class_docstr: Masked Linear Layer inheriting from `~torch.nn.Linear` class and applying a mask to consider
  only a selection of weight.
class_docstr_tok: ["Masked","Linear","Layer","inheriting","from","`","~torch.nn.Linear","`","class","and","applying","a","mask","to","consider","only","a","selection","of","weight","."]
code: def __init__(self, in_features, out_features, mask):
      nn.Linear.__init__(
          self, in_features=in_features, out_features=out_features
      )
  
      self.register_buffer("mask", mask)
  
file_path: benchmark_VAE/src/pythae/models/normalizing_flows/layers.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from pythae.models.base.base_utils import ModelOutput
label_desc: Use image node_id 1 to create a new MaskedLinear object from inherited base classes: nn with example: obj = MaskedLinear(in_features, out_features, mask)