code: def __init__(self, input_width, output_width, depth):
      super().__init__()
      self.input_width = input_width
      self.output_width = output_width
  
      self.depth = depth
      self.n_nodes = 2 ** (depth + 1) - 1
  
      l1_init_factor = 1.0 / math.sqrt(self.input_width)
      l2_init_factor = 1.0 / math.sqrt(self.n_nodes)
      self.w1s = nn.Parameter(
          torch.empty(
              (input_width * self.n_nodes, 1), dtype=torch.float
          ).uniform_(-l1_init_factor, +l1_init_factor),
          requires_grad=True,
      )
      self.w2s = nn.Parameter(
          torch.empty(
              (self.n_nodes, output_width), dtype=torch.float
          ).uniform_(-l2_init_factor, +l2_init_factor),
          requires_grad=True,
      )
  
imports: import torch
  from torch import nn
  import math
label_desc: Use image node_id 1 to create a new FFF_Sparse object from inherited base classes: nn with example: obj = FFF_Sparse(input_width, output_width, depth)