class_docstr: A CoreSaliency class that computes saliency masks by occluding the image.
  
  This method slides a window over the image and computes how that occlusion
  affects the class score. When the class score decreases, this is positive
  evidence for the class, otherwise it is negative evidence.
code: def getY(self, x_value, call_model_function, call_model_args):
      x_value_batched = np.expand_dims(x_value, axis=0)
      data = call_model_function(
          x_value_batched,
          call_model_args=call_model_args,
          expected_keys=self.expected_keys,
      )
      self.format_and_check_call_model_output(
          data, x_value_batched.shape, self.expected_keys
      )
      return data[OUTPUT_LAYER_VALUES][0]
  
imports: from .base import CoreSaliency
  from .base import OUTPUT_LAYER_VALUES
  import numpy
label_desc: Use image node_id 1 for calling the Occlusion obj's underlying member method code with example usage: obj.getY(x_value, call_model_function, call_model_args) and returns: data