详解PyTorch中Tensor的高阶操作

> import torch
> c = randn(2, 3)
> c
tensor([[ 0.0309, -1.5993, 0.1986],
    [-0.0699, -2.7813, -1.1828]])
> a = torch.ones(2, 3)
> a
tensor([[1., 1., 1.],
    [1., 1., 1.]])
> b = torch.zeros(2, 3)
> b
tensor([[0., 0., 0.],
    [0., 0., 0.]])
> torch.where(c > 0, a, b)
tensor([[1., 0., 1.],
    [0., 0., 0.]])

> a = torch.randn(4, 10)
> b = a.topk(3, dim = 1)
> b
(tensor([[ 1.0134, 0.8785, -0.0373],
    [ 1.4378, 1.4022, 1.0115],
    [ 0.8985, 0.6795, 0.6439],
    [ 1.2758, 1.0294, 1.0075]]), tensor([[5, 7, 6],
    [2, 5, 8],
    [5, 9, 2],
    [7, 9, 6]]))
> index = b[1]
> index
tensor([[5, 7, 6],
    [2, 5, 8],
    [5, 9, 2],
    [7, 9, 6]])
> label = torch.arange(10) + 100
> label
tensor([100, 101, 102, 103, 104, 105, 106, 107, 108, 109])
> torch.gather(label.expand(4, 10), dim=1, index=index.long()) # 进行聚合操作
tensor([[105, 107, 106],
    [102, 105, 108],
    [105, 109, 102],
    [107, 109, 106]])