code: def test_more_ops():
      a = Value(-4.0)
      b = Value(2.0)
      c = a + b
      d = a * b + b**3
      c += c + 1
      c += 1 + c + (-a)
      d += d * 2 + (b + a).relu()
      d += 3 * d + (b - a).relu()
      e = c - d
      f = e**2
      g = f / 2.0
      g += 10.0 / f
      g.backward()
      amg, bmg, gmg = a, b, g
  
      a = torch.Tensor([-4.0]).double()
      b = torch.Tensor([2.0]).double()
      a.requires_grad = True
      b.requires_grad = True
      c = a + b
      d = a * b + b**3
      c = c + c + 1
      c = c + 1 + c + (-a)
      d = d + d * 2 + (b + a).relu()
      d = d + 3 * d + (b - a).relu()
      e = c - d
      f = e**2
      g = f / 2.0
      g = g + 10.0 / f
      g.backward()
      apt, bpt, gpt = a, b, g
  
      tol = 1e-6
      # forward pass went well
      assert abs(gmg.data - gpt.data.item()) < tol
      # backward pass went well
      assert abs(amg.grad - apt.grad.item()) < tol
      assert abs(bmg.grad - bpt.grad.item()) < tol
  
imports: import torch
  from micrograd.engine import Value
label_desc: Use image node_id 2 for calling a global function with example usage: test_more_ops() without return types