AdaptiveMaxPool2d¶
-
class
torch.nn.
AdaptiveMaxPool2d
(output_size, return_indices=False)[source]¶ Applies a 2D adaptive max pooling over an input signal composed of several input planes.
The output is of size , for any input size. The number of output features is equal to the number of input planes.
- Parameters
output_size – the target output size of the image of the form . Can be a tuple or a single for a square image . and can be either a
int
, orNone
which means the size will be the same as that of the input.return_indices – if
True
, will return the indices along with the outputs. Useful to pass to nn.MaxUnpool2d. Default:False
- Shape:
Input: or .
Output: or , where .
Examples
>>> # target output size of 5x7 >>> m = nn.AdaptiveMaxPool2d((5,7)) >>> input = torch.randn(1, 64, 8, 9) >>> output = m(input) >>> # target output size of 7x7 (square) >>> m = nn.AdaptiveMaxPool2d(7) >>> input = torch.randn(1, 64, 10, 9) >>> output = m(input) >>> # target output size of 10x7 >>> m = nn.AdaptiveMaxPool2d((None, 7)) >>> input = torch.randn(1, 64, 10, 9) >>> output = m(input)