original_docstring: Get indices of different stages of proposals in validation mode.
  
          It will calculate the average interval for each segment.
          If the total number of valid length is smaller than num segments,
          it will return all zero indices.
  
          Args:
              valid_length (int): The length of the starting point's
                  valid interval.
              num_segments (int): Total number of segments.
  
          Returns:
              np.ndarray: Sampled frame indices in validation mode.
          
docstring: Get indices of different stages of proposals in validation mode.
  It will calculate the average interval for each segment.
  If the total number of valid length is smaller than num segments,
  it will return all zero indices.
docstring_tokens: Get indices of different stages of proposals in validation mode . It will calculate the average interval for each segment . If the total number of valid length is smaller than num segments it will return all zero indices .
code: def _get_val_indices(self, valid_length, num_segments):
          """Get indices of different stages of proposals in validation mode.
  
          It will calculate the average interval for each segment.
          If the total number of valid length is smaller than num segments,
          it will return all zero indices.
  
          Args:
              valid_length (int): The length of the starting point's
                  valid interval.
              num_segments (int): Total number of segments.
  
          Returns:
              np.ndarray: Sampled frame indices in validation mode.
          """
          if valid_length >= num_segments:
              avg_interval = valid_length / float(num_segments)
              base_offsets = np.arange(num_segments) * avg_interval
              offsets = (base_offsets + avg_interval / 2.0).astype(np.int)
          else:
              offsets = np.zeros((num_segments, ), dtype=np.int)
  
          return offsets
code_tokens: def _get_val_indices ( self , valid_length , num_segments ) : if valid_length >= num_segments : avg_interval = valid_length / float ( num_segments ) base_offsets = np . arange ( num_segments ) * avg_interval offsets = ( base_offsets + avg_interval / 2.0 ) . astype ( np . int ) else : offsets = np . zeros ( ( num_segments , ) , dtype = np . int ) return offsets
short_docstring: Get indices of different stages of proposals in validation mode.
short_docstring_tokens: Get indices of different stages of proposals in validation mode .
comment: """Get indices of different stages of proposals in validation mode.
  
          It will calculate the average interval for each segment.
          If the total number of valid length is smaller than num segments,
          it will return all zero indices.
  
          Args:
              valid_length (int): The length of the starting point's
                  valid interval.
              num_segments (int): Total number of segments.
  
          Returns:
              np.ndarray: Sampled frame indices in validation mode.
          """