torch (version 0.0.2)

torch_conv1d: Conv1d

Description

Conv1d

Arguments

input

NA input tensor of shape \((\mbox{minibatch} , \mbox{in\_channels} , iW)\)

weight

NA filters of shape \((\mbox{out\_channels} , \frac{\mbox{in\_channels}}{\mbox{groups}} , kW)\)

bias

NA optional bias of shape \((\mbox{out\_channels})\). Default: None

stride

NA the stride of the convolving kernel. Can be a single number or a one-element tuple (sW,). Default: 1

padding

NA implicit paddings on both sides of the input. Can be a single number or a one-element tuple (padW,). Default: 0

dilation

NA the spacing between kernel elements. Can be a single number or a one-element tuple (dW,). Default: 1

groups

NA split input into groups, \(\mbox{in\_channels}\) should be divisible by the number of groups. Default: 1

conv1d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1) -> Tensor

Applies a 1D convolution over an input signal composed of several input planes.

See ~torch.nn.Conv1d for details and output shape.

.. include:: cudnn_deterministic.rst

Examples

# NOT RUN {
if (torch_is_installed()) {

filters = torch_randn(c(33, 16, 3))
inputs = torch_randn(c(20, 16, 50))
nnf_conv1d(inputs, filters)
}
# }