optimize.py

import torch
from torch.utils.cpp_extension import CUDA_HOME

def optimize_model(model):
    """Apply various optimizations"""
    # Mixed precision
    model.half()
    
    # CUDA optimizations
    if torch.cuda.is_available():
        model = model.to('cuda')
        torch.backends.cudnn.benchmark = True
        torch.backends.cuda.matmul.allow_tf32 = True
    
    # Compile with torch.compile (PyTorch 2.0+)
    if hasattr(torch, 'compile'):
        model = torch.compile(model, mode="reduce-overhead")
    
    return model

def memory_optimization():
    """Memory optimization techniques"""
    torch.cuda.empty_cache()
    torch.backends.cudnn.deterministic = False