code: def test_data_parallel_resnet(self):
      import sys, pathlib
  
      sys.path.append(
          (
              pathlib.Path(__file__).parent.parent / "extra" / "models"
          ).as_posix()
      )
      from resnet import ResNet18
  
      fake_image = Tensor.rand((2, 3, 224, 224))
      fake_image_sharded = fake_image.shard((d0, d1), axis=0)
      m = ResNet18()
      m.load_from_pretrained()
      real_output = m(fake_image).numpy()
      for p in get_parameters(m):
          p.shard_((d0, d1)).realize()
      GlobalCounters.reset()
      shard_output = m(fake_image_sharded).realize()
      assert shard_output.lazydata.lbs[0].shape == (1, 1000)
      assert shard_output.lazydata.lbs[1].shape == (1, 1000)
      shard_output_np = shard_output.numpy()
      np.testing.assert_allclose(
          real_output, shard_output_np, atol=1e-6, rtol=1e-6
      )
  
imports: import functools
  import unittest
  from tinygrad import Tensor, Device, nn, GlobalCounters
  from tinygrad.device import _BufferCopy
  from tinygrad.helpers import CI
  from tinygrad.jit import TinyJit
  from tinygrad.nn.state import get_parameters
  import numpy
label_desc: Use image node_id 38 for calling the TestMultiTensor obj's underlying member method code with example usage: obj.test_data_parallel_resnet() without return types