0bfe3258b5
Replit-Commit-Author: Agent Replit-Commit-Session-Id: 7a657272-55ba-4a79-9a2e-f1ed9bc7a528 Replit-Commit-Checkpoint-Type: full_checkpoint Replit-Commit-Event-Id: 1c71ce6e-1a3e-4f53-bb5d-77cdd22b8ea3
133 lines
4.6 KiB
Python
133 lines
4.6 KiB
Python
#!/usr/bin/env python3
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"""
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Test rapido per verificare correzioni Tesla M60 in analisys_04.py
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"""
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import os
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import sys
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def test_tesla_m60_config():
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"""Test configurazione Tesla M60"""
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print("🧪 TEST CONFIGURAZIONE TESLA M60")
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print("=" * 50)
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try:
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# Test import TensorFlow con configurazione Tesla M60
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os.environ['TF_CPP_MIN_LOG_LEVEL'] = '1'
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# ⚡ CRITICO: Configurazione Tesla M60 CC 5.2 ⚡
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os.environ['TF_GPU_ALLOCATOR'] = 'legacy' # Necessario per CC 5.2
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print("🔧 TF_GPU_ALLOCATOR=legacy configurato per Tesla M60 CC 5.2")
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import tensorflow as tf
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print(f"✅ TensorFlow {tf.__version__} importato")
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# Test GPU detection
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gpus = tf.config.list_physical_devices('GPU')
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print(f"✅ GPU rilevate: {len(gpus)}")
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if gpus:
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gpu = gpus[0]
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print(f" GPU: {gpu}")
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# Test memory growth (sicuro)
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try:
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tf.config.experimental.set_memory_growth(gpu, True)
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print("✅ Memory growth configurato")
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memory_config = "memory_growth"
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except ValueError as e:
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if "virtual devices" in str(e):
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print("ℹ️ Virtual devices già configurati")
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memory_config = "virtual_device"
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else:
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print(f"⚠️ Memory config error: {e}")
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memory_config = "error"
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# Test mixed precision (con warning atteso)
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try:
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policy = tf.keras.mixed_precision.Policy('mixed_float16')
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tf.keras.mixed_precision.set_global_policy(policy)
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print("⚠️ Mixed precision abilitato (warning CC 5.2 atteso)")
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except Exception as e:
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print(f"❌ Mixed precision fallito: {e}")
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# Fallback FP32
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policy = tf.keras.mixed_precision.Policy('float32')
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tf.keras.mixed_precision.set_global_policy(policy)
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print("✅ Fallback FP32 configurato")
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# Test operazione GPU semplice
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try:
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with tf.device('/GPU:0'):
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a = tf.constant([[1.0, 2.0], [3.0, 4.0]])
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b = tf.constant([[1.0, 0.0], [0.0, 1.0]])
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c = tf.matmul(a, b)
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result = c.numpy()
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print(f"✅ Test operazione GPU: {result.shape}")
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except Exception as e:
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print(f"❌ Test GPU fallito: {e}")
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return True
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else:
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print("❌ Nessuna GPU rilevata")
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return False
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except Exception as e:
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print(f"❌ Test fallito: {e}")
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return False
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def test_batch_sizes():
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"""Test calcolo batch sizes"""
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print("\n🧪 TEST BATCH SIZES DINAMICI")
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print("=" * 50)
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# Simulazione batch size calculation
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available_memory_gb = 7.0 # Tesla M60 conservativo
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feature_count = 280
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memory_per_sample_mb = (feature_count * 4) / 1024 / 1024
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max_samples = int((available_memory_gb * 1024) / memory_per_sample_mb * 0.3)
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batch_sizes = {
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'feature_extraction': min(max_samples * 2, 8000),
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'model_training': min(max_samples, 2048),
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'prediction': min(max_samples * 3, 10000),
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'autoencoder': min(max_samples // 2, 1024),
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'lstm_sequence': min(max_samples, 4096),
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}
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print(f"✅ Feature count: {feature_count}")
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print(f"✅ Memory per sample: {memory_per_sample_mb:.3f} MB")
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print(f"✅ Max samples in memory: {max_samples:,}")
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print("✅ Batch sizes calcolati:")
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for name, size in batch_sizes.items():
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print(f" {name}: {size:,}")
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return True
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def main():
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"""Main test"""
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print("🚀 TEST CORREZIONI TESLA M60 per analisys_04.py")
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print("=" * 60)
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success = True
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# Test configurazione
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if not test_tesla_m60_config():
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success = False
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# Test batch sizes
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if not test_batch_sizes():
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success = False
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print("\n" + "=" * 60)
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if success:
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print("🎉 TUTTI I TEST SUPERATI!")
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print("✅ analisys_04.py dovrebbe funzionare correttamente")
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print("\n💡 Comando suggerito:")
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print(" python analisys_04.py --max-records 80000 --demo")
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else:
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print("❌ ALCUNI TEST FALLITI")
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print("⚠️ Verificare configurazione Tesla M60")
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return success
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if __name__ == "__main__":
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success = main()
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sys.exit(0 if success else 1) |