code: def test_embedding_max_norm(self):
      embedding = nn.Embedding(22, 5, max_norm=1.0)
      input = torch.tensor([2, 8, 8, 6], dtype=torch.long)
      output = embedding(input)
      self.assertEqual(output[1], output[2])
      self.assertTrue(output.data.norm(p=2, dim=1).le(1).all())
  
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 5 for calling the TestEmbeddingNN obj's underlying member method code with example usage: obj.test_embedding_max_norm() without return types