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: Concrete pass through the ReLU function
  
  :param x: concrete input to the activation function.
  :return: concrete outputs from the ReLU.
docstr_tok: ["Concrete","pass","through","the","ReLU","function",":","param","x",":","concrete","input","to","the","activation","function",".",":","return",":","concrete","outputs","from","the","ReLU","."]
code: def concrete_forward(self, x: "torch.Tensor") -> "torch.Tensor":
      """
      Concrete pass through the ReLU function
  
      :param x: concrete input to the activation function.
      :return: concrete outputs from the ReLU.
      """
      return self.concrete_activation(x)
  
imports: from typing import Tuple, Union
  import numpy
  import torch
label_desc: Use image node_id 4 for calling the ZonoReLU obj's underlying member method code with example usage: obj.concrete_forward(x) and returns: self