text: import torch
  import torch.nn as nn
  import torch.nn.functional as F
  
  class QNetwork(nn.Module):
      """Actor (Policy) Model."""
  
      def __init__(self, state_size, action_size, seed, fc1_units=512, fc2_units=512):
          """Initialize parameters and build model.
          Params
          ======
              state_size (int): Dimension of each state
              action_size (int): Dimension of each action
              seed (int): Random seed
          """
          super(QNetwork, self).__init__()
          self.seed = torch.manual_seed(seed)
          self.fc1 = nn.Linear(state_size, fc1_units)
          self.fc2 = nn.Linear(fc1_units, fc2_units)
          self.fc3 = nn.Linear(fc2_units, action_size)
  
      def forward(self, state):
          """Build a network that maps state -> action values."""
          x = F.relu(self.fc1(state))
          x = F.relu(self.fc2(x))
          return self.fc3(x)
  