v10.1.6: Restore missing PositionalEncoding class

app.py

@@ -75,6 +75,27 @@ device = None
 MAX_DIM = 2048
 DEFAULT_DIM = 1024
 
+# ============================================================================
+# L18.5: VL-JEPA PAPER-FAITHFUL IMPLEMENTATION
+# ============================================================================
+
+class PositionalEncoding(nn.Module):
+    """Positional encoding for Transformer (paper-style)."""
+    def __init__(self, d_model, max_len=512, dropout=0.1):
+        super().__init__()
+        self.dropout = nn.Dropout(p=dropout)
+        
+        pe = torch.zeros(max_len, d_model)
+        position = torch.arange(0, max_len, dtype=torch.float).unsqueeze(1)
+        div_term = torch.exp(torch.arange(0, d_model, 2).float() * (-math.log(10000.0) / d_model))
+        pe[:, 0::2] = torch.sin(position * div_term)
+        pe[:, 1::2] = torch.cos(position * div_term)
+        self.register_buffer('pe', pe.unsqueeze(0))
+    
+    def forward(self, x):
+        x = x + self.pe[:, :x.size(1)]
+        return self.dropout(x)
+
 class VLJEPAPredictor(nn.Module):
     """
     VL-JEPA Predictor v10.1 (Paper-Faithful Sequence)