




"""simple docstring"""
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_				:    Tuple										=     logging.get_logger(__name__)

@add_end_docstrings(lowercase__				)
class __lowercase(      lowercase__				):




					'''simple docstring'''


					def __init__(    self						,	*__a						,	**__a     ):
								super().__init__(*__a						,	**__a     )
								self.check_model_type(__a     )
					def     snake_case_				(    self						,	__a=None						,	__a=None						,	__a=None						,	**__a     ):
								__lowerCamelCase					:	str	       =				{}, {}
								if padding is not None:
											__lowerCamelCase					:	List[str]	       =				padding
								if truncation is not None:
											__lowerCamelCase					:	str	       =				truncation
								if top_k is not None:
											__lowerCamelCase					:	str	       =				top_k
								return preprocess_params, {}, postprocess_params
					def __call__(    self						,	__a						,	__a = None						,	**__a     ):
								if isinstance(__a						,	(Image.Image, str)     ) and isinstance(__a						,	__a     ):
											__lowerCamelCase					:	Optional[Any]	       =				{'image': image, 'question': question}
								else:
											__lowerCamelCase					:	int	       =				image
								__lowerCamelCase					:	int	       =				super().__call__(__a						,	**__a     )
								return results
					def     snake_case_				(    self						,	__a						,	__a=False						,	__a=False     ):
								__lowerCamelCase					:	Optional[Any]	       =				load_image(inputs['image']     )
								__lowerCamelCase					:	str	       =				self.tokenizer(
								    inputs['question']						,	return_tensors=self.framework						,	padding=__a						,	truncation=__a     )
								__lowerCamelCase					:	str	       =				self.image_processor(images=__a						,	return_tensors=self.framework     )
								model_inputs.update(__a     )
								return model_inputs
					def     snake_case_				(    self						,	__a     ):
								__lowerCamelCase					:	str	       =				self.model(**__a     )
								return model_outputs





					def     snake_case_				(    self						,	__a						,	__a=5     ):
								if top_k > self.model.config.num_labels:
											__lowerCamelCase					:	Union[str, Any]	       =				self.model.config.num_labels

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

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









"""simple docstring"""
def 						UpperCAmelCase				(			A__:    int							,				A__:    list[int]							,				A__:    int     )  ->     int:

			def count_of_possible_combinations(A__:    int     ) -> int:
						if target < 0:
									return 0
						if target == 0:
									return 1
						return sum(count_of_possible_combinations(target - item     ) for item in array     )

			return count_of_possible_combinations(A__     )





def 						UpperCAmelCase				(			A__:    int							,				A__:    list[int]							,				A__:    int     )  ->     int:

			def count_of_possible_combinations_with_dp_array(
			    A__:    int							,				A__:    list[int]     ) -> int:
						if target < 0:
									return 0
						if target == 0:
									return 1
						if dp_array[target] != -1:
									return dp_array[target]
						__lowerCamelCase					:	Dict	       =				sum(
						    count_of_possible_combinations_with_dp_array(target - item							,				A__     )
						    for item in array     )
						__lowerCamelCase					:	str	       =				answer
						return answer

			__lowerCamelCase					:	Union[str, Any]	       =				[-1] * (target + 1)
			return count_of_possible_combinations_with_dp_array(A__							,				A__     )





def 						UpperCAmelCase				(			A__:    int							,				A__:    list[int]							,				A__:    int     )  ->     int:
			__lowerCamelCase					:	int	       =				[0] * (target + 1)
			__lowerCamelCase					:	str	       =				1

			for i in range(1							,				target + 1     ):
						for j in range(A__     ):
									if i - array[j] >= 0:
												dp_array[i] += dp_array[i - array[j]]

			return dp_array[target]


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					a_				:    Any										=     3
					a_				:    str										=     5
					a_				:    List[Any]										=     [1, 2, 5]
					print(combination_sum_iv(n, array, target))



