code: def test_move_sparse_half_embedding(self):
      embedding = nn.Embedding(10, 3, sparse=True)
      self.assertEqual(embedding.weight.device.type, "cpu")
      self.assertEqual(
          embedding.weight.dtype, torch.get_default_dtype()
      )
      embedding.to(torch.float16)
      self.assertEqual(embedding.weight.dtype, torch.float16)
      self.assertEqual(embedding.embedding_dim, 3)
      self.assertEqual(embedding.num_embeddings, 10)
  
      if torch.cuda.is_available():
          embedding.to("cuda")
          self.assertEqual(embedding.weight.device.type, "cuda")
          embedding.to("cpu")
          self.assertEqual(embedding.weight.device.type, "cpu")
  
imports: import unittest
  import random
  import itertools
  from itertools import product
  import torch
  from torch.testing._internal.common_utils import run_tests, set_default_dtype, skipIfTorchDynamo, instantiate_parametrized_tests, parametrize, _assertGradAndGradgradChecks, IS_JETSON
  from torch.testing._internal.common_cuda import TEST_CUDA
  from torch.testing._internal.common_nn import NNTestCase
  from torch.testing._internal.common_device_type import onlyNativeDeviceTypes, dtypes, instantiate_device_type_tests, dtypesIfCUDA, onlyCUDA, TEST_WITH_ROCM, skipCUDAIf, skipMeta
  import torch.nn.functional
  import torch.nn
  from torch.testing._internal.common_utils import dtype2prec_DONTUSE
label_desc: Use image node_id 4 for calling the TestEmbeddingNN obj's underlying member method code with example usage: obj.test_move_sparse_half_embedding() without return types