


from __future__ import annotations

from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray






def 					UpperCamelCase   (      __magic_name__	:				float       ,       __magic_name__	:				float       ,       __magic_name__	:				bool = False	)  ->    list[float]:
		"""simple docstring"""




		if radian_mode:
				return [magnitude * cos(__magic_name__	), magnitude * sin(__magic_name__	)]
		return [magnitude * cos(radians(__magic_name__	)	), magnitude * sin(radians(__magic_name__	)	)]






def 					UpperCamelCase   (      __magic_name__	:				NDArray[floataa]       ,       __magic_name__	:				NDArray[floataa]       ,       __magic_name__	:				float = 10**-1	)  ->    bool:
		"""simple docstring"""




		lowercase__	     =						cross(__magic_name__       ,       __magic_name__	)
		lowercase__	     =						sum(__magic_name__	)
		return abs(__magic_name__	) < eps


if __name__ == "__main__":
	# Test to check if it works
	A			:						Optional[Any]        =  array(
	    [
	        polar_force(718.4, 1_8_0 - 3_0),
	        polar_force(879.54, 4_5),
	        polar_force(1_0_0, -9_0),
	    ]
	)

	A			:						NDArray[floataa]        =  array([[0, 0], [0, 0], [0, 0]])

	assert in_static_equilibrium(forces, location)

	# Problem 1 in image_data/2D_problems.jpg
	A			:						str        =  array(
	    [
	        polar_force(3_0 * 9.81, 1_5),
	        polar_force(2_1_5, 1_8_0 - 4_5),
	        polar_force(2_6_4, 9_0 - 3_0),
	    ]
	)

	A			:						Union[str, Any]        =  array([[0, 0], [0, 0], [0, 0]])

	assert in_static_equilibrium(forces, location)

	# Problem in image_data/2D_problems_1.jpg
	A			:						List[str]        =  array([[0, -2_0_0_0], [0, -1_2_0_0], [0, 1_5_6_0_0], [0, -1_2_4_0_0]])

	A			:						Dict        =  array([[0, 0], [6, 0], [1_0, 0], [1_2, 0]])

	assert in_static_equilibrium(forces, location)

	import doctest

	doctest.testmod()






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_      :      str    =     logging.get_logger(__name__)
@add_end_docstrings(_lowercase				)
class    __UpperCamelCase			(       _lowercase				):

 """simple docstring"""



 def __init__(	self		,				*SCREAMING_SNAKE_CASE		,				**SCREAMING_SNAKE_CASE      ) ->			int:
  super().__init__(*SCREAMING_SNAKE_CASE		,				**SCREAMING_SNAKE_CASE      )
  self.check_model_type(SCREAMING_SNAKE_CASE      )

 def 						_UpperCAmelCase       (	self		,				SCREAMING_SNAKE_CASE=None		,				SCREAMING_SNAKE_CASE=None		,				SCREAMING_SNAKE_CASE=None		,				**SCREAMING_SNAKE_CASE      ) ->			Union[str, Any]:
  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		,				SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE = None		,				**SCREAMING_SNAKE_CASE      ) ->			Optional[int]:
  if isinstance(SCREAMING_SNAKE_CASE		,				(Image.Image, str)      ) and isinstance(SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE      ):
   a__												= {'''image''': image, '''question''': question}
  else:
   a__												= image
  a__												= super().__call__(SCREAMING_SNAKE_CASE		,				**SCREAMING_SNAKE_CASE      )
  return results

 def 						_UpperCAmelCase       (	self		,				SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE=False		,				SCREAMING_SNAKE_CASE=False      ) ->			Dict:
  a__												= load_image(inputs['''image''']      )
  a__												= self.tokenizer(
      inputs['''question''']		,				return_tensors=self.framework		,				padding=SCREAMING_SNAKE_CASE		,				truncation=SCREAMING_SNAKE_CASE      )
  a__												= self.image_processor(images=SCREAMING_SNAKE_CASE		,				return_tensors=self.framework      )
  model_inputs.update(SCREAMING_SNAKE_CASE      )
  return model_inputs

 def 						_UpperCAmelCase       (	self		,				SCREAMING_SNAKE_CASE      ) ->			Union[str, Any]:
  a__												= self.model(**SCREAMING_SNAKE_CASE      )
  return model_outputs



 def 						_UpperCAmelCase       (	self		,				SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE=5      ) ->			Optional[Any]:
  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(SCREAMING_SNAKE_CASE      )
  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(SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE      )]





