class_docstr: Class implementing a dense layer on a zonotope.
  Bias is only added to the zeroth term.
class_docstr_tok: ["Class","implementing","a","dense","layer","on","a","zonotope",".","Bias","is","only","added","to","the","zeroth","term","."]
code: def __init__(self, in_features: int, out_features: int):
      super().__init__()
      self.weight = torch.nn.Parameter(
          torch.normal(
              mean=torch.zeros(out_features, in_features),
              std=torch.ones(out_features, in_features),
          )
      )
      self.bias = torch.nn.Parameter(
          torch.normal(
              mean=torch.zeros(out_features),
              std=torch.ones(out_features),
          )
      )
  
imports: from typing import Tuple, Union
  import numpy
  import torch
label_desc: Use image node_id 1 to create a new ZonoDenseLayer object from inherited base classes: torch.nn with example: obj = ZonoDenseLayer(in_features, out_features)