code: def step(optim, steps=1, kwargs={}):
      net = TinyNet()
      optim = optim([net.x, net.W], **kwargs)
      for _ in range(steps):
          out = net.forward()
          optim.zero_grad()
          out.backward()
          optim.step()
      return net.x.detach().numpy(), net.W.detach().numpy()
  
imports: import unittest
  import numpy
  import tensorflow
  import tensorflow_addons
  from tinygrad.tensor import Tensor
  from tinygrad.nn.optim import LAMB
label_desc: Use image node_id 1 for calling a global function with example usage: step(optim, steps, kwargs) and returns: net,  net