
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

lowercase  :					Union[str, Any]													=       logging.get_logger(__name__)




@add_end_docstrings(__lowercase)
class  lowerCamelCase__							(				__lowercase):




	'''simple docstring'''




	def __init__(					self		:Tuple     ,   *a		:int     ,   **a		:Any						)		-> int:
								super().__init__(*a     ,   **a						)
								self.check_model_type(a						)







	def    _lowerCamelCase				(					self		:Union[str, Any]     ,   a		:Dict=None     ,   a		:Dict=None     ,   a		:Union[str, Any]=None     ,   **a		:List[Any]						)		-> List[Any]:
								__UpperCamelCase   ,						__UpperCamelCase	:   List[str]			   =					{}, {}
								if padding is not None:
															__UpperCamelCase	:   Tuple			   =					padding
								if truncation is not None:
															__UpperCamelCase	:   str			   =					truncation
								if top_k is not None:
															__UpperCamelCase	:   int			   =					top_k
								return preprocess_params, {}, postprocess_params







	def __call__(					self		:int     ,   a		:Union["Image.Image", str]     ,   a		:str = None     ,   **a		:Any						)		-> int:
								if isinstance(a     ,   (Image.Image, str)						) and isinstance(a     ,   a						):
															__UpperCamelCase	:   Tuple			   =					{"image": image, "question": question}
								else:
															__UpperCamelCase	:   Dict			   =					image
								__UpperCamelCase	:   Union[str, Any]			   =					super().__call__(a     ,   **a						)
								return results







	def    _lowerCamelCase				(					self		:Optional[Any]     ,   a		:Optional[int]     ,   a		:Dict=False     ,   a		:Optional[int]=False						)		-> int:
								__UpperCamelCase	:   Optional[Any]			   =					load_image(inputs["image"]						)
								__UpperCamelCase	:   Dict			   =					self.tokenizer(
								    inputs["question"]     ,   return_tensors=self.framework     ,   padding=a     ,   truncation=a						)
								__UpperCamelCase	:   List[Any]			   =					self.image_processor(images=a     ,   return_tensors=self.framework						)
								model_inputs.update(a						)
								return model_inputs







	def    _lowerCamelCase				(					self		:List[str]     ,   a		:List[Any]						)		-> Optional[Any]:
								__UpperCamelCase	:   List[str]			   =					self.model(**a						)
								return model_outputs







	def    _lowerCamelCase				(					self		:List[Any]     ,   a		:List[str]     ,   a		:str=5						)		-> Any:
								if top_k > self.model.config.num_labels:
															__UpperCamelCase	:   Any			   =					self.model.config.num_labels

								if self.framework == "pt":
															__UpperCamelCase	:   Tuple			   =					model_outputs.logits.sigmoid()[0]
															__UpperCamelCase   ,						__UpperCamelCase	:   List[Any]			   =					probs.topk(a						)
								else:
															raise ValueError(f'Unsupported framework: {self.framework}'						)

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

from __future__ import annotations

import sys
from collections import deque
from typing import Generic, TypeVar

lowercase  :					Optional[Any]													=       TypeVar('T')




class  lowerCamelCase__							(				Generic[T]):




	'''simple docstring'''




	_A								=     42  # Cache store of keys
	_A								=     42  # References of the keys in cache
	_A								=     1_0  # Maximum capacity of cache







	def __init__(					self		:Optional[Any]     ,   a		:int						)		-> None:
								__UpperCamelCase	:   Union[str, Any]			   =					deque()
								__UpperCamelCase	:   str			   =					set()
								if not n:
															__UpperCamelCase	:   Union[str, Any]			   =					sys.maxsize
								elif n < 0:
															raise ValueError("n should be an integer greater than 0."						)
								else:
															__UpperCamelCase	:   Any			   =					n







	def    _lowerCamelCase				(					self		:Tuple     ,   a		:T						)		-> None:
								if x not in self.key_reference:
															if len(self.dq_store						) == LRUCache._MAX_CAPACITY:
																						__UpperCamelCase	:   int			   =					self.dq_store.pop()
																						self.key_reference.remove(a						)
								else:
															self.dq_store.remove(a						)

								self.dq_store.appendleft(a						)
								self.key_reference.add(a						)







	def    _lowerCamelCase				(					self		:Any						)		-> None:
								for k in self.dq_store:
															print(a						)







	def __repr__(					self		:Tuple						)		-> str:
								return f'LRUCache({self._MAX_CAPACITY}) => {list(self.dq_store						)}'


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		lowercase  :					LRUCache[str | int]													=       LRUCache(4)
		lru_cache.refer('A')
		lru_cache.refer(2)
		lru_cache.refer(3)
		lru_cache.refer('A')
		lru_cache.refer(4)
		lru_cache.refer(5)
		lru_cache.display()

		print(lru_cache)
		assert str(lru_cache) == "LRUCache(4) => [5, 4, 'A', 3]"