spconv_blocks

Sparse convolution blocks: submanifold, strided, and residual variants.

Classes:

SubMConv3dBlock –

Submanifold sparse 3D convolution followed by normalization and activation, on packed point features.
SparseConvBlock –

Sparse 3D convolution followed by normalization and activation.
SparseResidualBlock –

Pre-activation sparse residual block shared by the SPFormer and SphereFormer SpConv U-Nets.
SubMConv3dResidualBlock –

Residual block with a single \(3\times3\times3\) submanifold convolution: conv, norm, add the input, act.

SubMConv3dBlock ¶

SubMConv3dBlock(
    in_channels: int,
    out_channels: int,
    kernel_size: int,
    padding: int,
    norm: Union[str, Callable, None] = None,
    act: Union[str, Callable, None] = None,
    act_kwargs: Optional[Dict[str, Any]] = None,
    norm_kwargs: Optional[Dict[str, Any]] = None,
    bias: bool = True,
    stem_indice_key: Optional[str] = None,
)

Bases: Module

Submanifold sparse 3D convolution followed by normalization and activation, on packed point features.

Unlike SparseConvBlock, this block takes and returns packed \((N, C)\) features: it builds the SparseConvTensor from pos and batch itself, so it drops into a point-based backbone as a conditional position embedding.

Parameters:

in_channels (int) –

Number of input channels.
out_channels (int) –

Number of output channels.
kernel_size (int) –

Convolution kernel size.
padding (int) –

Convolution padding.
norm (Union[str, Callable, None], default: None ) –

Normalization passed to create_norm.
act (Union[str, Callable, None], default: None ) –

Activation passed to create_act.
act_kwargs (Optional[Dict[str, Any]], default: None ) –

Extra keyword arguments for the activation.
norm_kwargs (Optional[Dict[str, Any]], default: None ) –

Extra keyword arguments for the normalization.
bias (bool, default: True ) –

Whether the convolution has a bias term.
stem_indice_key (Optional[str], default: None ) –

spconv index key for the convolution.

SparseConvBlock ¶

SparseConvBlock(
    in_channels: int,
    out_channels: int,
    kernel_size: Union[int, Tuple[int, ...]],
    *,
    stride: Union[int, Tuple[int, ...]] = 1,
    padding: Union[int, Tuple[int, ...]] = 0,
    indice_key: str,
    conv_type: str = "subm",
    norm: Union[str, Callable, None] = "batch_norm",
    norm_kwargs: Optional[Dict[str, Any]] = None,
    act: Union[str, Callable, None] = "relu",
    act_kwargs: Optional[Dict[str, Any]] = None,
)

Bases: SparseSequential

Sparse 3D convolution followed by normalization and activation.

A subm (submanifold), spconv (regular, optionally strided), or inverseconv convolution over a SparseConvTensor, followed by normalization and activation on the features. As a SparseSequential subclass it drops directly into the sparse voxel backbones' convolution stacks.

Parameters:

in_channels (int) –

Number of input channels.
out_channels (int) –

Number of output channels.
kernel_size (Union[int, Tuple[int, ...]]) –

Convolution kernel size.
stride (Union[int, Tuple[int, ...]], default: 1 ) –

Convolution stride (used by spconv).
padding (Union[int, Tuple[int, ...]], default: 0 ) –

Convolution padding (used by spconv).
indice_key (str) –

spconv index key for the convolution.
conv_type (str, default: 'subm' ) –

One of subm, spconv, or inverseconv.
norm (Union[str, Callable, None], default: 'batch_norm' ) –

Normalization passed to create_norm.
norm_kwargs (Optional[Dict[str, Any]], default: None ) –

Extra keyword arguments for the normalization (e.g. eps, momentum).
act (Union[str, Callable, None], default: 'relu' ) –

Activation passed to create_act.
act_kwargs (Optional[Dict[str, Any]], default: None ) –

Extra keyword arguments for the activation.

SparseResidualBlock ¶

SparseResidualBlock(
    in_channels: int,
    out_channels: int,
    *,
    indice_key: Optional[str] = None,
    act: Union[str, Callable, None] = "relu",
    act_kwargs: Optional[Dict[str, Any]] = None,
    norm: Union[str, Callable, None] = "batch_norm",
    norm_kwargs: Optional[Dict[str, Any]] = None,
)

Bases: SparseModule

Pre-activation sparse residual block shared by the SPFormer and SphereFormer SpConv U-Nets.

The convolutional branch applies \(\text{norm} \to \text{act} \to \text{conv} \to \text{norm} \to \text{act} \to \text{conv}\) over two \(3\times3\times3\) submanifold convolutions; the identity branch is nn.Identity when the channels match, else a \(1\times1\times1\) SubMConv3d projection.

Parameters:

in_channels (int) –

Number of input channels.
out_channels (int) –

Number of output channels.
indice_key (Optional[str], default: None ) –

spconv index key shared by the two submanifold convolutions.
act (Union[str, Callable, None], default: 'relu' ) –

Activation passed to create_act.
act_kwargs (Optional[Dict[str, Any]], default: None ) –

Extra keyword arguments for the activation.
norm (Union[str, Callable, None], default: 'batch_norm' ) –

Normalization passed to create_norm.
norm_kwargs (Optional[Dict[str, Any]], default: None ) –

Extra keyword arguments for the normalization (e.g. eps, momentum).

SubMConv3dResidualBlock ¶

SubMConv3dResidualBlock(
    channels: int,
    *,
    indice_key: str,
    act: Union[str, Callable, None] = "relu",
    act_kwargs: Optional[Dict[str, Any]] = None,
    norm: Union[str, Callable, None] = "batch_norm",
    norm_kwargs: Optional[Dict[str, Any]] = None,
)

Bases: SparseModule

Residual block with a single \(3\times3\times3\) submanifold convolution: conv, norm, add the input, act.

Parameters:

channels (int) –

Input and output channels.
indice_key (str) –

Shared submanifold indice key.
act (Union[str, Callable, None], default: 'relu' ) –

Activation type or callable.
act_kwargs (Optional[Dict[str, Any]], default: None ) –

Extra activation arguments.
norm (Union[str, Callable, None], default: 'batch_norm' ) –

Normalization type or callable.
norm_kwargs (Optional[Dict[str, Any]], default: None ) –

Extra normalization arguments.