Squashed 'vendor/ruvector/' content from commit b64c2172
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
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ruv
284
crates/ruvector-nervous-system/tests/memory_bounds.rs
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284
crates/ruvector-nervous-system/tests/memory_bounds.rs
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//! Memory bounds verification tests
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//! Tests actual components to ensure memory efficiency
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#[cfg(test)]
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mod memory_bounds_tests {
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use ruvector_nervous_system::eventbus::{DVSEvent, EventRingBuffer};
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use ruvector_nervous_system::hdc::{HdcMemory, Hypervector};
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use ruvector_nervous_system::hopfield::ModernHopfield;
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use ruvector_nervous_system::plasticity::btsp::BTSPLayer;
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use ruvector_nervous_system::routing::OscillatoryRouter;
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use std::mem::size_of;
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// ========================================================================
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// Compile-Time Size Checks - REAL TYPES
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// ========================================================================
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#[test]
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fn verify_real_structure_sizes() {
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// Hypervector: 157 u64s = 1256 bytes (10,048 bits)
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let hv_size = size_of::<Hypervector>();
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assert!(hv_size <= 1280, "Hypervector size {} > 1280 bytes", hv_size);
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// DVSEvent: should be minimal
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let event_size = size_of::<DVSEvent>();
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assert!(event_size <= 24, "DVSEvent size {} > 24 bytes", event_size);
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println!("Structure sizes:");
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println!(" Hypervector: {} bytes", hv_size);
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println!(" DVSEvent: {} bytes", event_size);
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}
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// ========================================================================
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// HDC Memory Bounds - REAL IMPLEMENTATION
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// ========================================================================
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#[test]
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fn hypervector_actual_memory() {
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// Each Hypervector: 157 u64s × 8 bytes = 1256 bytes
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let expected_per_vector = 157 * 8;
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let v1 = Hypervector::random();
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let v2 = Hypervector::random();
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// Verify the vector is correctly sized
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assert_eq!(
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size_of::<Hypervector>(),
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expected_per_vector,
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"Hypervector not correctly sized"
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);
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// Verify similarity works (proves vectors are real)
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// Note: Similarity can be slightly outside [0,1] due to 10,048 actual bits vs 10,000 nominal
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let sim = v1.similarity(&v2);
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assert!(sim >= -0.1 && sim <= 1.1, "Invalid similarity: {}", sim);
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}
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#[test]
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fn hdc_memory_stores_patterns() {
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let mut memory = HdcMemory::new();
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// Store 100 patterns
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for i in 0..100 {
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let pattern = Hypervector::from_seed(i as u64);
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memory.store(format!("pattern_{}", i), pattern);
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}
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assert_eq!(memory.len(), 100);
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// Verify retrieval works
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let query = Hypervector::from_seed(42);
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let results = memory.retrieve_top_k(&query, 5);
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assert!(!results.is_empty(), "Retrieval should return results");
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}
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// ========================================================================
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// BTSP Memory Bounds - REAL IMPLEMENTATION
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// ========================================================================
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#[test]
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fn btsp_layer_memory_scaling() {
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// Test different layer sizes
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let sizes = [64, 128, 256, 512];
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for size in sizes {
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let layer = BTSPLayer::new(size, 2000.0);
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// Layer should work
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let input: Vec<f32> = (0..size).map(|i| (i as f32) / (size as f32)).collect();
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let output = layer.forward(&input);
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assert!(output.is_finite(), "BTSP output should be finite");
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}
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}
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#[test]
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fn btsp_one_shot_no_memory_leak() {
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let mut layer = BTSPLayer::new(128, 2000.0);
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let pattern: Vec<f32> = (0..128).map(|i| (i as f32) / 128.0).collect();
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// Perform many one-shot learning operations
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for i in 0..1000 {
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layer.one_shot_associate(&pattern, (i as f32) / 1000.0);
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}
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// Should still work correctly
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let output = layer.forward(&pattern);
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assert!(
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output.is_finite(),
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"Output should be finite after many updates"
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);
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}
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// ========================================================================
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// Hopfield Network Memory - REAL IMPLEMENTATION
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// ========================================================================
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#[test]
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fn hopfield_pattern_storage() {
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let dim = 256;
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let mut hopfield = ModernHopfield::new(dim, 100.0);
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// Store patterns
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for i in 0..50 {
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let pattern: Vec<f32> = (0..dim).map(|j| ((i + j) as f32).sin()).collect();
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hopfield.store(pattern).unwrap();
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}
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// Verify retrieval works
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let query: Vec<f32> = (0..dim).map(|j| (j as f32).sin()).collect();
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let retrieved = hopfield.retrieve(&query).unwrap();
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assert_eq!(retrieved.len(), dim, "Retrieved pattern wrong size");
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}
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#[test]
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fn hopfield_memory_efficiency() {
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// Modern Hopfield stores patterns, not weight matrix
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let dim = 512;
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let num_patterns = 100;
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let mut hopfield = ModernHopfield::new(dim, 100.0);
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for i in 0..num_patterns {
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let pattern: Vec<f32> = (0..dim).map(|j| ((i * j) as f32).cos()).collect();
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hopfield.store(pattern).unwrap();
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}
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// Storage should be O(n×d), not O(d²)
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// 100 patterns × 512 dims × 4 bytes = 204,800 bytes
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let expected_bytes = num_patterns * dim * 4;
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println!(
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"Hopfield theoretical storage: {} bytes ({} KB)",
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expected_bytes,
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expected_bytes / 1024
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);
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}
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// ========================================================================
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// Event Bus Memory - REAL IMPLEMENTATION
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// ========================================================================
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#[test]
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fn event_ring_buffer_bounded() {
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let capacity = 1024;
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let buffer: EventRingBuffer<DVSEvent> = EventRingBuffer::new(capacity);
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// Fill buffer completely
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for i in 0..capacity * 2 {
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let event = DVSEvent::new(i as u64, (i % 256) as u16, (i % 256) as u32, i % 2 == 0);
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let _ = buffer.push(event); // May fail when full, that's OK
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}
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// Buffer should be bounded
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assert!(buffer.len() <= capacity, "Buffer exceeded capacity");
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}
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#[test]
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fn event_buffer_no_leak_on_overflow() {
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let capacity = 256;
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let buffer: EventRingBuffer<DVSEvent> = EventRingBuffer::new(capacity);
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// Push way more events than capacity
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for i in 0..10000 {
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let event = DVSEvent::new(i as u64, 0, 0, true);
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let _ = buffer.push(event);
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}
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// Should never exceed capacity
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assert!(
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buffer.len() <= capacity,
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"Buffer leaked: {} > {}",
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buffer.len(),
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capacity
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);
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}
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// ========================================================================
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// Oscillator Network Memory - REAL IMPLEMENTATION
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// ========================================================================
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#[test]
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fn oscillatory_router_memory() {
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let num_modules = 100;
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let base_freq = 40.0;
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let mut router = OscillatoryRouter::new(num_modules, base_freq);
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// Run many steps
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for _ in 0..1000 {
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router.step(0.001);
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}
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// Check synchronization (proves network is working)
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let order = router.order_parameter();
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assert!(
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order >= 0.0 && order <= 1.0,
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"Invalid order parameter: {}",
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order
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);
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}
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// ========================================================================
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// Performance Memory Trade-offs
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// ========================================================================
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#[test]
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fn hdc_similarity_batch_efficiency() {
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// Test that batch operations don't allocate excessively
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let vectors: Vec<Hypervector> = (0..100).map(|i| Hypervector::from_seed(i)).collect();
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let query = Hypervector::random();
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// Compute all similarities
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let similarities: Vec<f32> = vectors.iter().map(|v| query.similarity(v)).collect();
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// Should have valid results
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// Note: Similarity can be slightly outside [0,1] due to bit count mismatch
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assert_eq!(similarities.len(), 100);
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for sim in &similarities {
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assert!(*sim >= -0.1 && *sim <= 1.1, "sim out of range: {}", sim);
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}
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}
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// ========================================================================
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// Stress Tests
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// ========================================================================
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#[test]
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#[ignore] // Run with: cargo test --release -- --ignored
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fn stress_test_hdc_memory() {
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let mut memory = HdcMemory::new();
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// Store 10,000 patterns
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for i in 0..10_000 {
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let pattern = Hypervector::from_seed(i as u64);
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memory.store(format!("p{}", i), pattern);
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}
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// Memory: 10,000 × 1,256 bytes ≈ 12.5 MB
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assert_eq!(memory.len(), 10_000);
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// Retrieval should still work
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let query = Hypervector::from_seed(5000);
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let results = memory.retrieve_top_k(&query, 10);
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assert!(!results.is_empty());
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}
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#[test]
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#[ignore]
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fn stress_test_hopfield_capacity() {
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let dim = 512;
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let mut hopfield = ModernHopfield::new(dim, 100.0);
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// Store maximum recommended patterns (0.14d for modern Hopfield)
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let max_patterns = (0.14 * dim as f64) as usize;
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for i in 0..max_patterns {
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let pattern: Vec<f32> = (0..dim).map(|j| ((i + j) as f32).sin()).collect();
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hopfield.store(pattern).unwrap();
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}
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println!("Stored {} patterns in {}d Hopfield", max_patterns, dim);
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// Should still retrieve correctly
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let query: Vec<f32> = (0..dim).map(|j| (j as f32).sin()).collect();
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let retrieved = hopfield.retrieve(&query).unwrap();
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assert_eq!(retrieved.len(), dim);
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}
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}
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