On this page
AdaptiveAvgPool2d
class torch.nn.AdaptiveAvgPool2d(output_size)
[source]-
Applies a 2D adaptive average pooling over an input signal composed of several input planes.
The output is of size H x W, for any input size. The number of output features is equal to the number of input planes.
- Parameters
-
output_size (Union[int, None, Tuple[Optional[int], Optional[int]]]) – the target output size of the image of the form H x W. Can be a tuple (H, W) or a single H for a square image H x H. H and W can be either a
int
, orNone
which means the size will be the same as that of the input.
- Shape:
-
- Input: or .
- Output: or , where .
Examples
>>> # target output size of 5x7 >>> m = nn.AdaptiveAvgPool2d((5, 7)) >>> input = torch.randn(1, 64, 8, 9) >>> output = m(input) >>> # target output size of 7x7 (square) >>> m = nn.AdaptiveAvgPool2d(7) >>> input = torch.randn(1, 64, 10, 9) >>> output = m(input) >>> # target output size of 10x7 >>> m = nn.AdaptiveAvgPool2d((None, 7)) >>> input = torch.randn(1, 64, 10, 9) >>> output = m(input)
© 2024, PyTorch Contributors
PyTorch has a BSD-style license, as found in the LICENSE file.
https://pytorch.org/docs/2.1/generated/torch.nn.AdaptiveAvgPool2d.html