code: def forward(self, x):
      x = x.conv2d(self.c1).relu().max_pool2d()
      x = x.conv2d(self.c2).relu().max_pool2d()
      x = x.reshape(shape=[x.shape[0], -1])
      return x.dot(self.l1)
  
file_path: tinygrad/examples/train_efficientnet.py
imports: import traceback
  import time
  from multiprocessing import Process, Queue
  import numpy
  from tqdm import trange
  from tinygrad.nn.state import get_parameters
  from tinygrad.nn import optim
  from tinygrad.helpers import getenv
  from tinygrad.tensor import Tensor
  from extra.datasets import fetch_cifar
  from extra.models.efficientnet import EfficientNet
label_desc: Use image node_id 2 for calling the TinyConvNet obj's underlying member method code with example usage: obj.forward(x) and returns: x