class_docstr: Class implementing custom backward pass for compute_normalization. See compute_normalization.
code: def forward(ctx, activations, t, num_iters):
      if t < 1.0:
          normalization_constants = compute_normalization_binary_search(
              activations, t, num_iters
          )
      else:
          normalization_constants = compute_normalization_fixed_point(
              activations, t, num_iters
          )
  
      ctx.save_for_backward(activations, normalization_constants)
      ctx.t = t
      return normalization_constants
  
imports: from typing import Optional
  import torch
  from torch import nn, Tensor
label_desc: Use image node_id 1 for calling the ComputeNormalization obj's underlying member method code with example usage: obj.forward(ctx, activations, t, num_iters) and returns: normalization_constants