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torch.nn.functional.max_pool1d
torch.nn.functional.max_pool1d(input, kernel_size, stride=None, padding=0, dilation=1, ceil_mode=False, return_indices=False)
-
Applies a 1D max pooling over an input signal composed of several input planes.
Note
The order of
ceil_mode
andreturn_indices
is different from what seen inMaxPool1d
, and will change in a future release.See
MaxPool1d
for details.- Parameters
-
- input – input tensor of shape , minibatch dim optional.
- kernel_size – the size of the window. Can be a single number or a tuple
(kW,)
- stride – the stride of the window. Can be a single number or a tuple
(sW,)
. Default:kernel_size
- padding – Implicit negative infinity padding to be added on both sides, must be >= 0 and <= kernel_size / 2.
- dilation – The stride between elements within a sliding window, must be > 0.
- ceil_mode – If
True
, will useceil
instead offloor
to compute the output shape. This ensures that every element in the input tensor is covered by a sliding window. - return_indices – If
True
, will return the argmax along with the max values. Useful fortorch.nn.functional.max_unpool1d
later
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https://pytorch.org/docs/2.1/generated/torch.nn.functional.max_pool1d.html