






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

__a   :							List[str]						= logging.get_logger(__name__)


@add_end_docstrings(lowercase_	)
class    __lowercase   (						lowercase_	):







     '''simple docstring'''




     def __init__(					self							:      Tuple			,						*UpperCamelCase_							:      Any			,						**UpperCamelCase_							:      List[Any]					):


         """simple docstring"""



         super().__init__(*UpperCamelCase_			,						**UpperCamelCase_					)
         self.check_model_type(UpperCamelCase_					)




     def 		lowerCAmelCase_  (					self							:      Optional[Any]			,						UpperCamelCase_							:      List[Any]=None			,						UpperCamelCase_							:      Optional[int]=None			,						UpperCamelCase_							:      Union[str, Any]=None			,						**UpperCamelCase_							:      int					):


         """simple docstring"""



         __A     ,						__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							:      str			,						UpperCamelCase_							:      Union["Image.Image", str]			,						UpperCamelCase_							:      str = None			,						**UpperCamelCase_							:      List[Any]					):


         """simple docstring"""



         if isinstance(UpperCamelCase_			,						(Image.Image, str)					) and isinstance(UpperCamelCase_			,						UpperCamelCase_					):
             __A       =						{"""image""": image, """question""": question}
         else:
             __A       =						image
         __A       =						super().__call__(UpperCamelCase_			,						**UpperCamelCase_					)
         return results




     def 		lowerCAmelCase_  (					self							:      Union[str, Any]			,						UpperCamelCase_							:      str			,						UpperCamelCase_							:      Union[str, Any]=False			,						UpperCamelCase_							:      Dict=False					):


         """simple docstring"""



         __A       =						load_image(inputs["""image"""]					)
         __A       =						self.tokenizer(
             inputs["""question"""]			,						return_tensors=self.framework			,						padding=UpperCamelCase_			,						truncation=UpperCamelCase_					)
         __A       =						self.image_processor(images=UpperCamelCase_			,						return_tensors=self.framework					)
         model_inputs.update(UpperCamelCase_					)
         return model_inputs




     def 		lowerCAmelCase_  (					self							:      Tuple			,						UpperCamelCase_							:      Optional[Any]					):


         """simple docstring"""



         __A       =						self.model(**UpperCamelCase_					)
         return model_outputs





     def 		lowerCAmelCase_  (					self							:      Dict			,						UpperCamelCase_							:      Any			,						UpperCamelCase_							:      Tuple=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     ,						__A       =						probs.topk(UpperCamelCase_					)
         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(UpperCamelCase_			,						UpperCamelCase_					)]












from __future__ import annotations

from typing import Generic, TypeVar

__a   :							str						= TypeVar("T")


class    __lowercase   (						Generic[T]	):







     '''simple docstring'''




     def __init__(					self							:      Any			,						UpperCamelCase_							:      T					):


         """simple docstring"""



         __A       =						data
         __A       =						self
         __A       =						0


class    __lowercase   (						Generic[T]	):







     '''simple docstring'''




     def __init__(					self							:      Optional[Any]					):


         """simple docstring"""



         __A       =						{}




     def 		lowerCAmelCase_  (					self							:      Union[str, Any]			,						UpperCamelCase_							:      T					):


         """simple docstring"""



         __A       =						DisjointSetTreeNode(UpperCamelCase_					)




     def 		lowerCAmelCase_  (					self							:      List[Any]			,						UpperCamelCase_							:      T					):


         """simple docstring"""



         __A       =						self.map[data]
         if elem_ref != elem_ref.parent:
             __A       =						self.find_set(elem_ref.parent.data					)
         return elem_ref.parent




     def 		lowerCAmelCase_  (					self							:      int			,						UpperCamelCase_							:      DisjointSetTreeNode[T]			,						UpperCamelCase_							:      DisjointSetTreeNode[T]					):


         """simple docstring"""



         if nodea.rank > nodea.rank:
             __A       =						nodea
         else:
             __A       =						nodea
             if nodea.rank == nodea.rank:
                 nodea.rank += 1





     def 		lowerCAmelCase_  (					self							:      Tuple			,						UpperCamelCase_							:      T			,						UpperCamelCase_							:      T					):


         """simple docstring"""



         self.link(self.find_set(UpperCamelCase_					)			,						self.find_set(UpperCamelCase_					)					)


class    __lowercase   (						Generic[T]	):







     '''simple docstring'''




     def __init__(					self							:      Optional[int]					):


         """simple docstring"""



         __A       =						{}




     def 		lowerCAmelCase_  (					self							:      int			,						UpperCamelCase_							:      T					):


         """simple docstring"""



         if node not in self.connections:
             __A       =						{}




     def 		lowerCAmelCase_  (					self							:      Dict			,						UpperCamelCase_							:      T			,						UpperCamelCase_							:      T			,						UpperCamelCase_							:      int					):


         """simple docstring"""



         self.add_node(UpperCamelCase_					)
         self.add_node(UpperCamelCase_					)
         __A       =						weight
         __A       =						weight





     def 		lowerCAmelCase_  (					self							:      Dict					):


         """simple docstring"""



         __A       =						[]
         __A       =						set()
         for start in self.connections:
             for end in self.connections[start]:
                 if (start, end) not in seen:
                     seen.add((end, start)					)
                     edges.append((start, end, self.connections[start][end])					)
         edges.sort(key=lambda UpperCamelCase_					: x[2]					)

         # creating the disjoint set
         __A       =						DisjointSetTree[T]()
         for node in self.connections:
             disjoint_set.make_set(UpperCamelCase_					)

         # MST generation
         __A       =						0
         __A       =						0
         __A       =						GraphUndirectedWeighted[T]()
         while num_edges < len(self.connections					) - 1:
             __A     ,						__A     ,						__A       =						edges[index]
             index += 1
             __A       =						disjoint_set.find_set(UpperCamelCase_					)
             __A       =						disjoint_set.find_set(UpperCamelCase_					)
             if parent_u != parent_v:
                 num_edges += 1
                 graph.add_edge(UpperCamelCase_			,						UpperCamelCase_			,						UpperCamelCase_					)
                 disjoint_set.union(UpperCamelCase_			,						UpperCamelCase_					)
         return graph




