如何从张量中获取一列? [英] How to get a column from a tensor?

问题描述

假设我有一个由 1 和 0 组成的张量，如下所示.如何获取特定列的索引以替换新值?如果我想用 [3.,4.,5.,6.] 替换第 1 列的值，我该如何实现?

Let's say I have a tensor consisting of 1 and 0's as shown below. How can I get the index of a specific column to replace with new values ? If I want to replace the values of column 1 with the [3.,4.,5.,6.], how do I accomplish this ?

a = torch.tensor([[[1., 0., 0., 0.]],
        [[0., 1., 0., 0.]],
        [[1., 0., 0., 0.]],
        [[0., 0., 0., 1.]],
        [[1., 0., 0., 0.]],
        [[0., 0., 0., 1.]],
        [[1., 0., 0., 0.]]])

推荐答案

将它们称为列"有点棘手，因为这是一个 3D 张量.

Calling them 'columns' is a bit tricky, given that this is a 3D tensor.

这将满足您的需求，将列"1 设置为您提供的值.

This will do what you need, setting 'column' 1 to the values you gave.

a = torch.tensor([[[1., 0., 0., 0.]],
        [[0., 1., 0., 0.]],
        [[1., 0., 0., 0.]],
        [[0., 0., 0., 1.]],
        [[1., 0., 0., 0.]],
        [[0., 0., 0., 1.]],
        [[1., 0., 0., 0.]]])

# Change values in 'column' 1 (zero-indexed):
# The 0 is there because of the size-1 second dimension.
a[1, 0, :] = torch.tensor([3., 4., 5., 6.])

print(a)
# tensor([[[1., 0., 0., 0.]],
#         [[3., 4., 5., 6.]],
#         [[1., 0., 0., 0.]],
#         [[0., 0., 0., 1.]],
#         [[1., 0., 0., 0.]],
#         [[0., 0., 0., 1.]],
#         [[1., 0., 0., 0.]]])

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