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diff --git a/code/sunlab/suntorch/models/variational/encoder.py b/code/sunlab/suntorch/models/variational/encoder.py
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+++ b/code/sunlab/suntorch/models/variational/encoder.py
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+import torch.nn as nn
+import torch.nn.functional as F
+
+
+class Encoder(nn.Module):
+    """# Encoder Neural Network
+    X_dim: Input dimension shape
+    N: Inner neuronal layer size
+    z_dim: Output dimension shape
+    """
+
+    def __init__(self, X_dim, N, z_dim, dropout=0.0, negative_slope=0.3):
+        super(Encoder, self).__init__()
+        self.lin1 = nn.Linear(X_dim, N)
+        self.lin2 = nn.Linear(N, N)
+        self.lin3mu = nn.Linear(N, z_dim)
+        self.lin3sigma = nn.Linear(N, z_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)
+
+        mu = self.lin3mu(x)
+        sigma = self.lin3sigma(x)
+        return mu, sigma