torch (version 0.0.2)

torch_conv3d: Conv3d

Description

Conv3d

Arguments

input

NA input tensor of shape \((\mbox{minibatch} , \mbox{in\_channels} , iT , iH , iW)\)

weight

NA filters of shape \((\mbox{out\_channels} , \frac{\mbox{in\_channels}}{\mbox{groups}} , kT , kH , kW)\)

bias

NA optional bias tensor of shape \((\mbox{out\_channels})\). Default: None

stride

NA the stride of the convolving kernel. Can be a single number or a tuple (sT, sH, sW). Default: 1

padding

NA implicit paddings on both sides of the input. Can be a single number or a tuple (padT, padH, padW). Default: 0

dilation

NA the spacing between kernel elements. Can be a single number or a tuple (dT, dH, dW). Default: 1

groups

NA split input into groups, \(\mbox{in\_channels}\) should be divisible by the number of groups. Default: 1

conv3d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1) -> Tensor

Applies a 3D convolution over an input image composed of several input planes.

See ~torch.nn.Conv3d for details and output shape.

.. include:: cudnn_deterministic.rst

Examples

# NOT RUN {
if (torch_is_installed()) {

# filters = torch_randn(c(33, 16, 3, 3, 3))
# inputs = torch_randn(c(20, 16, 50, 10, 20))
# nnf_conv3d(inputs, filters)
}
# }