code: def test_basic(self):
      # Setup embedding
      num_embeddings = 5
      output_dim = 6
      embedding_module = WordEmbedding(
          num_embeddings=num_embeddings,
          embedding_dim=4,
          embeddings_weight=None,
          init_range=[-1, 1],
          unk_token_idx=4,
          mlp_layer_dims=[3, output_dim],
      )
      self.assertEqual(embedding_module.embedding_dim, output_dim)
  
      # Check output shape
      input_batch_size, input_len = 4, 6
      token_ids = torch.randint(
          low=0, high=num_embeddings, size=[input_batch_size, input_len]
      )
      output_embedding = embedding_module(token_ids)
      expected_output_dims = [input_batch_size, input_len, output_dim]
      self.assertEqual(
          list(output_embedding.size()), expected_output_dims
      )
  
imports: import unittest
  import torch
  from pytext.models.embeddings.word_embedding import WordEmbedding
label_desc: Use image node_id 1 for calling the WordEmbeddingTest obj's underlying member method code with example usage: obj.test_basic() without return types