#!/usr/bin/env python3
"""
Test rapido per verificare correzioni Tesla M60 in analisys_04.py
"""

import os
import sys

def test_tesla_m60_config():
    """Test configurazione Tesla M60"""
    print("🧪 TEST CONFIGURAZIONE TESLA M60")
    print("=" * 50)
    
    try:
        # Test import TensorFlow con configurazione Tesla M60
        os.environ['TF_CPP_MIN_LOG_LEVEL'] = '1'
        # ⚡ CRITICO: Configurazione Tesla M60 CC 5.2 ⚡
        os.environ['TF_GPU_ALLOCATOR'] = 'legacy'  # Necessario per CC 5.2
        print("🔧 TF_GPU_ALLOCATOR=legacy configurato per Tesla M60 CC 5.2")
        import tensorflow as tf
        print(f"✅ TensorFlow {tf.__version__} importato")
        
        # Test GPU detection
        gpus = tf.config.list_physical_devices('GPU')
        print(f"✅ GPU rilevate: {len(gpus)}")
        
        if gpus:
            gpu = gpus[0]
            print(f"   GPU: {gpu}")
            
            # Test memory growth (sicuro)
            try:
                tf.config.experimental.set_memory_growth(gpu, True)
                print("✅ Memory growth configurato")
                memory_config = "memory_growth"
            except ValueError as e:
                if "virtual devices" in str(e):
                    print("ℹ️ Virtual devices già configurati")
                    memory_config = "virtual_device"
                else:
                    print(f"⚠️ Memory config error: {e}")
                    memory_config = "error"
            
            # Test mixed precision (con warning atteso)
            try:
                policy = tf.keras.mixed_precision.Policy('mixed_float16')
                tf.keras.mixed_precision.set_global_policy(policy)
                print("⚠️ Mixed precision abilitato (warning CC 5.2 atteso)")
            except Exception as e:
                print(f"❌ Mixed precision fallito: {e}")
                # Fallback FP32
                policy = tf.keras.mixed_precision.Policy('float32')
                tf.keras.mixed_precision.set_global_policy(policy)
                print("✅ Fallback FP32 configurato")
            
            # Test operazione GPU semplice
            try:
                with tf.device('/GPU:0'):
                    a = tf.constant([[1.0, 2.0], [3.0, 4.0]])
                    b = tf.constant([[1.0, 0.0], [0.0, 1.0]])
                    c = tf.matmul(a, b)
                    result = c.numpy()
                print(f"✅ Test operazione GPU: {result.shape}")
            except Exception as e:
                print(f"❌ Test GPU fallito: {e}")
            
            return True
        else:
            print("❌ Nessuna GPU rilevata")
            return False
            
    except Exception as e:
        print(f"❌ Test fallito: {e}")
        return False

def test_batch_sizes():
    """Test calcolo batch sizes"""
    print("\n🧪 TEST BATCH SIZES DINAMICI")
    print("=" * 50)
    
    # Simulazione batch size calculation
    available_memory_gb = 7.0  # Tesla M60 conservativo
    feature_count = 280
    memory_per_sample_mb = (feature_count * 4) / 1024 / 1024
    max_samples = int((available_memory_gb * 1024) / memory_per_sample_mb * 0.3)
    
    batch_sizes = {
        'feature_extraction': min(max_samples * 2, 8000),
        'model_training': min(max_samples, 2048),
        'prediction': min(max_samples * 3, 10000),
        'autoencoder': min(max_samples // 2, 1024),
        'lstm_sequence': min(max_samples, 4096),
    }
    
    print(f"✅ Feature count: {feature_count}")
    print(f"✅ Memory per sample: {memory_per_sample_mb:.3f} MB")
    print(f"✅ Max samples in memory: {max_samples:,}")
    print("✅ Batch sizes calcolati:")
    for name, size in batch_sizes.items():
        print(f"   {name}: {size:,}")
    
    return True

def main():
    """Main test"""
    print("🚀 TEST CORREZIONI TESLA M60 per analisys_04.py")
    print("=" * 60)
    
    success = True
    
    # Test configurazione
    if not test_tesla_m60_config():
        success = False
    
    # Test batch sizes
    if not test_batch_sizes():
        success = False
    
    print("\n" + "=" * 60)
    if success:
        print("🎉 TUTTI I TEST SUPERATI!")
        print("✅ analisys_04.py dovrebbe funzionare correttamente")
        print("\n💡 Comando suggerito:")
        print("   python analisys_04.py --max-records 80000 --demo")
    else:
        print("❌ ALCUNI TEST FALLITI")
        print("⚠️ Verificare configurazione Tesla M60")
    
    return success

if __name__ == "__main__":
    success = main()
    sys.exit(0 if success else 1)