Applies a 2D transposed convolution operator over an input image composed of several input planes, sometimes also called "deconvolution".
nnf_conv_transpose2d(
input,
weight,
bias = NULL,
stride = 1,
padding = 0,
output_padding = 0,
groups = 1,
dilation = 1
)
input tensor of shape (minibatch, in_channels, iH , iW)
filters of shape (out_channels , in_channels/groups, kH , kW)
optional bias tensor of shape (out_channels). Default: NULL
the stride of the convolving kernel. Can be a single number or a
tuple (sH, sW)
. Default: 1
implicit paddings on both sides of the input. Can be a
single number or a tuple (padH, padW)
. Default: 0
padding applied to the output
split input into groups, in_channels
should be divisible by the
number of groups. Default: 1
the spacing between kernel elements. Can be a single number or
a tuple (dH, dW)
. Default: 1