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feat(hyperopt): make TPE the default optimizer

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Change --optimizer default from "pso" to "tpe" since TPE has better
sample efficiency in 25D spaces. Fix clippy let_underscore_must_use
on CUDA sync tensor readback.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
jgrusewski
2026-03-03 18:50:02 +01:00
parent c29fafbbb6
commit 6d0182d77e
2 changed files with 3 additions and 3 deletions
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4
crates/ml/examples/hyperopt_baseline_rl.rs
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@@ -104,8 +104,8 @@ struct Args {
#[arg(long, default_value = "1.0")]
spread_ticks: f64,
/// Optimizer to use: "pso" (Particle Swarm) or "tpe" (Tree-Parzen Estimator)
#[arg(long, default_value = "pso")]
/// Optimizer to use: "tpe" (Tree-Parzen Estimator) or "pso" (Particle Swarm)
#[arg(long, default_value = "tpe")]
optimizer: String,
/// Number of parallel trial evaluations (PSO only; TPE is always sequential).

2
crates/ml/src/hyperopt/adapters/dqn.rs
View File

@@ -2950,7 +2950,7 @@ impl HyperparameterOptimizable for DQNTrainer {
if let Ok(sync_tensor) =
candle_core::Tensor::zeros(1, candle_core::DType::F32, &cleanup_device)
{
let _ = sync_tensor.to_vec0::<f32>();
drop(sync_tensor.to_vec0::<f32>());
}
// Brief pause to allow CUDA memory allocator to reclaim freed blocks
std::thread::sleep(std::time::Duration::from_millis(50));