

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


__UpperCAmelCase								=			logging.get_logger(__name__)

__UpperCAmelCase								=			{
    """microsoft/swinv2-tiny-patch4-window8-256""": (
        """https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"""
    ),
}



class SCREAMING_SNAKE_CASE     (  a_			):
  """simple docstring"""






  lowerCamelCase   :      Optional[int]										="swinv2"

  lowerCamelCase   :      Dict										={
      "num_attention_heads": "num_heads",
      "num_hidden_layers": "num_layers",
  }







  def __init__(      self			:   Dict	,							lowerCAmelCase			:   str=2_24	,							lowerCAmelCase			:   List[str]=4	,							lowerCAmelCase			:   Optional[int]=3	,							lowerCAmelCase			:   str=96	,							lowerCAmelCase			:   str=[2, 2, 6, 2]	,							lowerCAmelCase			:   Optional[int]=[3, 6, 12, 24]	,							lowerCAmelCase			:   List[Any]=7	,							lowerCAmelCase			:   Optional[int]=4.0	,							lowerCAmelCase			:   List[Any]=True	,							lowerCAmelCase			:   Dict=0.0	,							lowerCAmelCase			:   List[Any]=0.0	,							lowerCAmelCase			:   Union[str, Any]=0.1	,							lowerCAmelCase			:   Tuple="gelu"	,							lowerCAmelCase			:   str=False	,							lowerCAmelCase			:   Optional[int]=0.02	,							lowerCAmelCase			:   Union[str, Any]=1e-5	,							lowerCAmelCase			:   int=32	,							**lowerCAmelCase			:   str	,							)							->     List[Any]:






     """simple docstring"""







     super().__init__(**lowerCAmelCase   )

     __lowerCAmelCase  :      Optional[int]    =						image_size
     __lowerCAmelCase  :      Tuple    =						patch_size
     __lowerCAmelCase  :      Any    =						num_channels
     __lowerCAmelCase  :      List[Any]    =						embed_dim
     __lowerCAmelCase  :      Tuple    =						depths
     __lowerCAmelCase  :      Optional[int]    =						len(lowerCAmelCase   )
     __lowerCAmelCase  :      Dict    =						num_heads
     __lowerCAmelCase  :      Dict    =						window_size
     __lowerCAmelCase  :      Union[str, Any]    =						mlp_ratio
     __lowerCAmelCase  :      Tuple    =						qkv_bias
     __lowerCAmelCase  :      List[Any]    =						hidden_dropout_prob
     __lowerCAmelCase  :      int    =						attention_probs_dropout_prob
     __lowerCAmelCase  :      List[Any]    =						drop_path_rate
     __lowerCAmelCase  :      Any    =						hidden_act
     __lowerCAmelCase  :      Any    =						use_absolute_embeddings
     __lowerCAmelCase  :      List[Any]    =						layer_norm_eps
     __lowerCAmelCase  :      Any    =						initializer_range
     __lowerCAmelCase  :      Union[str, Any]    =						encoder_stride
     # we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
     # this indicates the channel dimension after the last stage of the model
     __lowerCAmelCase  :      Optional[Any]    =						int(embed_dim * 2 ** (len(lowerCAmelCase   ) - 1)   )
     __lowerCAmelCase  :      int    =						(0, 0, 0, 0)





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								=			logging.get_logger(__name__)





def      snake_case_				(__A					:						List[str] ,       __A					:						str					)      ->     int:
   __lowerCAmelCase  :      str    =						set()
   __lowerCAmelCase  :      int    =						[]

   def parse_line(__A					:						List[Any]					):
      for line in fp:
         if isinstance(__A ,       __A					):
            __lowerCAmelCase  :      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(__A					) > 0:
               __lowerCAmelCase  :      Tuple    =						"""\n""".join(__A					)
               # Only keep the warnings specified in `targets`
               if any(f''': {x}: ''' in warning for x in targets					):
                  selected_warnings.add(__A					)
               buffer.clear()
            continue
         else:
            __lowerCAmelCase  :      Optional[int]    =						line.strip()
            buffer.append(__A					)

   if from_gh:
      for filename in os.listdir(__A					):
         __lowerCAmelCase  :      Optional[Any]    =						os.path.join(__A ,       __A					)
         if not os.path.isdir(__A					):
            # read the file
            if filename != "warnings.txt":
               continue
            with open(__A					) as fp:
               parse_line(__A					)
   else:
      try:
         with zipfile.ZipFile(__A					) as z:
            for filename in z.namelist():
               if not os.path.isdir(__A					):
                  # read the file
                  if filename != "warnings.txt":
                     continue
                  with z.open(__A					) as fp:
                     parse_line(__A					)
      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      snake_case_				(__A					:						Dict ,       __A					:						Union[str, Any]					)      ->     Dict:
   __lowerCAmelCase  :      Any    =						set()

   __lowerCAmelCase  :      Optional[int]    =						[os.path.join(__A ,       __A					) for p in os.listdir(__A					) if (p.endswith(""".zip"""					) or from_gh)]
   for p in paths:
      selected_warnings.update(extract_warnings_from_single_artifact(__A ,       __A					)					)

   return selected_warnings


if __name__ == "__main__":





   def      snake_case_				(__A					:						int					)      ->     Tuple:
      return values.split(""","""					)

   __UpperCAmelCase								=			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								=			parser.parse_args()

   __UpperCAmelCase								=			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								=			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								=			extract_warnings(args.output_dir, args.targets)
   __UpperCAmelCase								=			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)


