



'''simple docstring'''


_lowerCamelCase	:       Optional[Any]      	=	9.8_06_65







def 				__lowerCamelCase				(   A__    ,						A__    ,						A__ = g    )       ->	float:






   """simple docstring"""

   if fluid_density <= 0:
      raise ValueError('Impossible fluid density'    )
   if volume < 0:
      raise ValueError('Impossible Object volume'    )
   if gravity <= 0:
      raise ValueError('Impossible Gravity'    )

   return fluid_density * gravity * volume


if __name__ == "__main__":
   import doctest

   # run doctest
   doctest.testmod()






'''simple docstring'''


from io import BytesIO
from typing import List, Union

import requests

from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_decord_available():
   import numpy as np
   from decord import VideoReader


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

_lowerCamelCase	:       Any      	=	logging.get_logger(__name__)

@add_end_docstrings(_a		)
class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""





    def __init__(  self      :					Any  ,						*UpperCamelCase__      :					Dict  ,						**UpperCamelCase__      :					Union[str, Any] ):


       """simple docstring"""







       super().__init__(*UpperCamelCase__  ,						**UpperCamelCase__ )
       requires_backends(self  ,						'decord' )
       self.check_model_type(UpperCamelCase__ )






    def  A       (  self      :					Optional[int]  ,						UpperCamelCase__      :					Optional[int]=None  ,						UpperCamelCase__      :					Optional[Any]=None  ,						UpperCamelCase__      :					Optional[Any]=None ):


       """simple docstring"""







       UpperCamelCase					=  {}
       if frame_sampling_rate is not None:
          UpperCamelCase					=  frame_sampling_rate
       if num_frames is not None:
          UpperCamelCase					=  num_frames

       UpperCamelCase					=  {}
       if top_k is not None:
          UpperCamelCase					=  top_k
       return preprocess_params, {}, postprocess_params






    def __call__(  self      :					List[str]  ,						UpperCamelCase__      :					Union[str, List[str]]  ,						**UpperCamelCase__      :					Dict ):


       """simple docstring"""







       return super().__call__(UpperCamelCase__  ,						**UpperCamelCase__ )






    def  A       (  self      :					Tuple  ,						UpperCamelCase__      :					Union[str, Any]  ,						UpperCamelCase__      :					Tuple=None  ,						UpperCamelCase__      :					Tuple=1 ):


       """simple docstring"""







       if num_frames is None:
          UpperCamelCase					=  self.model.config.num_frames

       if video.startswith('http://' ) or video.startswith('https://' ):
          UpperCamelCase					=  BytesIO(requests.get(UpperCamelCase__ ).content )

       UpperCamelCase					=  VideoReader(UpperCamelCase__ )
       videoreader.seek(0 )

       UpperCamelCase					=  0
       UpperCamelCase					=  num_frames * frame_sampling_rate - 1
       UpperCamelCase					=  np.linspace(UpperCamelCase__  ,						UpperCamelCase__  ,						num=UpperCamelCase__  ,						dtype=np.intaa )

       UpperCamelCase					=  videoreader.get_batch(UpperCamelCase__ ).asnumpy()
       UpperCamelCase					=  list(UpperCamelCase__ )

       UpperCamelCase					=  self.image_processor(UpperCamelCase__  ,						return_tensors=self.framework )
       return model_inputs






    def  A       (  self      :					Union[str, Any]  ,						UpperCamelCase__      :					List[str] ):


       """simple docstring"""







       UpperCamelCase					=  self.model(**UpperCamelCase__ )
       return model_outputs






    def  A       (  self      :					int  ,						UpperCamelCase__      :					str  ,						UpperCamelCase__      :					List[Any]=5 ):


       """simple docstring"""







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

       if self.framework == "pt":
          UpperCamelCase					=  model_outputs.logits.softmax(-1 )[0]
          UpperCamelCase				,      UpperCamelCase					=  probs.topk(UpperCamelCase__ )
       else:
          raise ValueError(f"""Unsupported framework: {self.framework}""" )

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

