torch_npu.npu_max(self, dim, keepdim=False) -> (Tensor, Tensor)
使用dim对最大结果进行计数。类似于torch.max, 优化NPU设备实现。
>>> input = torch.randn(2, 2, 2, 2, dtype = torch.float32).npu()
>>> input
tensor([[[[-1.8135, 0.2078],
[-0.6678, 0.7846]],
[[ 0.6458, -0.0923],
[-0.2124, -1.9112]]],
[[[-0.5800, -0.4979],
[ 0.2580, 1.1335]],
[[ 0.6669, 0.1876],
[ 0.1160, -0.1061]]]], device='npu:0')
>>> outputs, indices = torch_npu.npu_max(input, 2)
>>> outputs
tensor([[[-0.6678, 0.7846],
[ 0.6458, -0.0923]],
[[ 0.2580, 1.1335],
[ 0.6669, 0.1876]]], device='npu:0')
>>> indices
tensor([[[1, 1],
[0, 0]],
[[1, 1],
[0, 0]]], device='npu:0', dtype=torch.int32)