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作者还尝试了混合精度的方法，例如用 bfloat16 精度训练专家，同时对其余计算使用全精度进行。较低的精度可以减少处理器间的通信成本、计算成本以及存储 tensor 的内存。然而，在最初的实验中，当专家和门控网络都使用 bfloat16 精度训练时，出现了不稳定的训练
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