Merge commit 'd803bfe2b1fe7f5e219e50ac20d6801a0a58ac75' as 'vendor/ruvector'

vendor/ruvector/examples/rust/gnn_example.rs

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+//! Example demonstrating the Ruvector GNN layer usage
+
+use ruvector_gnn::{RuvectorLayer, Linear, MultiHeadAttention, GRUCell, LayerNorm};
+
+fn main() {
+    println!("=== Ruvector GNN Layer Example ===\n");
+
+    // Create a GNN layer
+    // Parameters: input_dim=128, hidden_dim=256, heads=4, dropout=0.1
+    let gnn_layer = RuvectorLayer::new(128, 256, 4, 0.1);
+
+    // Simulate a node embedding (128 dimensions)
+    let node_embedding = vec![0.5; 128];
+
+    // Simulate 3 neighbor embeddings
+    let neighbor_embeddings = vec![
+        vec![0.3; 128],
+        vec![0.7; 128],
+        vec![0.5; 128],
+    ];
+
+    // Edge weights (e.g., inverse distances)
+    let edge_weights = vec![0.8, 0.6, 0.4];
+
+    // Forward pass through the GNN layer
+    let updated_embedding = gnn_layer.forward(&node_embedding, &neighbor_embeddings, &edge_weights);
+
+    println!("Input dimension: {}", node_embedding.len());
+    println!("Output dimension: {}", updated_embedding.len());
+    println!("Number of neighbors: {}", neighbor_embeddings.len());
+    println!("\n✓ GNN layer forward pass successful!");
+
+    // Demonstrate individual components
+    println!("\n=== Individual Components ===\n");
+
+    // 1. Linear layer
+    let linear = Linear::new(128, 64);
+    let linear_output = linear.forward(&node_embedding);
+    println!("Linear layer: 128 -> {}", linear_output.len());
+
+    // 2. Layer normalization
+    let layer_norm = LayerNorm::new(128, 1e-5);
+    let normalized = layer_norm.forward(&node_embedding);
+    println!("LayerNorm output dimension: {}", normalized.len());
+
+    // 3. Multi-head attention
+    let attention = MultiHeadAttention::new(128, 4);
+    let keys = neighbor_embeddings.clone();
+    let values = neighbor_embeddings.clone();
+    let attention_output = attention.forward(&node_embedding, &keys, &values);
+    println!("Multi-head attention output: {}", attention_output.len());
+
+    // 4. GRU cell
+    let gru = GRUCell::new(128, 256);
+    let hidden_state = vec![0.0; 256];
+    let new_hidden = gru.forward(&node_embedding, &hidden_state);
+    println!("GRU cell output dimension: {}", new_hidden.len());
+
+    println!("\n✓ All components working correctly!");
+}