Model from nature paper
@@ -67,17 +67,19 @@ class DQN(nn.Module):
super(DQN, self).__init__()
self.conv = nn.Sequential(
- nn.Conv2d(input_shape[0], 16, kernel_size=8, stride=4),
+ nn.Conv2d(input_shape[0], 32, kernel_size=8, stride=4),
nn.ReLU(),
- nn.Conv2d(16, 32, kernel_size=4, stride=2),
+ nn.Conv2d(32, 64, kernel_size=4, stride=2),
nn.ReLU(),
+ nn.Conv2d(64, 64, kernel_size=3, stride=1),
+ nn.ReLU()
)
conv_out_size = self._get_conv_out(input_shape)
self.fc = nn.Sequential(
- nn.Linear(conv_out_size, 256),
+ nn.Linear(conv_out_size, 512),
nn.ReLU(),
- nn.Linear(256, n_actions)
+ nn.Linear(512, n_actions)
)
def _get_conv_out(self, shape):
