code: def test_embedding_from_pretrained(self, dtype):
      a = torch.tensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], dtype=dtype)
      embedding = nn.Embedding.from_pretrained(a)
      self.assertEqual(a, embedding.weight.data)
  
      input = torch.LongTensor([0, 1])
      output = embedding(input)
      self.assertEqual(a, output)
  
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 6 for calling the TestEmbeddingNN obj's underlying member method code with example usage: obj.test_embedding_from_pretrained(dtype) without return types