code: def __init__(self, classes=10):
      conv = 3
      inter_chan, out_chan = 8, 16  # for speed
      self.c1 = Tensor.uniform(inter_chan, 3, conv, conv)
      self.c2 = Tensor.uniform(out_chan, inter_chan, conv, conv)
      self.l1 = Tensor.uniform(out_chan * 6 * 6, classes)
  
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 1 to create a new TinyConvNet object  with example: obj = TinyConvNet(classes)