class_docstr: MADE building block layer
class_docstr_tok: ["MADE","building","block","layer"]
code: def __init__(self, input_size, n_outputs, mask, cond_label_size=None):
      super().__init__(input_size, n_outputs)
  
      self.register_buffer("mask", mask)
  
      self.cond_label_size = cond_label_size
      if cond_label_size is not None:
          self.cond_weight = nn.Parameter(
              torch.rand(n_outputs, cond_label_size)
              / math.sqrt(cond_label_size)
          )
  
imports: import copy
  import math
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.distributions import Normal
label_desc: Use image node_id 1 to create a new MaskedLinear object from inherited base classes: nn with example: obj = MaskedLinear(input_size, n_outputs, mask, cond_label_size)