                  SCREAMING_SNAKE_CASE__		:							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)

      SCREAMING_SNAKE_CASE__		:							Dict 				=				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)

      SCREAMING_SNAKE_CASE__		:							str 				=				get_all_errors(args.output_dir, job_links=job_links)

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

      # print the top 30 most common test errors
      SCREAMING_SNAKE_CASE__		:							int 				=				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)

      SCREAMING_SNAKE_CASE__		:							Union[str, Any] 				=				reduce_by_error(errors)
      SCREAMING_SNAKE_CASE__		:							Dict 				=				reduce_by_model(errors)

      SCREAMING_SNAKE_CASE__		:							int 				=				make_github_table(reduced_by_error)
      SCREAMING_SNAKE_CASE__		:							Union[str, 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)









from collections import OrderedDict
from typing import Any, List, Mapping, Optional

from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging


lowercase_   							=  logging.get_logger(__name__)

lowercase_   							=  {
    'EleutherAI/gpt-j-6B': 'https://huggingface.co/EleutherAI/gpt-j-6B/resolve/main/config.json',
    # See all GPT-J models at https://huggingface.co/models?filter=gpt_j
}





class 					__lowerCAmelCase	(   SCREAMING_SNAKE_CASE				):
  _a		     =    """gptj"""
  _a		     =    {
      """max_position_embeddings""": """n_positions""",
      """hidden_size""": """n_embd""",
      """num_attention_heads""": """n_head""",
      """num_hidden_layers""": """n_layer""",
  }




  def __init__(							self				,  lowerCAmelCase=50_400				,  lowerCAmelCase=2_048				,  lowerCAmelCase=4_096				,  lowerCAmelCase=28				,  lowerCAmelCase=16				,  lowerCAmelCase=64				,  lowerCAmelCase=None				,  lowerCAmelCase="gelu_new"				,  lowerCAmelCase=0.0				,  lowerCAmelCase=0.0				,  lowerCAmelCase=0.0				,  lowerCAmelCase=1e-5				,  lowerCAmelCase=0.02				,  lowerCAmelCase=True				,  lowerCAmelCase=50_256				,  lowerCAmelCase=50_256				,  lowerCAmelCase=False				,  **lowerCAmelCase				,  )    ->					Optional[Any]:
        '''simple docstring'''






        _lowercase      			=vocab_size
        _lowercase      			=n_positions
        _lowercase      			=n_embd
        _lowercase      			=n_layer
        _lowercase      			=n_head
        _lowercase      			=n_inner
        _lowercase      			=rotary_dim
        _lowercase      			=activation_function
        _lowercase      			=resid_pdrop
        _lowercase      			=embd_pdrop
        _lowercase      			=attn_pdrop
        _lowercase      			=layer_norm_epsilon
        _lowercase      			=initializer_range
        _lowercase      			=use_cache

        _lowercase      			=bos_token_id
        _lowercase      			=eos_token_id

        super().__init__(
            bos_token_id=lowerCAmelCase				,  eos_token_id=lowerCAmelCase				,  tie_word_embeddings=lowerCAmelCase				,  **lowerCAmelCase   )





class 					__lowerCAmelCase	(   SCREAMING_SNAKE_CASE				):




  def __init__(							self				,  lowerCAmelCase				,  lowerCAmelCase = "default"				,  lowerCAmelCase = None				,  lowerCAmelCase = False				,  )    ->					Optional[int]:
        '''simple docstring'''






        super().__init__(lowerCAmelCase				,  task=lowerCAmelCase				,  patching_specs=lowerCAmelCase				,  use_past=lowerCAmelCase   )
        if not getattr(self._config				,  'pad_token_id'				,  lowerCAmelCase   ):
              # TODO: how to do that better?
              _lowercase      			=0




  @property
  def     A__	(							self   )    ->					Mapping[str, Mapping[int, str]]:
        '''simple docstring'''






        _lowercase      			=OrderedDict({'input_ids': {0: 'batch', 1: 'sequence'}}   )
        if self.use_past:
              self.fill_with_past_key_values_(lowerCAmelCase				,  direction='inputs'   )
              _lowercase      			={0: 'batch', 1: 'past_sequence + sequence'}
        else:
              _lowercase      			={0: 'batch', 1: 'sequence'}

        return common_inputs




  @property
  def     A__	(							self   )    ->					int:
        '''simple docstring'''






        return self._config.n_layer




  @property
  def     A__	(							self   )    ->					int:
        '''simple docstring'''






        return self._config.n_head




  def     A__	(							self				,  lowerCAmelCase				,  lowerCAmelCase = -1				,  lowerCAmelCase = -1				,  lowerCAmelCase = False				,  lowerCAmelCase = None				,  )    ->					Mapping[str, Any]:
        '''simple docstring'''






        _lowercase      			=super(lowerCAmelCase				,  self   ).generate_dummy_inputs(
            lowerCAmelCase				,  batch_size=lowerCAmelCase				,  seq_length=lowerCAmelCase				,  is_pair=lowerCAmelCase				,  framework=lowerCAmelCase   )

        # We need to order the input in the way they appears in the forward()
        _lowercase      			=OrderedDict({'input_ids': common_inputs['input_ids']}   )

        # Need to add the past_keys
        if self.use_past:
              if not is_torch_available():
                    raise ValueError('Cannot generate dummy past_keys inputs without PyTorch installed.'   )
              else:
                    import torch

                    _lowercase			,			_lowercase      			=common_inputs['input_ids'].shape
                    # Not using the same length for past_key_values
                    _lowercase      			=seqlen + 2
                    _lowercase      			=(
                        batch,
                        self.num_attention_heads,
                        past_key_values_length,
                        self._config.hidden_size // self.num_attention_heads,
                    )
                    _lowercase      			=[
                        (torch.zeros(lowerCAmelCase   ), torch.zeros(lowerCAmelCase   )) for _ in range(self.num_layers   )
                    ]

        _lowercase      			=common_inputs['attention_mask']
        if self.use_past:
              _lowercase      			=ordered_inputs['attention_mask'].dtype
              _lowercase      			=torch.cat(
                  [ordered_inputs['attention_mask'], torch.ones(lowerCAmelCase				,  lowerCAmelCase				,  dtype=lowerCAmelCase   )]				,  dim=1   )

        return ordered_inputs




  @property
  def     A__	(							self   )    ->					int:
        '''simple docstring'''






        return 13


