class torch.nn.AdaptiveMaxPool3d(output_size: Union[T, Tuple[T, ...]], return_indices: bool = False)[source]

Applies a 3D adaptive max pooling over an input signal composed of several input planes.

The output is of size D x H x W, for any input size. The number of output features is equal to the number of input planes.

Parameters
• output_size – the target output size of the image of the form D x H x W. Can be a tuple (D, H, W) or a single D for a cube D x D x D. D, H and W can be either a int, or None which means the size will be the same as that of the input.

• return_indices – if True, will return the indices along with the outputs. Useful to pass to nn.MaxUnpool3d. Default: False

Examples

>>> # target output size of 5x7x9