code: def _small_encoder(self):
      layers = [
          TransformerLayer(
              embedding_dim=12,
              attention=MultiheadSelfAttention(
                  embed_dim=12, num_heads=12, scaling=0.125
              ),
          )
          for _ in range(2)
      ]
      transformer = Transformer(
          vocab_size=100, embedding_dim=12, layers=layers
      )
      return SentenceEncoder(transformer)
  
file_path: pytext/pytext/models/representations/test/transformer_test.py
imports: import unittest
  import torch
  from pytext.models.representations.transformer import MultiheadSelfAttention, SentenceEncoder, Transformer, TransformerLayer
  from pytext.models.representations.transformer.representation import TransformerRepresentation
label_desc: Use image node_id 1 for calling the SentenceEncoderTest obj's underlying member method code with example usage: obj._small_encoder() and returns: SentenceEncoder