
"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


SCREAMING_SNAKE_CASE_            =    {
    """configuration_blip""": [
        """BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BlipConfig""",
        """BlipTextConfig""",
        """BlipVisionConfig""",
    ],
    """processing_blip""": ["""BlipProcessor"""],
}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE_            =    ["""BlipImageProcessor"""]


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE_            =    [
       """BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """BlipModel""",
       """BlipPreTrainedModel""",
       """BlipForConditionalGeneration""",
       """BlipForQuestionAnswering""",
       """BlipVisionModel""",
       """BlipTextModel""",
       """BlipForImageTextRetrieval""",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE_            =    [
       """TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """TFBlipModel""",
       """TFBlipPreTrainedModel""",
       """TFBlipForConditionalGeneration""",
       """TFBlipForQuestionAnswering""",
       """TFBlipVisionModel""",
       """TFBlipTextModel""",
       """TFBlipForImageTextRetrieval""",
   ]

if TYPE_CHECKING:
   from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
   from .processing_blip import BlipProcessor

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .image_processing_blip import BlipImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_blip import (
          BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
          BlipForConditionalGeneration,
          BlipForImageTextRetrieval,
          BlipForQuestionAnswering,
          BlipModel,
          BlipPreTrainedModel,
          BlipTextModel,
          BlipVisionModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_blip import (
          TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFBlipForConditionalGeneration,
          TFBlipForImageTextRetrieval,
          TFBlipForQuestionAnswering,
          TFBlipModel,
          TFBlipPreTrainedModel,
          TFBlipTextModel,
          TFBlipVisionModel,
      )

else:
   import sys

   SCREAMING_SNAKE_CASE_            =    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)









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


_lowerCamelCase      :						int							=  logging.get_logger(__name__)







def SCREAMING_SNAKE_CASE							(			lowercase_					,							lowercase_		)  ->			Dict:



       """simple docstring"""

       A__ 					=       set()
       A__ 					=       []

       def parse_line(lowercase_		):
              for line in fp:
                     if isinstance(lowercase_					,							lowercase_		):
                            A__ 					=       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(lowercase_		) > 0:
                                   A__ 					=       '''\n'''.join(lowercase_		)
                                   # Only keep the warnings specified in `targets`
                                   if any(f""": {x}: """ in warning for x in targets		):
                                          selected_warnings.add(lowercase_		)
                                   buffer.clear()
                            continue
                     else:
                            A__ 					=       line.strip()
                            buffer.append(lowercase_		)

       if from_gh:
              for filename in os.listdir(lowercase_		):
                     A__ 					=       os.path.join(lowercase_					,							lowercase_		)
                     if not os.path.isdir(lowercase_		):
                            # read the file
                            if filename != "warnings.txt":
                                   continue
                            with open(lowercase_		) as fp:
                                   parse_line(lowercase_		)
       else:
              try:
                     with zipfile.ZipFile(lowercase_		) as z:
                            for filename in z.namelist():
                                   if not os.path.isdir(lowercase_		):
                                          # read the file
                                          if filename != "warnings.txt":
                                                 continue
                                          with z.open(lowercase_		) as fp:
                                                 parse_line(lowercase_		)
              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 SCREAMING_SNAKE_CASE							(			lowercase_					,							lowercase_		)  ->			str:



       """simple docstring"""

       A__ 					=       set()

       A__ 					=       [os.path.join(lowercase_					,							lowercase_		) for p in os.listdir(lowercase_		) if (p.endswith('''.zip'''		) or from_gh)]
       for p in paths:
              selected_warnings.update(extract_warnings_from_single_artifact(lowercase_					,							lowercase_		)		)

       return selected_warnings


if __name__ == "__main__":







  def SCREAMING_SNAKE_CASE							(			lowercase_		)  ->			int:



         """simple docstring"""

         return values.split(''','''		)

  _lowerCamelCase      :						int							=  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.""",
  )

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

  _lowerCamelCase      :						List[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
    _lowerCamelCase      :						Any							=  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
  _lowerCamelCase      :						Any							=  extract_warnings(args.output_dir, args.targets)
  _lowerCamelCase      :						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)


