docstr: In the backward pass we receive a Tensor containing the gradient of the loss
  with respect to the output, and we need to compute the gradient of the loss
  with respect to the input.
code: def backward(ctx, grad_output):
      """
      In the backward pass we receive a Tensor containing the gradient of the loss
      with respect to the output, and we need to compute the gradient of the loss
      with respect to the input.
      """
      (input_abs,) = ctx.saved_tensors
      grad_input = grad_output.clone()
  
      return grad_input * (1.0 / input_abs) / 2.302585093
  
file_path: ARKitScenes/depth_upsampling/losses/gradient_loss.py
imports: import torch
  import dataset_keys
label_desc: Use image node_id 2 for calling the SafeTorchLog obj's underlying member method code with example usage: obj.backward(ctx, grad_output) and returns: unknown