
"""simple docstring"""


def  lowercase						(	lowerCAmelCase__						):
			return " ".join(input_str.split()[::-1]						)


if __name__ == "__main__":
						import 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

_a					:			List[Any]							=    logging.get_logger(__name__)



@add_end_docstrings(a			)
class 							lowercase_						(		a			):

  '''simple docstring'''





  def __init__(  self ,			*a_ ,			**a_  )				->					str:


    """simple docstring"""
    super().__init__(*a_ ,			**a_  )
    requires_backends(self ,			'decord'  )
    self.check_model_type(a_  )
  def     snake_case_      (  self ,			a_=None ,			a_=None ,			a_=None  )				->					int:


    """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 ,			a_ ,			**a_  )				->					Union[str, Any]:


    """simple docstring"""
    return super().__call__(a_ ,			**a_  )
  def     snake_case_      (  self ,			a_ ,			a_=None ,			a_=1  )				->					Tuple:


    """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(a_  ).content  )

    UpperCAmelCase    				=						VideoReader(a_  )
    videoreader.seek(0  )

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

    UpperCAmelCase    				=						videoreader.get_batch(a_  ).asnumpy()
    UpperCAmelCase    				=						list(a_  )

    UpperCAmelCase    				=						self.image_processor(a_ ,			return_tensors=self.framework  )
    return model_inputs
  def     snake_case_      (  self ,			a_  )				->					Union[str, Any]:


    """simple docstring"""
    UpperCAmelCase    				=						self.model(**a_  )
    return model_outputs





  def     snake_case_      (  self ,			a_ ,			a_=5  )				->					Union[str, Any]:


    """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(a_  )
    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(a_ ,			a_  )]


