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PyTorch Distributed Training Scalable distributed training and performance optimization in research and production is enabled by the torch distributed backend
PyTorch 教程 | 菜鸟教程 创建张量： torch randn(2, 3) 创建一个 2 行 3 列的张量，填充随机数（遵循正态分布）。 device=device 和 dtype=dtype 分别指定了计算设备（CPU 或 GPU）和数据类型（浮点型）。 张量操作： a * b：逐元素相乘。 a sum()：计算张量 a 所有元素的和。