英文:
Pytorch how to convert each element of tensor into tensors?
问题
将如下张量：
> tensor([ 0.5324, -0.1281, 0.0565, 0.0114])
转换为：
> tensor([ [0.5324], [-0.1281], [0.0565], [0.0114] ])
使每个元素都成为一个张量本身。是否有简单的方法可以做到这一点？谢谢
英文:
if I have tensor like this:
> tensor([ 0.5324, -0.1281, 0.0565, 0.0114])
and I want to convert into:
> tensor([ [0.5324], [-0.1281], [0.0565], [0.0114] ])
so each element is tensor itself. Is there any easy way to do this?
Thank you
答案1
得分: 0
是的，可以轻松实现所需的转换。您可以使用PyTorch中的unsqueeze()函数向您的张量添加额外的维度。以下是如何做到这一点的示例：
import torch
original_tensor = torch.tensor([0.5324, -0.1281, 0.0565, 0.0114])
converted_tensor = original_tensor.unsqueeze(1)
print(converted_tensor)
输出：
tensor([[ 0.5324],
[-0.1281],
[ 0.0565],
[ 0.0114]])
unsqueeze()函数接受一个参数dim，该参数指定您要插入额外维度的位置。在这种情况下，dim=1表示您希望将额外的维度插入为一列，从而将每个元素转换为其自己的张量。
请注意，生成的张量的形状将为(4, 1)，而不是原始张量中的(4,)，反映了添加的维度。
英文:
Yes, there is an easy way to achieve the desired conversion. You can use the unsqueeze() function in PyTorch to add an extra dimension to your tensor. Here's how you can do it:
import torch
original_tensor = torch.tensor([0.5324, -0.1281, 0.0565, 0.0114])
converted_tensor = original_tensor.unsqueeze(1)
print(converted_tensor)
Output:
tensor([[ 0.5324],
[-0.1281],
[ 0.0565],
[ 0.0114]])
The unsqueeze() function takes an argument dim which specifies the position where you want to insert the extra dimension. In this case, dim=1 means you want to insert the extra dimension as a column, effectively transforming each element into its own tensor.
Note that the resulting tensor will have shape (4, 1) instead of (4,) as in the original tensor, reflecting the added dimension.
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