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-rw-r--r--code/sunlab/suntorch/models/variational/decoder.py33
1 files changed, 33 insertions, 0 deletions
diff --git a/code/sunlab/suntorch/models/variational/decoder.py b/code/sunlab/suntorch/models/variational/decoder.py
new file mode 100644
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+++ b/code/sunlab/suntorch/models/variational/decoder.py
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+import torch.nn as nn
+import torch.nn.functional as F
+from torch import sigmoid
+
+
+class Decoder(nn.Module):
+ """# Decoder Neural Network
+ X_dim: Output dimension shape
+ N: Inner neuronal layer size
+ z_dim: Input dimension shape
+ """
+
+ def __init__(self, X_dim, N, z_dim, dropout=0.0, negative_slope=0.3):
+ super(Decoder, self).__init__()
+ self.lin1 = nn.Linear(z_dim, N)
+ self.lin2 = nn.Linear(N, N)
+ self.lin3 = nn.Linear(N, X_dim)
+ self.p = dropout
+ self.negative_slope = negative_slope
+
+ def forward(self, x):
+ x = self.lin1(x)
+ if self.p > 0.0:
+ x = F.dropout(x, p=self.p, training=self.training)
+ x = F.leaky_relu(x, negative_slope=self.negative_slope)
+
+ x = self.lin2(x)
+ if self.p > 0.0:
+ x = F.dropout(x, p=self.p, training=self.training)
+ x = F.leaky_relu(x, negative_slope=self.negative_slope)
+
+ x = self.lin3(x)
+ return sigmoid(x)