





"""simple docstring"""




import math

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase     :     Union[str, Any]							=	logging.get_logger(__name__)

UpperCAmelCase     :     Tuple							=	{
    """facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json""",
    # See all Data2VecAudio models at https://huggingface.co/models?filter=data2vec-audio
}







class     __lowerCAmelCase	(   UpperCamelCase__):
      _lowercase    : List[str]            =      """data2vec-audio"""







      def __init__(   self		,				lowerCAmelCase__=3_2		,				lowerCAmelCase__=7_6_8		,				lowerCAmelCase__=1_2		,				lowerCAmelCase__=1_2		,				lowerCAmelCase__=3_0_7_2		,				lowerCAmelCase__="gelu"		,				lowerCAmelCase__=0.1		,				lowerCAmelCase__=0.1		,				lowerCAmelCase__=0.1		,				lowerCAmelCase__=0.0		,				lowerCAmelCase__=0.1		,				lowerCAmelCase__=0.1		,				lowerCAmelCase__=0.02		,				lowerCAmelCase__=1E-5		,				lowerCAmelCase__="gelu"		,				lowerCAmelCase__=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2)		,				lowerCAmelCase__=(5, 2, 2, 2, 2, 2, 2)		,				lowerCAmelCase__=(1_0, 3, 3, 3, 3, 2, 2)		,				lowerCAmelCase__=False		,				lowerCAmelCase__=1_6		,				lowerCAmelCase__=1_9		,				lowerCAmelCase__=5		,				lowerCAmelCase__=0.05		,				lowerCAmelCase__=1_0		,				lowerCAmelCase__=2		,				lowerCAmelCase__=0.0		,				lowerCAmelCase__=1_0		,				lowerCAmelCase__=0		,				lowerCAmelCase__="sum"		,				lowerCAmelCase__=False		,				lowerCAmelCase__=False		,				lowerCAmelCase__=2_5_6		,				lowerCAmelCase__=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 1_5_0_0)		,				lowerCAmelCase__=(5, 3, 3, 1, 1)		,				lowerCAmelCase__=(1, 2, 3, 1, 1)		,				lowerCAmelCase__=5_1_2		,				lowerCAmelCase__=0		,				lowerCAmelCase__=1		,				lowerCAmelCase__=2		,				lowerCAmelCase__=False		,				lowerCAmelCase__=3		,				lowerCAmelCase__=2		,				lowerCAmelCase__=3		,				lowerCAmelCase__=None		,				**lowerCAmelCase__		,				)       ->						Any:



        '''simple docstring'''




        super().__init__(**lowerCAmelCase__		,				pad_token_id=lowerCAmelCase__		,				bos_token_id=lowerCAmelCase__		,				eos_token_id=lowerCAmelCase__							)
        a__     : Tuple  =hidden_size
        a__     : Tuple  =feat_extract_activation
        a__     : Optional[Any]  =list(lowerCAmelCase__							)
        a__     : Tuple  =list(lowerCAmelCase__							)
        a__     : Optional[Any]  =list(lowerCAmelCase__							)
        a__     : Dict  =conv_bias
        a__     : Tuple  =num_conv_pos_embeddings
        a__     : Optional[Any]  =num_conv_pos_embedding_groups
        a__     : Union[str, Any]  =conv_pos_kernel_size
        a__     : Any  =len(self.conv_dim							)
        a__     : Tuple  =num_hidden_layers
        a__     : Union[str, Any]  =intermediate_size
        a__     : Optional[Any]  =hidden_act
        a__     : Union[str, Any]  =num_attention_heads
        a__     : str  =hidden_dropout
        a__     : Optional[Any]  =attention_dropout
        a__     : List[str]  =activation_dropout
        a__     : Optional[Any]  =feat_proj_dropout
        a__     : Tuple  =final_dropout
        a__     : str  =layerdrop
        a__     : List[Any]  =layer_norm_eps
        a__     : Any  =initializer_range
        a__     : Any  =vocab_size
        a__     : Dict  =use_weighted_layer_sum

        if (
            (len(self.conv_stride							) != self.num_feat_extract_layers)
            or (len(self.conv_kernel							) != self.num_feat_extract_layers)
            or (len(self.conv_dim							) != self.num_feat_extract_layers)
        ):
          raise ValueError(
              "Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =="
              " `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ="
              F''' {len(self.conv_dim							)}`, `len(config.conv_stride) = {len(self.conv_stride							)}`,'''
              F''' `len(config.conv_kernel) = {len(self.conv_kernel							)}`.'''							)

        # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
        a__     : List[str]  =mask_time_prob
        a__     : Dict  =mask_time_length
        a__     : str  =mask_time_min_masks
        a__     : str  =mask_feature_prob
        a__     : int  =mask_feature_length
        a__     : Any  =mask_feature_min_masks

        # ctc loss
        a__     : Optional[int]  =ctc_loss_reduction
        a__     : List[str]  =ctc_zero_infinity

        # adapter
        a__     : Union[str, Any]  =add_adapter
        a__     : int  =adapter_kernel_size
        a__     : Any  =adapter_stride
        a__     : str  =num_adapter_layers
        a__     : List[Any]  =output_hidden_size or hidden_size

        # SequenceClassification-specific parameter. Feel free to ignore for other classes.
        a__     : List[str]  =classifier_proj_size

        # XVector-specific parameters. Feel free to ignore for other classes.
        a__     : Optional[Any]  =list(lowerCAmelCase__							)
        a__     : str  =list(lowerCAmelCase__							)
        a__     : int  =list(lowerCAmelCase__							)
        a__     : int  =xvector_output_dim







      @property
      def        _lowercase  (   self							)       ->						Optional[Any]:



        '''simple docstring'''




        return math.prod(self.conv_stride							)













import argparse
import json
import os
import time
import zipfile

from get_ci_error_statistics import download_artifact, get_artifacts_links

from transformers import logging


UpperCAmelCase     :     Union[str, Any]							=	logging.get_logger(__name__)
def 					_A	(		SCREAMING_SNAKE_CASE					:       Optional[int]	,	SCREAMING_SNAKE_CASE					:       List[Any]						):





  """simple docstring"""



  a__     : Tuple  =set()
  a__     : Optional[Any]  =[]

  def parse_line(SCREAMING_SNAKE_CASE					:       Optional[int]						):
    for line in fp:
      if isinstance(SCREAMING_SNAKE_CASE	,	SCREAMING_SNAKE_CASE						):
        a__     : str  =line.decode("UTF-8"						)
      if "warnings summary (final)" in line:
        continue
      # This means we are outside the body of a warning
      elif not line.startswith(" "						):
        # process a single warning and move it to `selected_warnings`.
        if len(SCREAMING_SNAKE_CASE						) > 0:
          a__     : Union[str, Any]  ="\n".join(SCREAMING_SNAKE_CASE						)
          # Only keep the warnings specified in `targets`
          if any(f''': {x}: ''' in warning for x in targets						):
            selected_warnings.add(SCREAMING_SNAKE_CASE						)
          buffer.clear()
        continue
      else:
        a__     : Optional[Any]  =line.strip()
        buffer.append(SCREAMING_SNAKE_CASE						)

  if from_gh:
    for filename in os.listdir(SCREAMING_SNAKE_CASE						):
      a__     : str  =os.path.join(SCREAMING_SNAKE_CASE	,	SCREAMING_SNAKE_CASE						)
      if not os.path.isdir(SCREAMING_SNAKE_CASE						):
        # read the file
        if filename != "warnings.txt":
          continue
        with open(SCREAMING_SNAKE_CASE						) as fp:
          parse_line(SCREAMING_SNAKE_CASE						)
  else:
    try:
      with zipfile.ZipFile(SCREAMING_SNAKE_CASE						) as z:
        for filename in z.namelist():
          if not os.path.isdir(SCREAMING_SNAKE_CASE						):
            # read the file
            if filename != "warnings.txt":
              continue
            with z.open(SCREAMING_SNAKE_CASE						) as fp:
              parse_line(SCREAMING_SNAKE_CASE						)
    except Exception:
      logger.warning(
          f'''{artifact_path} is either an invalid zip file or something else wrong. This file is skipped.'''						)

  return selected_warnings
def 					_A	(		SCREAMING_SNAKE_CASE					:       List[Any]	,	SCREAMING_SNAKE_CASE					:       Optional[Any]						):





  """simple docstring"""



  a__     : Optional[int]  =set()

  a__     : Any  =[os.path.join(SCREAMING_SNAKE_CASE	,	SCREAMING_SNAKE_CASE						) for p in os.listdir(SCREAMING_SNAKE_CASE						) if (p.endswith(".zip"						) or from_gh)]
  for p in paths:
    selected_warnings.update(extract_warnings_from_single_artifact(SCREAMING_SNAKE_CASE	,	SCREAMING_SNAKE_CASE						)						)

  return selected_warnings


if __name__ == "__main__":
     def 					_A	(		SCREAMING_SNAKE_CASE					:       Optional[int]						):





       """simple docstring"""



       return values.split(","						)

     UpperCAmelCase     :     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.""")
     # optional parameters
     parser.add_argument(
         """--targets""",
         default="""DeprecationWarning,UserWarning,FutureWarning""",
         type=list_str,
         help="""Comma-separated list of target warning(s) which we want to extract.""",
     )
     parser.add_argument(
         """--from_gh""",
         action="""store_true""",
         help="""If running from a GitHub action workflow and collecting warnings from its artifacts.""",
     )

     UpperCAmelCase     :     List[Any]							=	parser.parse_args()

     UpperCAmelCase     :     str							=	args.from_gh
     if from_gh:
          # The artifacts have to be downloaded using `actions/download-artifact@v3`
          pass
     else:
          os.makedirs(args.output_dir, exist_ok=True)

          # get download links
          UpperCAmelCase     :     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)

          # download artifacts
          for idx, (name, url) in enumerate(artifacts.items()):
               print(name)
               print(url)
               print("""=""" * 80)
               download_artifact(name, url, args.output_dir, args.token)
               # Be gentle to GitHub
               time.sleep(1)

    # extract warnings from artifacts
     UpperCAmelCase     :     Tuple							=	extract_warnings(args.output_dir, args.targets)
     UpperCAmelCase     :     Optional[Any]							=	sorted(selected_warnings)
     with open(os.path.join(args.output_dir, """selected_warnings.json"""), """w""", encoding="""UTF-8""") as fp:
          json.dump(selected_warnings, fp, ensure_ascii=False, indent=4)






