code: def __init__(self, W):
      self.whitening = W
      self.net = [
          nn.Conv2d(12, 32, kernel_size=1, bias=False),
          lambda x: x.quick_gelu(),
          ConvGroup(32, 64),
          ConvGroup(64, 256),
          ConvGroup(256, 512),
          lambda x: x.max((2, 3)),
          nn.Linear(512, 10, bias=False),
          lambda x: x.mul(1.0 / 9),
      ]
  
file_path: tinygrad/examples/hlb_cifar10.py
imports: import random, time
  import numpy
  from typing import Optional
  from extra.datasets import fetch_cifar, cifar_mean, cifar_std
  from tinygrad import nn, dtypes, Tensor, Device, GlobalCounters, TinyJit
  from tinygrad.nn.state import get_state_dict, get_parameters
  from tinygrad.nn import optim
  from extra.lr_scheduler import OneCycleLR
  from tinygrad.helpers import Context, getenv
label_desc: Use image node_id 1 to create a new SpeedyResNet object  with example: obj = SpeedyResNet(W)