class_docstr: A TF1CoreSaliency class that implements IG along blur path.
  
  https://arxiv.org/abs/2004.03383
  
  Generates a saliency mask by computing integrated gradients for a given input
  and prediction label using a path that successively blurs the image.
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docstr: Returns a BlurIG mask.
  
  Args:
    x_value: Input value, not batched.
    feed_dict: (Optional) feed dictionary to pass to the session.run call.
    max_sigma: Maximum size of the gaussian blur kernel.
    steps: Number of successive blur applications between x and fully blurred
      image (with kernel max_sigma).
    grad_step: Gaussian gradient step size.
    sqrt: Chooses square root when deciding spacing between sigma. (Full
      mathematical implication remains to be understood).
    batch_size: Maximum number of x inputs (steps along the integration path)
      that are passed to sess.run as a batch.
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code: def GetMask(
      self,
      x_value,
      feed_dict=None,
      max_sigma=50,
      steps=100,
      grad_step=0.01,
      sqrt=False,
      batch_size=1,
  ):
      """Returns a BlurIG mask.
  
      Args:
        x_value: Input value, not batched.
        feed_dict: (Optional) feed dictionary to pass to the session.run call.
        max_sigma: Maximum size of the gaussian blur kernel.
        steps: Number of successive blur applications between x and fully blurred
          image (with kernel max_sigma).
        grad_step: Gaussian gradient step size.
        sqrt: Chooses square root when deciding spacing between sigma. (Full
          mathematical implication remains to be understood).
        batch_size: Maximum number of x inputs (steps along the integration path)
          that are passed to sess.run as a batch.
      """
      self.validate_xy_tensor_shape(steps, batch_size)
  
      return self.core_instance.GetMask(
          x_value,
          self.call_model_function,
          call_model_args=feed_dict,
          max_sigma=max_sigma,
          steps=steps,
          grad_step=grad_step,
          sqrt=sqrt,
          batch_size=batch_size,
      )
  
imports: from .base import TF1CoreSaliency
  from ..core import blur_ig
label_desc: Use image node_id 2 for calling the BlurIG obj's underlying member method code with example usage: obj.GetMask(x_value, feed_dict, max_sigma, steps, grad_step, sqrt, batch_size) and returns: self