x = x.view(B, H, W, C) x0 = x[:, 0::2, 0::2, :]
时间: 2024-06-03 10:09:05 浏览: 9
These two lines of code are used to downsample an image tensor by a factor of 2 in both the height and width dimensions, while preserving the number of channels.
The first line reshapes the tensor `x` to have dimensions `(B, H, W, C)`, where `B` is the batch size, `H` is the height, `W` is the width, and `C` is the number of channels.
The second line selects every second element along the height and width dimensions, starting from the 0th index. This effectively downsamples the tensor by a factor of 2 in both dimensions, resulting in a tensor with dimensions `(B, H/2, W/2, C)`.
For example, if `x` had dimensions `(1, 4, 4, 3)`, the first line would reshape it to `(1, 4, 4, 3)`, and the second line would select every second element along the height and width dimensions, resulting in a tensor with dimensions `(1, 2, 2, 3)`.
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