




from typing import Union

from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
		from PIL import Image

		from ..image_utils import load_image

if is_torch_available():
		from ..models.auto.modeling_auto import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING

__UpperCamelCase   :			str          = logging.get_logger(__name__)

@add_end_docstrings(SCREAMING_SNAKE_CASE__					)
class 						__lowerCAmelCase      (      SCREAMING_SNAKE_CASE__					):
							def __init__(		self		:Any						, *__magic_name__		:Any						, **__magic_name__		:Union[str, Any]							):







								'''simple docstring'''







								super().__init__(*_lowercase						, **_lowercase							)
								self.check_model_type(_lowercase							)
							def  lowerCamelCase__				(		self		:List[str]						, __magic_name__		:Tuple=None						, __magic_name__		:str=None						, __magic_name__		:Optional[Any]=None						, **__magic_name__		:List[str]							):







								'''simple docstring'''







								a									=				{}, {}
								if padding is not None:
									a									=				padding
								if truncation is not None:
									a									=				truncation
								if top_k is not None:
									a									=				top_k
								return preprocess_params, {}, postprocess_params
							def __call__(		self		:Optional[int]						, __magic_name__		:Union["Image.Image", str]						, __magic_name__		:str = None						, **__magic_name__		:Optional[Any]							):







								'''simple docstring'''







								if isinstance(_lowercase						, (Image.Image, str)							) and isinstance(_lowercase						, _lowercase							):
									a									=				{"image": image, "question": question}
								else:
									a									=				image
								a									=				super().__call__(_lowercase						, **_lowercase							)
								return results
							def  lowerCamelCase__				(		self		:Union[str, Any]						, __magic_name__		:Optional[Any]						, __magic_name__		:List[str]=False						, __magic_name__		:List[Any]=False							):







								'''simple docstring'''







								a									=				load_image(inputs["""image"""]							)
								a									=				self.tokenizer(
								    inputs["""question"""]						, return_tensors=self.framework						, padding=_lowercase						, truncation=_lowercase							)
								a									=				self.image_processor(images=_lowercase						, return_tensors=self.framework							)
								model_inputs.update(_lowercase							)
								return model_inputs
							def  lowerCamelCase__				(		self		:Union[str, Any]						, __magic_name__		:Optional[int]							):







								'''simple docstring'''







								a									=				self.model(**_lowercase							)
								return model_outputs





							def  lowerCamelCase__				(		self		:Dict						, __magic_name__		:Tuple						, __magic_name__		:int=5							):







								'''simple docstring'''







								if top_k > self.model.config.num_labels:
									a									=				self.model.config.num_labels

								if self.framework == "pt":
									a									=				model_outputs.logits.sigmoid()[0]
									a									=				probs.topk(_lowercase							)
								else:
									raise ValueError(F'Unsupported framework: {self.framework}'							)

								a									=				scores.tolist()
								a									=				ids.tolist()
								return [{"score": score, "answer": self.model.config.idalabel[_id]} for score, _id in zip(_lowercase						, _lowercase							)]






"""simple docstring"""







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


A		=						logging.get_logger(__name__)

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							Optional[int]     ,		lowerCamelCase_:							List[Any] ):
						"""simple docstring"""






						snake_case   :			Optional[Any]						    = set()
						snake_case   :			Optional[int]						    = []

						def parse_line(lowerCamelCase_:							Union[str, Any] ):
												for line in fp:
																		if isinstance(lowerCamelCase_     ,		lowerCamelCase_ ):
																								snake_case   :			Optional[Any]						    = 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:
																														snake_case   :			str						    = "\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:
																								snake_case   :			Dict						    = line.strip()
																								buffer.append(lowerCamelCase_ )

						if from_gh:
												for filename in os.listdir(lowerCamelCase_ ):
																		snake_case   :			Tuple						    = 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  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							Union[str, Any]     ,		lowerCamelCase_:							Any ):
						"""simple docstring"""






						snake_case   :			Dict						    = set()

						snake_case   :			str						    = [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  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							Dict ):
									"""simple docstring"""






									return values.split("," )

			A		=						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.',
			)

			A		=						parser.parse_args()

			A		=						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
						A		=						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('=' * 8_0)
									download_artifact(name, url, args.output_dir, args.token)
									# Be gentle to GitHub
									time.sleep(1)

    # extract warnings from artifacts
			A		=						extract_warnings(args.output_dir, args.targets)
			A		=						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)



