Conv2d — nnf_conv2d • torch

Applies a 2D convolution over an input image composed of several input planes.

Usage

nnf_conv2d(
  input,
  weight,
  bias = NULL,
  stride = 1,
  padding = 0,
  dilation = 1,
  groups = 1
)

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