





# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
					from PIL import Image


class     A     (_a       ):
			'''simple docstring'''




			__lowerCamelCase      :			List[Any]							     =       "Salesforce/blip-image-captioning-base"
			__lowerCamelCase      :			str							     =       (
			    "This is a tool that generates a description of an image. It takes an input named `image` which should be the "
			    "image to caption, and returns a text that contains the description in English."
			)
			__lowerCamelCase      :			List[Any]							     =       "image_captioner"
			__lowerCamelCase      :			List[Any]							     =       AutoModelForVisionaSeq

			__lowerCamelCase      :			str							     =       ["image"]
			__lowerCamelCase      :			Dict							     =       ["text"]






			def __init__(     self  :       List[Any]				,      *__lowerCAmelCase  :       List[Any]				,      **__lowerCAmelCase  :       Dict  )      ->      Optional[int]:







					"""simple docstring"""






					requires_backends(self				,      ["""vision"""]  )
					super().__init__(*__lowerCamelCase				,      **__lowerCamelCase  )






			def   a_			(     self  :       Tuple				,      __lowerCAmelCase  :       "Image"  )      ->      Union[str, Any]:







					"""simple docstring"""






					return self.pre_processor(images=__lowerCamelCase				,      return_tensors="""pt"""  )






			def   a_			(     self  :       int				,      __lowerCAmelCase  :       Union[str, Any]  )      ->      Optional[Any]:







					"""simple docstring"""






					return self.model.generate(**__lowerCamelCase  )







			def   a_			(     self  :       List[str]				,      __lowerCAmelCase  :       Dict  )      ->      str:







					"""simple docstring"""






					return self.pre_processor.batch_decode(__lowerCamelCase				,      skip_special_tokens=__lowerCamelCase  )[0].strip()









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


__magic_name__  :  List[Any]					=       logging.get_logger(__name__)
def 		a_							( __lowerCAmelCase   , __lowerCAmelCase				):
  lowerCAmelCase__										=      set()
  lowerCAmelCase__										=      []

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

  if from_gh:
    for filename in os.listdir(__lowerCAmelCase				):
      lowerCAmelCase__										=      os.path.join(__lowerCAmelCase   , __lowerCAmelCase				)
      if not os.path.isdir(__lowerCAmelCase				):
        # read the file
        if filename != "warnings.txt":
          continue
        with open(__lowerCAmelCase				) as fp:
          parse_line(__lowerCAmelCase				)
  else:
    try:
      with zipfile.ZipFile(__lowerCAmelCase				) as z:
        for filename in z.namelist():
          if not os.path.isdir(__lowerCAmelCase				):
            # read the file
            if filename != "warnings.txt":
              continue
            with z.open(__lowerCAmelCase				) as fp:
              parse_line(__lowerCAmelCase				)
    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_							( __lowerCAmelCase   , __lowerCAmelCase				):
  lowerCAmelCase__										=      set()

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

  return selected_warnings


if __name__ == "__main__":
      def 		a_							( __lowerCAmelCase				):
        return values.split(''','''				)

      __magic_name__  :  Optional[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.""",
      )

      __magic_name__  :  Optional[Any]					=       parser.parse_args()

      __magic_name__  :  Optional[int]					=       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
            __magic_name__  :  Optional[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
      __magic_name__  :  Optional[Any]					=       extract_warnings(args.output_dir, args.targets)
      __magic_name__  :  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)

