Linux PyTorch内存占用高怎么解决

<code>import torch
<h1>假设你有一个模型和一些张量</h1><p>model = ...
tensor1 = ...
tensor2 = ...</p><h1>训练循环结束后</h1><p>del tensor1
del tensor2
torch.cuda.empty_cache()</code>

<code>from torch.cuda.amp import GradScaler, autocast</p><p>scaler = GradScaler()</p>
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                <p>for data, target in dataloader:
optimizer.zero_grad()</p><pre class="brush:php;toolbar:false;"><code>with autocast():
    output = model(data)
    loss = criterion(output, target)

scaler.scale(loss).backward()
scaler.step(optimizer)
scaler.update()</code></pre><p>通过以上方法，可以更好地控制和优化PyTorch训练过程中的内存使用情况。</p></code>