torch.nn.functional.conv_transpose3d
function conv_transpose3d<S extends Shape, D extends DType = DType, Dev extends DeviceType = DeviceType>(input: Tensor<S, D, Dev>, weight: Tensor): Tensor<Shape, D, Dev>function conv_transpose3d<S extends Shape, D extends DType = DType, Dev extends DeviceType = DeviceType>(input: Tensor<S, D, Dev>, weight: Tensor, bias: Tensor | null, stride: number | [number, number, number], padding: number | [number, number, number], output_padding: number | [number, number, number], groups: number, dilation: number | [number, number, number], options: ConvTranspose3dFunctionalOptions): Tensor<Shape, D, Dev>3D transposed convolution: applies a 3D transposed convolution operator over an input volume.
Essential for upsampling in volumetric data generation, 3D GANs, and medical imaging.
Parameters
inputTensor<S, D, Dev>- Input tensor of shape (batch, in_channels, iD, iH, iW)
weightTensor- Filters of shape (in_channels, out_channels/groups, kD, kH, kW)