class_docstr: Perform SmoothGrad algorithm for a given input
  
  Paper: [SmoothGrad: removing noise by adding noise](https://arxiv.org/abs/1706.03825)
docstr: Save the output to a specific dir.
  
  Args:
      grid (numpy.ndarray): Gtid of all the smoothed gradients
      output_dir (str): Output directory path
      output_name (str): Output name
code: def save(self, grid, output_dir, output_name):
      """
      Save the output to a specific dir.
  
      Args:
          grid (numpy.ndarray): Gtid of all the smoothed gradients
          output_dir (str): Output directory path
          output_name (str): Output name
      """
      save_grayscale(grid, output_dir, output_name)
  
file_path: tf-explain/tf_explain/core/smoothgrad.py
imports: import numpy
  import tensorflow
  from tf_explain.utils.display import grid_display
  from tf_explain.utils.image import transform_to_normalized_grayscale
  from tf_explain.utils.saver import save_grayscale
label_desc: Use image node_id 4 for calling the SmoothGrad obj's underlying member method code with example usage: obj.save(grid, output_dir, output_name) without return types