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Use ReLU with normalization

This commit is contained in:
Mattéo Delabre 2019-12-15 00:03:20 -05:00
parent 197a01e993
commit 6d31ab3a13
Signed by: matteo
GPG Key ID: AE3FBD02DC583ABB
1 changed files with 4 additions and 3 deletions
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constellation/ConstellationNet.py
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@ -36,12 +36,13 @@ class ConstellationNet(nn.Module):
for layer_size in encoder_layers_sizes:
encoder_layers.append(nn.Linear(prev_layer_size, layer_size))
encoder_layers.append(nn.Tanh())
encoder_layers.append(nn.ReLU())
prev_layer_size = layer_size
encoder_layers += [
nn.Linear(prev_layer_size, 2),
nn.Tanh(),
nn.ReLU(),
nn.BatchNorm1d(2),
]
self.encoder = nn.Sequential(*encoder_layers)
@ -56,7 +57,7 @@ class ConstellationNet(nn.Module):
for layer_size in decoder_layers_sizes:
decoder_layers.append(nn.Linear(prev_layer_size, layer_size))
decoder_layers.append(nn.Tanh())
decoder_layers.append(nn.ReLU())
prev_layer_size = layer_size
# Softmax is not used at the end of the network because the