torch_conv2d {torch} | R Documentation |
Conv2d
Description
Conv2d
Usage
torch_conv2d(
input,
weight,
bias = list(),
stride = 1L,
padding = 0L,
dilation = 1L,
groups = 1L
)
Arguments
input |
input tensor of shape |
weight |
filters of shape |
bias |
optional bias tensor of shape |
stride |
the stride of the convolving kernel. Can be a single number or a tuple |
padding |
implicit paddings on both sides of the input. Can be a single number or a tuple |
dilation |
the spacing between kernel elements. Can be a single number or a tuple |
groups |
split input into groups, |
conv2d(input, weight, bias=NULL, stride=1, padding=0, dilation=1, groups=1) -> Tensor
Applies a 2D convolution over an input image composed of several input planes.
See nn_conv2d()
for details and output shape.
Examples
if (torch_is_installed()) {
# With square kernels and equal stride
filters = torch_randn(c(8,4,3,3))
inputs = torch_randn(c(1,4,5,5))
nnf_conv2d(inputs, filters, padding=1)
}