code: def test_pooling_mlp(self):
      # Setup embedding
      config = IntSingleCategoryEmbedding.Config(
          pooling_type="max",
          feature_buckets={1: 10, 2: 20},
          mlp_layer_dims=[40],
      )
      embedding_module = IntSingleCategoryEmbedding.from_config(config)
  
      output = embedding_module(
          {
              1: torch.tensor([11, 12, 13], dtype=torch.int),
              2: torch.tensor([21, 22, 23], dtype=torch.int),
          }
      )
  
      self.assertEqual(list(output.size()), [3, 40])
      self.assertEqual(embedding_module.get_output_dim(), 40)
  
imports: import unittest
  import torch
  from pytext.models.embeddings.int_single_category_embedding import IntSingleCategoryEmbedding
label_desc: Use image node_id 3 for calling the IntSingleCategoryEmbeddingTest obj's underlying member method code with example usage: obj.test_pooling_mlp() without return types