class_docstr: Implements "DeepZ" for relu.
  
  | Paper link:  https://papers.nips.cc/paper/2018/file/f2f446980d8e971ef3da97af089481c3-Paper.pdf
class_docstr_tok: ["Implements","``","DeepZ","''","for","relu",".","|","Paper","link",":","https",":","\/\/papers.nips.cc\/paper\/2018\/file\/f2f446980d8e971ef3da97af089481c3-Paper.pdf"]
docstr: Forward pass through the relu
  
  :param x: input zonotope to the dense layer.
  :return x: zonotope after being pushed through the dense layer.
docstr_tok: ["Forward","pass","through","the","relu",":","param","x",":","input","zonotope","to","the","dense","layer",".",":","return","x",":","zonotope","after","being","pushed","through","the","dense","layer","."]
code: def forward(self, x: "torch.Tensor") -> "torch.Tensor":
      """
      Forward pass through the relu
  
      :param x: input zonotope to the dense layer.
      :return x: zonotope after being pushed through the dense layer.
      """
      return self.zonotope_relu(x)
  
imports: from typing import Tuple, Union
  import numpy
  import torch
label_desc: Use image node_id 3 for calling the ZonoReLU obj's underlying member method code with example usage: obj.forward(x) and returns: self