code: def forward(self, state: torch.Tensor, action: torch.Tensor):
      # state shape: seq_len, batch_size, state_dim
      # action shape: seq_len, batch_size, action_dim
      return self.dnn(state, action).squeeze(2).transpose(0, 1)
  
imports: import logging
  import math
  from typing import List
  import torch
  import torch.nn
  import torch.nn.functional
  from reagent.core import parameters, types
  from reagent.models import convolutional_network, fully_connected_network
  from reagent.models.base import ModelBase
  from reagent.models.fully_connected_network import ACTIVATION_MAP
label_desc: Use image node_id 2 for calling the SingleStepSyntheticRewardNet obj's underlying member method code with example usage: obj.forward(state, action) and returns: self