nnf_conv1d() R function from [torch]

Conv1d

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


nnf_conv1d(
  input,
  weight,
  bias = NULL,
  stride = 1,
  padding = 0,
  dilation = 1,
  groups = 1
)

input: input tensor of shape (minibatch, in_channels , iW)
weight: filters of shape (out_channels, in_channels/groups , kW)
bias: optional bias of shape (out_channels). Default: NULL
stride: the stride of the convolving kernel. Can be a single number or a one-element tuple (sW,). Default: 1
padding: implicit paddings on both sides of the input. Can be a single number or a one-element tuple (padW,). Default: 0
dilation: the spacing between kernel elements. Can be a single number or a one-element tuple (dW,). Default: 1
groups: split input into groups, in_channels should be divisible by the number of groups. Default: 1

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