torch.nn.MaxUnpool3dOptions
3D max unpooling: reconstructs volumetric tensor from MaxPool3d output and indices.
Inverse operation of MaxPool3d for 3D spatial/volumetric data. Essential for:
- 3D deconvolution networks (medical imaging, video upsampling)
- 3D encoder-decoder architectures
- Volumetric feature reconstruction
- 3D segmentation upsampling paths
Places pooled values at recorded max positions, zeros elsewhere.
Definition
export interface MaxUnpool3dOptions {
/** Stride of the pooling operation (default: kernel_size) */
stride?: number | [number, number, number];
/** Padding used in MaxPool3d (default: 0) */
padding?: number | [number, number, number];
}stride(number | [number, number, number])optional- – Stride of the pooling operation (default: kernel_size)
padding(number | [number, number, number])optional- – Padding used in MaxPool3d (default: 0)
Examples
// 3D volumetric unpooling
const pool = new torch.nn.MaxPool3d(2, 2, 0, true); // return_indices=true
const x = torch.randn([4, 64, 64, 64, 64]);
const [pooled, indices] = pool.forward(x) as [torch.Tensor, torch.Tensor]; // [4, 64, 32, 32, 32]
const unpool = new torch.nn.MaxUnpool3d(2, 2);
const reconstructed = unpool.unpool(pooled, indices); // [4, 64, 64, 64, 64]