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  1. class Actor(nn.Module):
  2.     """Actor (Policy) Model."""
  3.  
  4.     def __init__(self, state_size, action_size, seed, fc_units=256):
  5.         """Initialize parameters and build model.
  6.         Params
  7.         ======
  8.             state_size (int): Dimension of each state
  9.             action_size (int): Dimension of each action
  10.             seed (int): Random seed
  11.             fc1_units (int): Number of nodes in first hidden layer
  12.             fc2_units (int): Number of nodes in second hidden layer
  13.         """
  14.         super(Actor, self).__init__()
  15.         self.seed = torch.manual_seed(seed)
  16.         self.fc1 = nn.Linear(state_size, fc_units)
  17.         self.fc2 = nn.Linear(fc_units, action_size)
  18.         self.reset_parameters()
  19.  
  20.     def reset_parameters(self):
  21.         self.fc1.weight.data.uniform_(*hidden_init(self.fc1))
  22.         self.fc2.weight.data.uniform_(-3e-3, 3e-3)
  23.  
  24.     def forward(self, state):
  25.         """Build an actor (policy) network that maps states -> actions."""
  26.         x = F.relu(self.fc1(state))
  27.         return F.tanh(self.fc2(x))
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