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PyTorch GPU 内存分析(memory profiling)的实践指南:梯度检查点、混合 ...
模型有 2 亿个参数,fp32 精度下理论上只需 800 MB。为什么 24 GB 的 GPU 却满了?原因在于模型参数只是训练期间占用 GPU 内存的七种因素之一。了解这七个原因才能从靠猜转变为凭工程的判断。 所以保守估计总计,一个"理论上"只需 800 MB 的模型,实际要占用 5–8 GB。
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