oneflow.nn.AdaptiveMaxPool1d¶
-
class
oneflow.nn.
AdaptiveMaxPool1d
(output_size, return_indices: bool = False)¶ Applies a 1D adaptive max pooling over an input signal composed of several input planes.
The documentation is referenced from: https://pytorch.org/docs/1.10/generated/torch.nn.AdaptiveMaxPool1d.html.
The output size is \(L_{out}\), for any input size. The number of output features is equal to the number of input planes.
- Parameters
output_size – the target output size \(L_{out}\).
return_indices – if
True
, will return the indices along with the outputs. Default:False
- Shape:
Input: \((N, C, L_{in})\).
Output: \((N, C, L_{out})\), where \(L_{out}=\text{output_size}\).
Examples:
>>> import oneflow as flow >>> # target output size of 5 >>> m = flow.nn.AdaptiveMaxPool1d(5) >>> input = flow.randn(1, 64, 8) >>> output = m(input) >>> print(output.shape) oneflow.Size([1, 64, 5])