code: def step(tensor, optim, steps=1, teeny=False, **kwargs):
      net = TeenyNet(tensor) if teeny else TinyNet(tensor)
      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 numpy
  import torch
  import unittest
  from tinygrad import Tensor, Device
  from tinygrad.nn.optim import Adam, SGD, AdamW
  from tinygrad.helpers import CI
label_desc: Use image node_id 1 for calling a global function with example usage: step(tensor, optim, steps, teeny) and returns: net,  net