code: def test_transformer_synthetic_reward(self):
      state_dim = 10
      action_dim = 2
      d_model = 64
      nhead = 8
      num_encoder_layers = 2
      dim_feedforward = 64
      dropout = 0.0
      activation = "relu"
      last_layer_activation = "leaky_relu"
      layer_norm_eps = 1e-5
      max_len = 10
  
      net = TransformerSyntheticRewardNet(
          state_dim=state_dim,
          action_dim=action_dim,
          d_model=d_model,
          nhead=nhead,
          num_encoder_layers=num_encoder_layers,
          dim_feedforward=dim_feedforward,
          dropout=dropout,
          activation=activation,
          last_layer_activation=last_layer_activation,
          layer_norm_eps=layer_norm_eps,
          max_len=max_len,
      )
  
      reward_net = SyntheticRewardNet(net)
      export_net = reward_net.export_mlp()
      transformer = export_net.transformer
      assert export_net.state_dim == state_dim
      assert export_net.action_dim == action_dim
      assert export_net.d_model == d_model
      assert export_net.nhead == nhead
      assert export_net.dim_feedforward == dim_feedforward
      assert export_net.dropout == dropout
      assert export_net.activation == activation
      assert export_net.layer_norm_eps == layer_norm_eps
  
      assert transformer.num_layers == num_encoder_layers
      dnn_out = export_net.fc_out
      assert dnn_out.in_features == d_model
      assert dnn_out.out_features == 1
  
      output_activation = export_net.output_activation
      assert output_activation._get_name() == "LeakyReLU"
  
file_path: ReAgent/reagent/test/models/test_synthetic_reward_net.py
imports: import logging
  import unittest
  import torch
  from reagent.core import parameters
  from reagent.models.synthetic_reward import _gen_mask, NGramConvolutionalNetwork, NGramFullyConnectedNetwork, SequenceSyntheticRewardNet, SingleStepSyntheticRewardNet, SyntheticRewardNet, TransformerSyntheticRewardNet
  from reagent.models.synthetic_reward_sparse_arch import SingleStepSyntheticSparseArchRewardNet, SyntheticRewardSparseArchNet
  from torchrec import EmbeddingBagCollection, EmbeddingBagConfig
label_desc: Use image node_id 5 for calling the TestSyntheticReward obj's underlying member method code with example usage: obj.test_transformer_synthetic_reward() without return types