torch (version 0.14.2)

nn_max_unpool1d: Computes a partial inverse of MaxPool1d.

Description

MaxPool1d is not fully invertible, since the non-maximal values are lost. MaxUnpool1d takes in as input the output of MaxPool1d including the indices of the maximal values and computes a partial inverse in which all non-maximal values are set to zero.

Usage

nn_max_unpool1d(kernel_size, stride = NULL, padding = 0)

Arguments

kernel_size

(int or tuple): Size of the max pooling window.

stride

(int or tuple): Stride of the max pooling window. It is set to kernel_size by default.

padding

(int or tuple): Padding that was added to the input

Inputs

• input: the input Tensor to invert

• indices: the indices given out by nn_max_pool1d()

• output_size (optional): the targeted output size

Shape

• Input: $(N,C,H_{in})$

• Output: $(N,C,H_{out})$, where $$H_{out}=(H_{in}-1)\times \text{stride}[0]-2\times \text{padding}[0]+\text{kernel\_size}[0]$$ or as given by output_size in the call operator

Examples

if (torch_is_installed()) {
pool <- nn_max_pool1d(2, stride = 2, return_indices = TRUE)
unpool <- nn_max_unpool1d(2, stride = 2)

input <- torch_tensor(array(1:8 / 1, dim = c(1, 1, 8)))
out <- pool(input)
unpool(out[[1]], out[[2]])

# Example showcasing the use of output_size
input <- torch_tensor(array(1:8 / 1, dim = c(1, 1, 8)))
out <- pool(input)
unpool(out[[1]], out[[2]], output_size = input$size())
unpool(out[[1]], out[[2]])
}