0fa7aa41c0
- DQN: adapter creation, deterministic inference, varied inputs - PPO: adapter creation, deterministic inference, short input padding - TFT: sequence buffering, valid prediction after warmup - Mamba2: sequence buffering, valid prediction, deterministic SSM - Ensemble: all 4 models -> EnsembleCoordinator -> trading decision - Smoke: full pipeline with 10 sequential predictions, stability check This establishes the production baseline proving the ML pipeline works end-to-end with all 4 models contributing to ensemble decisions. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
89 lines
2.5 KiB
Rust
89 lines
2.5 KiB
Rust
//! PPO model integration test
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//!
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//! Verifies: create model -> forward pass -> valid output with padding
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//! Uses lightweight config for fast execution (<10s)
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use ml::ensemble::adapters::PpoInferenceAdapter;
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use ml::ensemble::inference_adapter::{FeatureVector, ModelInferenceAdapter};
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use ml::ppo::ppo::PPOConfig;
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fn small_ppo_config() -> PPOConfig {
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PPOConfig {
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state_dim: 64,
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num_actions: 45,
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policy_hidden_dims: vec![32, 32],
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value_hidden_dims: vec![32, 32],
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..Default::default()
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}
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}
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#[test]
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fn test_ppo_adapter_produces_valid_prediction() {
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let adapter =
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PpoInferenceAdapter::new(small_ppo_config()).expect("PpoInferenceAdapter::new should succeed");
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assert_eq!(adapter.model_name(), "PPO");
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assert!(adapter.is_ready());
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// 51-dim input gets zero-padded to state_dim=64
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let fv = FeatureVector {
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values: vec![0.1; 51],
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timestamp: 1_700_000_000_000_000,
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};
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let pred = adapter.predict(&fv).expect("PPO predict should succeed");
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assert!(
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pred.direction >= -1.0 && pred.direction <= 1.0,
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"direction {} out of [-1,1]",
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pred.direction
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);
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assert!(
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pred.confidence >= 0.0 && pred.confidence <= 1.0,
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"confidence {} out of [0,1]",
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pred.confidence
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);
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assert!(pred.direction.is_finite(), "direction must not be NaN/Inf");
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assert!(
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pred.confidence.is_finite(),
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"confidence must not be NaN/Inf"
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);
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}
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#[test]
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fn test_ppo_deterministic_inference() {
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let adapter =
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PpoInferenceAdapter::new(small_ppo_config()).expect("PpoInferenceAdapter::new should succeed");
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let fv = FeatureVector {
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values: vec![0.3; 51],
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timestamp: 1_700_000_000_000_000,
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};
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let pred1 = adapter.predict(&fv).expect("predict 1");
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let pred2 = adapter.predict(&fv).expect("predict 2");
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assert_eq!(
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pred1.direction, pred2.direction,
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"PPO inference should be deterministic"
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);
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}
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#[test]
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fn test_ppo_handles_short_input() {
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let adapter =
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PpoInferenceAdapter::new(small_ppo_config()).expect("PpoInferenceAdapter::new should succeed");
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// 10-dim input (much shorter than state_dim=64) should still work via padding
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let fv = FeatureVector {
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values: vec![0.5; 10],
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timestamp: 1_700_000_000_000_000,
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};
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let pred = adapter
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.predict(&fv)
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.expect("PPO should handle short input via padding");
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assert!(pred.direction.is_finite());
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assert!(pred.confidence.is_finite());
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}
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