code: def multiplies_by_inputs(self):
      return self._multiply_by_inputs
  
imports: import typing
  from typing import Any, Callable, cast, List, Tuple, Union
  import numpy
  import torch
  from captum._utils.gradient import _forward_layer_eval, compute_layer_gradients_and_eval
  from captum._utils.typing import Literal, TargetType, TensorOrTupleOfTensorsGeneric
  from captum.attr._core.gradient_shap import _scale_input
  from captum.attr._core.noise_tunnel import NoiseTunnel
  from captum.attr._utils.attribution import GradientAttribution, LayerAttribution
  from captum.attr._utils.common import _compute_conv_delta_and_format_attrs, _format_callable_baseline, _format_input_baseline
  from captum.log import log_usage
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 6 for calling the LayerInputBaselineXGradient obj's underlying member method code with example usage: obj.multiplies_by_inputs() and returns: self