docstr: In the forward pass we receive a Tensor containing the input and return
  a Tensor containing the output. ctx is a context object that can be used
  to stash information for backward computation. You can cache arbitrary
  objects for use in the backward pass using the ctx.save_for_backward method.
code: def forward(ctx, input):
      """
      In the forward pass we receive a Tensor containing the input and return
      a Tensor containing the output. ctx is a context object that can be used
      to stash information for backward computation. You can cache arbitrary
      objects for use in the backward pass using the ctx.save_for_backward method.
      """
  
      input_abs = torch.abs(input) + 1e-9
      ctx.save_for_backward(input_abs)
  
      return torch.log(input_abs)
  
file_path: ARKitScenes/depth_upsampling/losses/gradient_loss.py
imports: import torch
  import dataset_keys
label_desc: Use image node_id 1 for calling the SafeTorchLog obj's underlying member method code with example usage: obj.forward(ctx, input) and returns: torch