class_docstr: Base class for saliency methods. Alone, this class doesn't do anything.
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docstr: Returns an unsmoothed mask.
  
  Args:
    x_value: Input ndarray.
    call_model_function: A function that interfaces with a model to return
      specific output in a dictionary when given an input and other arguments.
      Expected function signature:
      - call_model_function(x_value_batch,
                            call_model_args=None,
                            expected_keys=None):
        x_value_batch - Input for the model, given as a batch (i.e. dimension
          0 is the batch dimension, dimensions 1 through n represent a single
          input).
        call_model_args - Other arguments used to call and run the model.
        expected_keys - List of keys that are expected in the output. Possible
          keys in this list are CONVOLUTION_LAYER_VALUES, 
          CONVOLUTION_OUTPUT_GRADIENTS, INPUT_OUTPUT_GRADIENTS, and
          OUTPUT_LAYER_VALUES, and are explained in detail where declared.
    call_model_args: The arguments that will be passed to the call model
      function, for every call of the model.
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code: def GetMask(self, x_value, call_model_function, call_model_args=None):
      """Returns an unsmoothed mask.
  
      Args:
        x_value: Input ndarray.
        call_model_function: A function that interfaces with a model to return
          specific output in a dictionary when given an input and other arguments.
          Expected function signature:
          - call_model_function(x_value_batch,
                                call_model_args=None,
                                expected_keys=None):
            x_value_batch - Input for the model, given as a batch (i.e. dimension
              0 is the batch dimension, dimensions 1 through n represent a single
              input).
            call_model_args - Other arguments used to call and run the model.
            expected_keys - List of keys that are expected in the output. Possible
              keys in this list are CONVOLUTION_LAYER_VALUES,
              CONVOLUTION_OUTPUT_GRADIENTS, INPUT_OUTPUT_GRADIENTS, and
              OUTPUT_LAYER_VALUES, and are explained in detail where declared.
        call_model_args: The arguments that will be passed to the call model
          function, for every call of the model.
  
      """
      raise NotImplementedError(
          "A derived class should implemented GetMask()"
      )
  
imports: import numpy
label_desc: Use image node_id 1 for calling the CoreSaliency obj's underlying member method code with example usage: obj.GetMask(x_value, call_model_function, call_model_args) without return types