Conv1d
Conv1d
torch_conv1d( input, weight, bias = list(), stride = 1L, padding = 0L, dilation = 1L, groups = 1L )
input |
input tensor of shape (\mbox{minibatch} , \mbox{in\_channels} , iW) |
weight |
filters of shape (\mbox{out\_channels} , \frac{\mbox{in\_channels}}{\mbox{groups}} , kW) |
bias |
optional bias of shape (\mbox{out\_channels}). Default: |
stride |
the stride of the convolving kernel. Can be a single number or a one-element tuple |
padding |
implicit paddings on both sides of the input. Can be a single number or a one-element tuple |
dilation |
the spacing between kernel elements. Can be a single number or a one-element tuple |
groups |
split input into groups, \mbox{in\_channels} should be divisible by the number of groups. Default: 1 |
Applies a 1D convolution over an input signal composed of several input planes.
See nn_conv1d() for details and output shape.
if (torch_is_installed()) {
filters = torch_randn(c(33, 16, 3))
inputs = torch_randn(c(20, 16, 50))
nnf_conv1d(inputs, filters)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.