nnf_conv2d: Conv2d
In torch: Tensors and Neural Networks with 'GPU' Acceleration

nnf_conv2d

R Documentation

Conv2d

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

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