training/test_setup.py

#!/usr/bin/env python3
import torch
import transformers
import peft
import datasets
import evaluate
import sklearn
import wandb
import tensorboard

print('✅ Alle Training-Pakete erfolgreich importiert!')
print(f'🚀 PyTorch Version: {torch.__version__}')
print(f'🤖 Transformers Version: {transformers.__version__}')
print(f'🔧 PEFT Version: {peft.__version__}')
print(f'📊 Datasets Version: {datasets.__version__}')
print(f'🎯 CUDA verfügbar: {torch.cuda.is_available()}')

if torch.cuda.is_available():
    print(f'📱 GPU: {torch.cuda.get_device_name(0)}')
    print(f'💾 VRAM: {torch.cuda.get_device_properties(0).total_memory / 1024**3:.1f} GB')
else:
    print('💻 CPU-Modus (kein CUDA)')

print('\n🎯 Hardware-Empfehlungen für LoRA-Training:')
print('• Minimum: 8GB RAM + 4GB VRAM')
print('• Empfohlen: 16GB RAM + 8GB VRAM') 
print('• Optimal: 32GB RAM + 16GB+ VRAM')