class_docstr: stores a single scalar value and its gradient 
class_docstr_tok: ["stores","a","single","scalar","value","and","its","gradient"]
code: def relu(self):
      out = Value(0 if self.data < 0 else self.data, (self,), "ReLU")
  
      def _backward():
          self.grad += (out.data > 0) * out.grad
  
      out._backward = _backward
  
      return out
  
file_path: micrograd/micrograd/engine.py
label_desc: Use image node_id 5 for calling the Value obj's underlying member method code with example usage: obj.relu() and returns: out