- Reduce CI GPU test datasets 16x for walltime reduction - Reduce early-stop epochs 50→10, add --test-threads=1 - Serialize all GPU lib tests to prevent cuBLAS init race - Align state_dim to 16 for BF16 tensor core HMMA dispatch - BF16 precision tolerance in ml-dqn tests - Enable branching DQN + tracing subscriber in smoke tests - Prevent min_replay_size > buffer_size deadlock in early-stop tests - Prevent AutoReplaySizer from breaking gradient collapse warmup - Replace racy tokio::spawn checkpoint counter with AtomicUsize - Set warmup_steps=0 and max_training_steps_per_epoch=300 in early-stop tests - RealDataLoader respects TEST_DATA_DIR for CI PVC layout - Add collapse_warmup_capacity to gpu_smoketest DQNConfig - Drain CUDA context between test binaries - Detached HEAD checkout prevents local branch corruption - GPU pipeline tests: fix BF16 dtype and rank-1 squeeze assertions - OOD input handling tests use use_gpu: true Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
471 lines
15 KiB
Rust
471 lines
15 KiB
Rust
#![allow(
|
|
clippy::assertions_on_constants,
|
|
clippy::assertions_on_result_states,
|
|
clippy::clone_on_copy,
|
|
clippy::decimal_literal_representation,
|
|
clippy::doc_markdown,
|
|
clippy::empty_line_after_doc_comments,
|
|
clippy::field_reassign_with_default,
|
|
clippy::get_unwrap,
|
|
clippy::identity_op,
|
|
clippy::inconsistent_digit_grouping,
|
|
clippy::indexing_slicing,
|
|
clippy::integer_division,
|
|
clippy::len_zero,
|
|
clippy::let_underscore_must_use,
|
|
clippy::manual_div_ceil,
|
|
clippy::manual_let_else,
|
|
clippy::manual_range_contains,
|
|
clippy::modulo_arithmetic,
|
|
clippy::needless_range_loop,
|
|
clippy::non_ascii_literal,
|
|
clippy::redundant_clone,
|
|
clippy::shadow_reuse,
|
|
clippy::shadow_same,
|
|
clippy::shadow_unrelated,
|
|
clippy::single_match_else,
|
|
clippy::str_to_string,
|
|
clippy::string_slice,
|
|
clippy::tests_outside_test_module,
|
|
clippy::too_many_lines,
|
|
clippy::unnecessary_wraps,
|
|
clippy::unseparated_literal_suffix,
|
|
clippy::use_debug,
|
|
clippy::useless_vec,
|
|
clippy::wildcard_enum_match_arm,
|
|
clippy::else_if_without_else,
|
|
clippy::expect_used,
|
|
clippy::missing_const_for_fn,
|
|
clippy::similar_names,
|
|
clippy::type_complexity,
|
|
clippy::collapsible_else_if,
|
|
clippy::doc_lazy_continuation,
|
|
clippy::items_after_test_module,
|
|
clippy::map_clone,
|
|
clippy::multiple_unsafe_ops_per_block,
|
|
clippy::unwrap_or_default,
|
|
clippy::assign_op_pattern,
|
|
clippy::needless_borrow,
|
|
clippy::println_empty_string,
|
|
clippy::unnecessary_cast,
|
|
clippy::used_underscore_binding,
|
|
clippy::create_dir,
|
|
clippy::implicit_saturating_sub,
|
|
clippy::exit,
|
|
clippy::expect_fun_call,
|
|
clippy::too_many_arguments,
|
|
clippy::unnecessary_map_or,
|
|
clippy::unwrap_used,
|
|
dead_code,
|
|
unused_imports,
|
|
unused_variables,
|
|
clippy::cloned_ref_to_slice_refs,
|
|
clippy::neg_multiply,
|
|
clippy::while_let_loop,
|
|
clippy::bool_assert_comparison,
|
|
clippy::excessive_precision,
|
|
clippy::trivially_copy_pass_by_ref,
|
|
clippy::op_ref,
|
|
clippy::redundant_closure,
|
|
clippy::unnecessary_lazy_evaluations,
|
|
clippy::if_then_some_else_none,
|
|
clippy::unnecessary_to_owned,
|
|
clippy::single_component_path_imports,
|
|
)]
|
|
//! Integration tests for ensemble checkpoint hot-swapping
|
|
//!
|
|
//! Tests the complete hot-swap workflow:
|
|
//! 1. Load DQN checkpoint into active buffer
|
|
//! 2. Stage new checkpoint in shadow buffer
|
|
//! 3. Validate staged checkpoint (1000 predictions, latency checks)
|
|
//! 4. Commit atomic swap (<1μs)
|
|
//! 5. Verify active buffer now points to new checkpoint
|
|
//! 6. Test rollback mechanism
|
|
|
|
use ml::ensemble::{
|
|
CheckpointModel, CheckpointValidator, EnsembleMetrics, HotSwapManager, RollbackPolicy,
|
|
};
|
|
use ml::{Features, MLResult, ModelPrediction};
|
|
use std::sync::Arc;
|
|
use std::time::Instant;
|
|
use tracing::info;
|
|
|
|
/// Mock prediction function for DQN epoch 30
|
|
fn create_dqn_epoch_30_predictor(
|
|
) -> Arc<dyn Fn(&Features) -> MLResult<ModelPrediction> + Send + Sync> {
|
|
Arc::new(|features: &Features| {
|
|
let value = (features.values.iter().sum::<f64>() / features.values.len() as f64) * 0.8;
|
|
Ok(ModelPrediction::new(
|
|
"DQN_epoch_30".to_string(),
|
|
value.tanh(),
|
|
0.78,
|
|
))
|
|
})
|
|
}
|
|
|
|
/// Mock prediction function for DQN epoch 50 (improved)
|
|
fn create_dqn_epoch_50_predictor(
|
|
) -> Arc<dyn Fn(&Features) -> MLResult<ModelPrediction> + Send + Sync> {
|
|
Arc::new(|features: &Features| {
|
|
let value = (features.values.iter().sum::<f64>() / features.values.len() as f64) * 0.9;
|
|
Ok(ModelPrediction::new(
|
|
"DQN_epoch_50".to_string(),
|
|
value.tanh(),
|
|
0.85,
|
|
))
|
|
})
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_hot_swap_workflow_complete() {
|
|
info!("Hot-Swap Workflow Test");
|
|
|
|
// Initialize hot-swap manager
|
|
let validator = CheckpointValidator::new();
|
|
let policy = RollbackPolicy::default();
|
|
let manager = HotSwapManager::new(validator, policy);
|
|
|
|
// Step 1: Load DQN epoch 30 into active buffer
|
|
info!("Step 1: Loading DQN epoch 30 into active buffer");
|
|
let checkpoint_v30 = Arc::new(CheckpointModel::new(
|
|
"DQN".to_string(),
|
|
"ml/checkpoints/dqn/checkpoint_epoch_30.safetensors".to_string(),
|
|
create_dqn_epoch_30_predictor(),
|
|
));
|
|
|
|
manager
|
|
.register_model("DQN".to_string(), checkpoint_v30)
|
|
.await
|
|
.expect("Failed to register model");
|
|
|
|
let active = manager.get_active_checkpoint("DQN").await.unwrap();
|
|
assert_eq!(
|
|
active.checkpoint_path,
|
|
"ml/checkpoints/dqn/checkpoint_epoch_30.safetensors"
|
|
);
|
|
info!(checkpoint_path = %active.checkpoint_path, "Active checkpoint loaded");
|
|
|
|
// Step 2: Stage DQN epoch 50 in shadow buffer
|
|
info!("Step 2: Staging DQN epoch 50 in shadow buffer");
|
|
let checkpoint_v50 = Arc::new(CheckpointModel::new(
|
|
"DQN".to_string(),
|
|
"ml/checkpoints/dqn/checkpoint_epoch_50.safetensors".to_string(),
|
|
create_dqn_epoch_50_predictor(),
|
|
));
|
|
|
|
manager
|
|
.stage_checkpoint("DQN", checkpoint_v50)
|
|
.await
|
|
.expect("Failed to stage checkpoint");
|
|
info!("Staged checkpoint in shadow buffer");
|
|
|
|
// Step 3: Validate staged checkpoint
|
|
info!("Step 3: Validating staged checkpoint (1000 predictions)");
|
|
let validation_start = Instant::now();
|
|
let validation = manager
|
|
.validate_staged_checkpoint("DQN")
|
|
.await
|
|
.expect("Failed to validate checkpoint");
|
|
let validation_duration = validation_start.elapsed();
|
|
|
|
assert!(
|
|
validation.passed,
|
|
"Validation failed: {:?}",
|
|
validation.failure_reason
|
|
);
|
|
assert!(
|
|
validation.p99_latency_us < 50,
|
|
"P99 latency {}μs exceeds 50μs",
|
|
validation.p99_latency_us
|
|
);
|
|
assert!(
|
|
validation.predictions_in_range >= 950,
|
|
"Only {} predictions in range",
|
|
validation.predictions_in_range
|
|
);
|
|
|
|
info!("Validation PASSED");
|
|
info!(avg_latency_us = validation.avg_latency_us, "Avg latency");
|
|
info!(p99_latency_us = validation.p99_latency_us, "P99 latency");
|
|
info!(
|
|
predictions_in_range = validation.predictions_in_range,
|
|
predictions_validated = validation.predictions_validated,
|
|
validation_duration_ms = validation_duration.as_millis(),
|
|
"Validation predictions in range"
|
|
);
|
|
|
|
// Record metrics
|
|
EnsembleMetrics::record_validation(
|
|
"DQN",
|
|
true,
|
|
validation_duration.as_millis() as u64,
|
|
validation.p99_latency_us,
|
|
);
|
|
|
|
// Step 4: Commit atomic swap
|
|
info!("Step 4: Committing atomic swap");
|
|
let swap_latency = manager
|
|
.commit_swap("DQN")
|
|
.await
|
|
.expect("Failed to commit swap");
|
|
|
|
assert!(
|
|
swap_latency.as_micros() < 100,
|
|
"Swap latency {}μs exceeds 100μs",
|
|
swap_latency.as_micros()
|
|
);
|
|
|
|
info!(swap_latency_us = swap_latency.as_micros(), "Atomic swap completed");
|
|
|
|
// Record metrics
|
|
EnsembleMetrics::record_swap_success("DQN", swap_latency.as_micros() as u64);
|
|
|
|
// Step 5: Verify active checkpoint is now epoch 50
|
|
info!("Step 5: Verifying active checkpoint");
|
|
let active = manager.get_active_checkpoint("DQN").await.unwrap();
|
|
assert_eq!(
|
|
active.checkpoint_path,
|
|
"ml/checkpoints/dqn/checkpoint_epoch_50.safetensors"
|
|
);
|
|
info!(checkpoint_path = %active.checkpoint_path, "Active checkpoint loaded");
|
|
|
|
// Test prediction with new checkpoint
|
|
let features = Features::new(
|
|
vec![0.5, 0.6, 0.7, 0.8, 0.9],
|
|
vec![
|
|
"f1".to_string(),
|
|
"f2".to_string(),
|
|
"f3".to_string(),
|
|
"f4".to_string(),
|
|
"f5".to_string(),
|
|
],
|
|
);
|
|
|
|
let prediction = active.predict(&features).unwrap();
|
|
assert_eq!(prediction.model_id, "DQN_epoch_50");
|
|
assert!(prediction.confidence >= 0.85);
|
|
info!(
|
|
value = prediction.value,
|
|
confidence = prediction.confidence,
|
|
"Prediction with new checkpoint"
|
|
);
|
|
|
|
info!("Hot-Swap Workflow Test PASSED");
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_hot_swap_rollback() {
|
|
info!("Hot-Swap Rollback Test");
|
|
|
|
let validator = CheckpointValidator::new();
|
|
let policy = RollbackPolicy::default();
|
|
let manager = HotSwapManager::new(validator, policy);
|
|
|
|
// Register initial checkpoint
|
|
let checkpoint_v30 = Arc::new(CheckpointModel::new(
|
|
"DQN".to_string(),
|
|
"checkpoint_epoch_30.safetensors".to_string(),
|
|
create_dqn_epoch_30_predictor(),
|
|
));
|
|
|
|
manager
|
|
.register_model("DQN".to_string(), checkpoint_v30)
|
|
.await
|
|
.unwrap();
|
|
|
|
// Stage and commit new checkpoint
|
|
let checkpoint_v50 = Arc::new(CheckpointModel::new(
|
|
"DQN".to_string(),
|
|
"checkpoint_epoch_50.safetensors".to_string(),
|
|
create_dqn_epoch_50_predictor(),
|
|
));
|
|
|
|
manager
|
|
.stage_checkpoint("DQN", checkpoint_v50)
|
|
.await
|
|
.unwrap();
|
|
manager.commit_swap("DQN").await.unwrap();
|
|
|
|
// Verify new checkpoint is active
|
|
let active = manager.get_active_checkpoint("DQN").await.unwrap();
|
|
assert_eq!(active.checkpoint_path, "checkpoint_epoch_50.safetensors");
|
|
info!("Swapped to epoch 50");
|
|
|
|
// Simulate failure and rollback
|
|
info!("Simulating failure and rolling back");
|
|
manager.rollback("DQN").await.unwrap();
|
|
|
|
// Verify rollback restored epoch 30
|
|
let active = manager.get_active_checkpoint("DQN").await.unwrap();
|
|
assert_eq!(active.checkpoint_path, "checkpoint_epoch_30.safetensors");
|
|
info!("Rolled back to epoch 30");
|
|
|
|
// Record metrics
|
|
EnsembleMetrics::record_swap_rollback("DQN");
|
|
EnsembleMetrics::record_rollback("DQN", "test_failure");
|
|
|
|
info!("Rollback Test PASSED");
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_swap_latency_benchmark() {
|
|
info!("Swap Latency Benchmark");
|
|
|
|
let validator = CheckpointValidator::new();
|
|
let policy = RollbackPolicy::default();
|
|
let manager = HotSwapManager::new(validator, policy);
|
|
|
|
// Register initial checkpoint
|
|
let checkpoint_v1 = Arc::new(CheckpointModel::new(
|
|
"DQN".to_string(),
|
|
"checkpoint_v1.safetensors".to_string(),
|
|
create_dqn_epoch_30_predictor(),
|
|
));
|
|
|
|
manager
|
|
.register_model("DQN".to_string(), checkpoint_v1)
|
|
.await
|
|
.unwrap();
|
|
|
|
// Run 100 swap operations to benchmark
|
|
let mut swap_latencies = Vec::new();
|
|
|
|
for i in 0..100 {
|
|
let checkpoint = Arc::new(CheckpointModel::new(
|
|
"DQN".to_string(),
|
|
format!("checkpoint_v{}.safetensors", i + 2),
|
|
create_dqn_epoch_50_predictor(),
|
|
));
|
|
|
|
manager.stage_checkpoint("DQN", checkpoint).await.unwrap();
|
|
|
|
let swap_latency = manager.commit_swap("DQN").await.unwrap();
|
|
swap_latencies.push(swap_latency.as_micros() as u64);
|
|
}
|
|
|
|
// Calculate statistics
|
|
swap_latencies.sort_unstable();
|
|
let avg_latency = swap_latencies.iter().sum::<u64>() / swap_latencies.len() as u64;
|
|
let p50_latency = swap_latencies[50];
|
|
let p99_latency = swap_latencies[99];
|
|
|
|
info!("Swap latency statistics (100 swaps)");
|
|
info!(avg_latency_us = avg_latency, "Average swap latency");
|
|
info!(p50_latency_us = p50_latency, "P50 swap latency");
|
|
info!(p99_latency_us = p99_latency, "P99 swap latency");
|
|
info!(min_latency_us = swap_latencies[0], "Min swap latency");
|
|
info!(max_latency_us = swap_latencies[99], "Max swap latency");
|
|
|
|
// All swaps should be < 1μs (but we allow 100μs for CI/testing)
|
|
assert!(
|
|
p99_latency < 100,
|
|
"P99 swap latency {}μs exceeds 100μs",
|
|
p99_latency
|
|
);
|
|
|
|
info!("Swap Latency Benchmark PASSED");
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_zero_dropped_predictions() {
|
|
info!("Zero Dropped Predictions Test");
|
|
|
|
let validator = CheckpointValidator::new();
|
|
let policy = RollbackPolicy::default();
|
|
let manager = HotSwapManager::new(validator, policy);
|
|
|
|
// Register initial checkpoint
|
|
let checkpoint_v30 = Arc::new(CheckpointModel::new(
|
|
"DQN".to_string(),
|
|
"checkpoint_epoch_30.safetensors".to_string(),
|
|
create_dqn_epoch_30_predictor(),
|
|
));
|
|
|
|
manager
|
|
.register_model("DQN".to_string(), checkpoint_v30)
|
|
.await
|
|
.unwrap();
|
|
|
|
// Spawn prediction workload (1000 predictions in background)
|
|
let manager_clone = Arc::new(manager);
|
|
let prediction_task = {
|
|
let manager = manager_clone.clone();
|
|
tokio::spawn(async move {
|
|
let mut success_count = 0;
|
|
let mut error_count = 0;
|
|
|
|
for i in 0..1000 {
|
|
let features = Features::new(
|
|
vec![
|
|
(i as f64 * 0.01).sin(),
|
|
(i as f64 * 0.02).cos(),
|
|
(i as f64 * 0.03).tanh(),
|
|
(i as f64 * 0.01 + 1.0).ln(),
|
|
(i as f64 * 0.001).exp().min(10.0),
|
|
],
|
|
vec![
|
|
"f1".to_string(),
|
|
"f2".to_string(),
|
|
"f3".to_string(),
|
|
"f4".to_string(),
|
|
"f5".to_string(),
|
|
],
|
|
);
|
|
|
|
match manager.get_active_checkpoint("DQN").await {
|
|
Ok(checkpoint) => match checkpoint.predict(&features) {
|
|
Ok(_) => success_count += 1,
|
|
Err(_) => error_count += 1,
|
|
},
|
|
Err(_) => error_count += 1,
|
|
}
|
|
|
|
// Small delay to simulate realistic prediction rate
|
|
tokio::time::sleep(tokio::time::Duration::from_micros(100)).await;
|
|
}
|
|
|
|
(success_count, error_count)
|
|
})
|
|
};
|
|
|
|
// Wait a bit for predictions to start
|
|
tokio::time::sleep(tokio::time::Duration::from_millis(10)).await;
|
|
|
|
// Perform hot-swap while predictions are running
|
|
info!("Performing hot-swap during active predictions");
|
|
let checkpoint_v50 = Arc::new(CheckpointModel::new(
|
|
"DQN".to_string(),
|
|
"checkpoint_epoch_50.safetensors".to_string(),
|
|
create_dqn_epoch_50_predictor(),
|
|
));
|
|
|
|
manager_clone
|
|
.stage_checkpoint("DQN", checkpoint_v50)
|
|
.await
|
|
.unwrap();
|
|
let swap_latency = manager_clone.commit_swap("DQN").await.unwrap();
|
|
info!(swap_latency_us = swap_latency.as_micros(), "Hot-swap completed during active predictions");
|
|
|
|
// Wait for prediction task to complete
|
|
let (success_count, error_count) = prediction_task.await.unwrap();
|
|
|
|
info!("Prediction results during hot-swap");
|
|
info!(success_count, "Successful predictions");
|
|
info!(error_count, "Error predictions");
|
|
info!(total = success_count + error_count, "Total predictions");
|
|
|
|
// Verify zero dropped predictions (all predictions should succeed)
|
|
assert_eq!(
|
|
error_count, 0,
|
|
"Found {} dropped predictions during hot-swap",
|
|
error_count
|
|
);
|
|
assert_eq!(
|
|
success_count, 1000,
|
|
"Expected 1000 successful predictions, got {}",
|
|
success_count
|
|
);
|
|
|
|
info!("Zero Dropped Predictions Test PASSED");
|
|
}
|