Files
foxhunt/crates/ml/tests/bug20_portfolio_normalization_test.rs
jgrusewski ca4c38d921 fix(tests): CI GPU test stability, walltime reduction, BF16 tolerance
- 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>
2026-03-15 12:00:13 +01:00

200 lines
6.3 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,
)]
// Bug #20: Portfolio value normalization test
// Tests that portfolio value is normalized by initial_capital
// to prevent 100,000x feature imbalance
use anyhow::Result;
use ml::dqn::portfolio_tracker::PortfolioTracker;
use tracing::info;
#[test]
fn test_portfolio_value_normalized_to_baseline() -> Result<()> {
// Bug #20: Portfolio value should be normalized to ~1.0 baseline
let initial_capital = 100_000.0;
let avg_spread = 0.0001;
let cash_reserve_percent = 0.0;
let tracker = PortfolioTracker::new(initial_capital, avg_spread, cash_reserve_percent);
// At start, portfolio value = initial_capital
let features = tracker.get_portfolio_features(4000.0);
// Bug #20: Feature should be 1.0 (normalized), NOT 100,000
assert_eq!(features.len(), 3, "Should have 3 portfolio features");
let portfolio_feature = features[0];
// After fix, this should be ~1.0 (normalized by initial_capital)
// Before fix, this would be 100,000.0 (raw value)
assert!(
(portfolio_feature - 1.0).abs() < 0.01,
"Portfolio value should be normalized to 1.0, got: {}",
portfolio_feature
);
info!(portfolio_feature, "Portfolio value normalized correctly");
Ok(())
}
#[test]
fn test_all_portfolio_features_similar_scale() -> Result<()> {
// Bug #20: All portfolio features should be in similar scale
// No 100,000x imbalance
let initial_capital = 100_000.0;
let avg_spread = 0.0001;
let cash_reserve_percent = 0.0;
let tracker = PortfolioTracker::new(initial_capital, avg_spread, cash_reserve_percent);
let features = tracker.get_portfolio_features(4000.0);
// Check all features are in reasonable scale (NOT 100,000x difference)
for (i, &feature) in features.iter().enumerate() {
assert!(
feature.abs() < 10.0,
"Feature {} should be in reasonable scale, got: {}",
i,
feature
);
}
info!(?features, "All portfolio features in similar scale");
Ok(())
}
#[test]
fn test_feature_scale_consistency() -> Result<()> {
// Bug #20: Verify portfolio features don't dominate other features
// The key test is that portfolio value is NOT 100,000 (raw value)
let initial_capital = 100_000.0;
let avg_spread = 0.0001;
let cash_reserve_percent = 0.0;
let tracker = PortfolioTracker::new(initial_capital, avg_spread, cash_reserve_percent);
let features = tracker.get_portfolio_features(4000.0);
// The key fix: Portfolio value should be ~1.0 (normalized), NOT 100,000
let portfolio_value = features[0];
// Before Bug #20 fix: Would be 100,000.0 (raw value)
// After Bug #20 fix: Should be ~1.0 (normalized)
assert!(
portfolio_value.abs() < 10.0,
"Portfolio value should be normalized, got: {}",
portfolio_value
);
// Check that portfolio value doesn't dwarf other features by 100,000x
// (spread is intentionally small, but that's OK - key is portfolio isn't massive)
let max_feature = features.iter().copied().fold(f32::NEG_INFINITY, f32::max);
// Before fix: max_feature would be 100,000 (raw portfolio value)
// After fix: max_feature should be ~1.0 (normalized portfolio value)
assert!(
max_feature < 10.0,
"Max feature should be in normalized scale, got: {}",
max_feature
);
info!(max_feature, portfolio_value, "Feature scale check passed");
Ok(())
}
#[test]
fn test_portfolio_feature_format() -> Result<()> {
// Test that get_portfolio_features returns 3 features:
// [portfolio_value, position_normalized, spread]
let tracker = PortfolioTracker::new(100_000.0, 0.0001, 0.0);
let features = tracker.get_portfolio_features(4000.0);
assert_eq!(features.len(), 3, "Should return exactly 3 features");
// Feature 0: Portfolio value (should be normalized to ~1.0)
// Feature 1: Position (normalized by max_position)
// Feature 2: Spread
info!(?features, "Portfolio features");
info!(value = features[0], "Feature 0 (portfolio value)");
info!(position = features[1], "Feature 1 (position)");
info!(spread = features[2], "Feature 2 (spread)");
Ok(())
}