nnf_conv1d: Conv1d

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Conv1d

Description

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

Usage

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

Arguments

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

torch documentation built on June 7, 2023, 6:19 p.m.