code: def forward(self, x):
      return x.dot(self.l1).relu().dot(self.l2).log_softmax()
  
imports: import numpy
  import torch
  import unittest
  from tinygrad.tensor import Tensor
  from tinygrad.nn.state import get_parameters
  from tinygrad.nn.optim import Adam
  from extra.lr_scheduler import MultiStepLR, ReduceLROnPlateau, CosineAnnealingLR, OneCycleLR
  from extra.training import train, evaluate
  from extra.datasets import fetch_mnist
label_desc: Use image node_id 3 for calling the TinyBobNet obj's underlying member method code with example usage: obj.forward(x) and returns: x