9c3d741a08
Move 17 library crates into crates/, CLI binary into bin/fxt, consolidate 10 test crates into testing/, split config crate from deployment config files. Root directory reduced from 38+ to ~17 directories. All Cargo.toml paths and build.rs proto refs updated. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
80 lines
2.9 KiB
Rust
80 lines
2.9 KiB
Rust
// Minimal test to verify PPO minibatch_size fix
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// Run with: cargo run --example test_ppo_fix --features cuda
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use ml::hyperopt::adapters::ppo::PPOParams;
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use ml::hyperopt::traits::ParameterSpace;
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fn main() {
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println!("Testing PPO minibatch_size parameter integration...\n");
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// Test 1: Roundtrip for each valid divisor
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let valid_divisors = [64, 128, 256, 512, 1024, 2048];
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for &size in &valid_divisors {
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let params = PPOParams {
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policy_learning_rate: 1e-5,
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value_learning_rate: 1e-4,
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clip_epsilon: 0.2,
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value_loss_coeff: 1.0,
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entropy_coeff: 0.01,
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minibatch_size: size,
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};
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let continuous = params.to_continuous();
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let recovered = PPOParams::from_continuous(&continuous).expect("Failed to recover params");
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assert_eq!(
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recovered.minibatch_size, size,
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"Roundtrip failed for minibatch_size={}",
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size
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);
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println!("✓ Roundtrip test passed for minibatch_size={}", size);
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}
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// Test 2: Verify discrete sampling
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println!("\nTesting discrete sampling from continuous space...");
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for idx in 0..=5 {
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let continuous = vec![
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1e-5_f64.ln(), // policy_learning_rate
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1e-4_f64.ln(), // value_learning_rate
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0.2, // clip_epsilon
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1.0, // value_loss_coeff
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0.01_f64.ln(), // entropy_coeff
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idx as f64, // minibatch_size index
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];
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let params = PPOParams::from_continuous(&continuous).expect("Failed to parse params");
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let expected = valid_divisors[idx];
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assert_eq!(
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params.minibatch_size, expected,
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"Index {} should map to {}",
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idx, expected
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);
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println!("✓ Index {} -> minibatch_size={}", idx, expected);
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}
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// Test 3: Verify bounds
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println!("\nTesting bounds...");
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let bounds = PPOParams::continuous_bounds();
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assert_eq!(bounds.len(), 6, "Should have 6 parameters");
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assert_eq!(bounds[5], (0.0, 5.0), "Minibatch index should be [0, 5]");
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println!("✓ Bounds test passed: {:?}", bounds[5]);
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// Test 4: Verify parameter names
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println!("\nTesting parameter names...");
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let names = PPOParams::param_names();
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assert_eq!(names.len(), 6, "Should have 6 parameter names");
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assert_eq!(
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names[5], "minibatch_size",
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"6th parameter should be 'minibatch_size'"
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);
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println!("✓ Parameter names test passed: {}", names[5]);
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println!("\n✅ ALL TESTS PASSED! Bug #1 fix verified.");
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println!("\nSummary:");
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println!(" - File: ml/src/hyperopt/adapters/ppo.rs line 385");
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println!(" - Fix: Changed `mini_batch_size: 512` to `mini_batch_size: params.minibatch_size`");
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println!(" - Impact: Hyperopt now correctly samples minibatch_size from [64, 128, 256, 512, 1024, 2048]");
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}
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