foxhunt/scripts/validate_train_script.sh

#!/bin/bash
# Validates that train_all_models_fixed.sh uses correct commands
# Does NOT run full training (too expensive), just validates structure

set -e

echo "🔍 Validating train_all_models_fixed.sh..."
echo ""

SCRIPT_PATH="scripts/train_all_models_fixed.sh"

# 1. Check script exists
if [ ! -f "$SCRIPT_PATH" ]; then
    echo "❌ Script not found: $SCRIPT_PATH"
    exit 1
fi
echo "✅ Script exists: $SCRIPT_PATH"

# 2. Check script is executable or can be made executable
if [ ! -x "$SCRIPT_PATH" ]; then
    chmod +x "$SCRIPT_PATH"
    echo "✅ Made script executable"
else
    echo "✅ Script already executable"
fi

# 3. Check bash syntax
if bash -n "$SCRIPT_PATH"; then
    echo "✅ Bash syntax valid"
else
    echo "❌ Bash syntax errors found"
    exit 1
fi

# 4. Verify it uses correct cargo commands
if grep -q 'cargo run -p ml --example "train_${MODEL_TYPE}"' "$SCRIPT_PATH"; then
    echo "✅ Uses correct cargo run pattern"
else
    echo "❌ Incorrect cargo command pattern"
    exit 1
fi

# 5. Verify it passes correct arguments
REQUIRED_ARGS=("epochs" "learning-rate" "batch-size" "output-dir" "verbose")
for arg in "${REQUIRED_ARGS[@]}"; do
    if grep -q "\-\-$arg" "$SCRIPT_PATH"; then
        echo "✅ Passes argument: --$arg"
    else
        echo "❌ Missing argument: --$arg"
        exit 1
    fi
done

# 6. Verify model types are correct
MODELS=("dqn" "ppo" "mamba2" "tft")
for model in "${MODELS[@]}"; do
    if grep -q "\"$model\"" "$SCRIPT_PATH"; then
        echo "✅ Includes model: $model"
    else
        echo "❌ Missing model: $model"
        exit 1
    fi
done

# 7. Check GPU detection
if grep -q "nvidia-smi" "$SCRIPT_PATH"; then
    echo "✅ Includes GPU detection"
else
    echo "⚠️  No GPU detection (warning only)"
fi

# 8. Check output directory creation
if grep -q "mkdir -p" "$SCRIPT_PATH"; then
    echo "✅ Creates output directory"
else
    echo "❌ Missing output directory creation"
    exit 1
fi

# 9. Verify uses --release and --features cuda
if grep -q "\-\-release \-\-features cuda" "$SCRIPT_PATH"; then
    echo "✅ Uses release build with CUDA"
else
    echo "⚠️  Missing --release or --features cuda (warning only)"
fi

# 10. Check logging
if grep -q "tee.*training.log" "$SCRIPT_PATH"; then
    echo "✅ Logs training output"
else
    echo "⚠️  No training log capture (warning only)"
fi

echo ""
echo "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
echo "✅ All Validation Checks Passed!"
echo "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
echo ""
echo "📋 Script Summary:"
echo "   • Location: $SCRIPT_PATH"
echo "   • Models: ${MODELS[*]}"
echo "   • Arguments: ${REQUIRED_ARGS[*]}"
echo "   • GPU: Required (nvidia-smi check)"
echo "   • Build: Release with CUDA features"
echo ""
echo "🚀 Ready to train! Run:"
echo "   bash $SCRIPT_PATH"
echo ""