From 85b3f02af41c5a7b570ef8138ef9004be7606c6c Mon Sep 17 00:00:00 2001
From: jgrusewski <jgrusewski@localhost>
Date: Thu, 12 Mar 2026 21:58:11 +0100
Subject: [PATCH] fix(hyperopt): enforce minimum 5 trials, skip hyperopt when
 trials=0

The hyperopt binary was crashing with "trials (5) must be greater than
n_initial (5)" when --trials 0 was passed. Root cause: the bump logic
set trials = n_initial instead of max(5, n_initial + 1).

Fix: both hyperopt_baseline_rl and hyperopt_baseline_supervised now clamp
trials to max(5, n_initial + 1). Also add `when` condition to the
compile-and-train DAG so hyperopt step is skipped when trials=0, and
train-best gracefully handles missing hyperopt results.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---
 crates/ml/examples/hyperopt_baseline_rl.rs    | 15 ++++++-------
 .../examples/hyperopt_baseline_supervised.rs  | 14 +++++++------
 .../k8s/argo/compile-and-train-template.yaml  | 21 +++++++++++--------
 3 files changed, 28 insertions(+), 22 deletions(-)

diff --git a/crates/ml/examples/hyperopt_baseline_rl.rs b/crates/ml/examples/hyperopt_baseline_rl.rs
index a347c4f0d..f6600e327 100644
--- a/crates/ml/examples/hyperopt_baseline_rl.rs
+++ b/crates/ml/examples/hyperopt_baseline_rl.rs
@@ -509,15 +509,16 @@ fn main() -> Result<()> {
         );
     }
 
-    // Enforce trials > n_initial (ArgminOptimizer needs at least n_initial
-    // LHS exploration rounds + 1 TPE-guided trial to be meaningful)
-    let min_trials = args.n_initial + 1;
-    if args.trials < min_trials {
+    // Enforce minimum 5 trials AND trials > n_initial
+    // (ArgminOptimizer needs at least n_initial LHS rounds + 1 TPE-guided trial)
+    const MIN_TRIALS: usize = 5;
+    let effective_min = MIN_TRIALS.max(args.n_initial + 1);
+    if args.trials < effective_min {
         info!(
-            "Trials {} below minimum (n_initial {} + 1) — bumping to {}",
-            args.trials, args.n_initial, min_trials
+            "Trials {} below minimum {} (floor={}, n_initial {}+1={}) — clamping",
+            args.trials, effective_min, MIN_TRIALS, args.n_initial, args.n_initial + 1
         );
-        args.trials = min_trials;
+        args.trials = effective_min;
     }
 
     // Create output directory
diff --git a/crates/ml/examples/hyperopt_baseline_supervised.rs b/crates/ml/examples/hyperopt_baseline_supervised.rs
index f003eb8d6..2a023f3d4 100644
--- a/crates/ml/examples/hyperopt_baseline_supervised.rs
+++ b/crates/ml/examples/hyperopt_baseline_supervised.rs
@@ -654,14 +654,16 @@ fn main() -> Result<()> {
 
     info!("Models to optimize: {:?}", models);
 
-    // Enforce trials > n_initial (ArgminOptimizer needs LHS exploration + ≥1 TPE trial)
-    let min_trials = args.n_initial + 1;
-    if args.trials < min_trials {
+    // Enforce minimum 5 trials AND trials > n_initial
+    // (ArgminOptimizer needs at least n_initial LHS rounds + 1 TPE-guided trial)
+    const MIN_TRIALS: usize = 5;
+    let effective_min = MIN_TRIALS.max(args.n_initial + 1);
+    if args.trials < effective_min {
         info!(
-            "Trials {} below minimum (n_initial {} + 1) — bumping to {}",
-            args.trials, args.n_initial, min_trials
+            "Trials {} below minimum {} (floor={}, n_initial {}+1={}) — clamping",
+            args.trials, effective_min, MIN_TRIALS, args.n_initial, args.n_initial + 1
         );
-        args.trials = min_trials;
+        args.trials = effective_min;
     }
 
     if let Some(parent) = args.output.parent() {
diff --git a/infra/k8s/argo/compile-and-train-template.yaml b/infra/k8s/argo/compile-and-train-template.yaml
index ef506ff60..6ed5f74c6 100644
--- a/infra/k8s/argo/compile-and-train-template.yaml
+++ b/infra/k8s/argo/compile-and-train-template.yaml
@@ -111,9 +111,10 @@ spec:
           - name: hyperopt
             template: hyperopt
             dependencies: [fetch-binary, gpu-warmup]
+            when: "{{workflow.parameters.hyperopt-trials}} != 0"
           - name: train-best
             template: train-best
-            dependencies: [hyperopt]
+            dependencies: [fetch-binary, gpu-warmup, hyperopt]
           - name: evaluate
             template: evaluate
             dependencies: [train-best]
@@ -431,16 +432,18 @@ spec:
 
             # Determine binary and hyperopt flag
             case "$MODEL" in
-              dqn|ppo)
-                BINARY=train_baseline_rl
-                HYPEROPT_FLAG="--hyperopt-results /workspace/output/${MODEL}_hyperopt_results.json"
-                ;;
-              *)
-                BINARY=train_baseline_supervised
-                HYPEROPT_FLAG="--hyperopt-results /workspace/output/${MODEL}_hyperopt_results.json"
-                ;;
+              dqn|ppo) BINARY=train_baseline_rl ;;
+              *)       BINARY=train_baseline_supervised ;;
             esac
 
+            HYPEROPT_FLAG=""
+            if [ -f "/workspace/output/${MODEL}_hyperopt_results.json" ]; then
+              HYPEROPT_FLAG="--hyperopt-results /workspace/output/${MODEL}_hyperopt_results.json"
+              echo "  Using hyperopt results: ${MODEL}_hyperopt_results.json"
+            else
+              echo "  No hyperopt results — training with default hyperparams"
+            fi
+
             echo "=== Training best: $MODEL ({{workflow.parameters.train-epochs}} epochs) ==="
 
             /workspace/bin/${BINARY} \