code: def test_enet(self):
      model = EfficientNet(getenv("ENET_NUM", 0), has_se=False)
      for p in get_parameters(model):
          p.assign(np.zeros(p.shape, dtype=p.dtype.np))
      img = Tensor.randn(1, 3, 224, 224)
      with CLCache(51):
          model.forward(img).realize()
  
imports: import os
  import torch
  import gc
  import numpy
  import unittest
  from tinygrad.tensor import Tensor, Device
  from tinygrad import nn, GlobalCounters
  from tinygrad.helpers import getenv
  from tinygrad.nn import optim
  from tinygrad.jit import CacheCollector
  from extra.models.convnext import ConvNeXt
  from extra.models.efficientnet import EfficientNet
  from extra.models.resnet import ResNet18
  from extra.models.vit import ViT
  from tinygrad.nn.state import get_parameters
label_desc: Use image node_id 4 for calling the TestInferenceMinKernels obj's underlying member method code with example usage: obj.test_enet() without return types