Index

A | B | C | D | E | F | G | H | I | L | M | N | P | R | S | T

A

affine (BatchNorm attribute)
- (GroupNorm attribute)

B

BatchNorm (class in torchsparse.nn.modules.norm)

build_kernel_map() (in module torchsparse.nn.functional.build_kmap)

C

D

detach() (PointTensor method)
- (SparseTensor method)

E

F

G

H

half() (SparseTensor method)

I

init() (in module torchsparse.backends)

inplace (LeakyReLU attribute)
- (ReLU attribute)

L

leaky_relu() (in module torchsparse.nn.functional.activation)

LeakyReLU (class in torchsparse.nn.modules.activation)

M

momentum (BatchNorm attribute)

N

P

PointTensor (class in torchsparse.tensor)

R

reset_parameters() (Conv3d method)
- (ToBEVConvolution method)
- (ToDenseBEVConvolution method)

S

T

to() (PointTensor method)
- (SparseTensor method)
ToBEVConvolution (class in torchsparse.nn.modules.bev)
ToBEVHeightCompression (class in torchsparse.nn.modules.bev)
ToBEVReduction (class in torchsparse.nn.modules.bev)
ToDenseBEVConvolution (class in torchsparse.nn.modules.bev)
torchsparse
- module
torchsparse.backbones
- module
torchsparse.backbones.modules
- module
torchsparse.backbones.modules.blocks
- module
torchsparse.backbones.resnet
- module
torchsparse.backbones.unet
- module
torchsparse.backends
- module
torchsparse.nn
- module
torchsparse.nn.functional
- module
torchsparse.nn.functional.activation
- module
torchsparse.nn.functional.build_kmap
- module
torchsparse.nn.functional.conv
- module
torchsparse.nn.functional.count
- module
torchsparse.nn.functional.crop
- module
torchsparse.nn.functional.devoxelize
- module
torchsparse.nn.functional.downsample
- module
torchsparse.nn.functional.hash
- module
torchsparse.nn.functional.pooling
- module
torchsparse.nn.functional.query
- module
torchsparse.nn.functional.voxelize
- module
torchsparse.nn.modules
- module

torchsparse.nn.modules.activation
- module
torchsparse.nn.modules.bev
- module
torchsparse.nn.modules.conv
- module
torchsparse.nn.modules.crop
- module
torchsparse.nn.modules.norm
- module
torchsparse.nn.modules.pooling
- module
torchsparse.nn.utils
- module
torchsparse.nn.utils.apply
- module
torchsparse.nn.utils.kernel
- module
torchsparse.operators
- module
torchsparse.tensor
- module
torchsparse.utils
- module
torchsparse.utils.collate
- module
torchsparse.utils.quantize
- module
torchsparse.utils.tune
- module
torchsparse.utils.utils
- module
torchsparse.version
- module
track_running_stats (BatchNorm attribute)
training (Conv3d attribute)
- (GlobalAvgPool attribute)
- (GlobalMaxPool attribute)
- (SparseCrop attribute)
- (SparseResBlock attribute)
- (SparseResUNet42 attribute)
- (ToBEVConvolution attribute)
- (ToBEVHeightCompression attribute)
- (ToBEVReduction attribute)
- (ToDenseBEVConvolution attribute)
tune() (in module torchsparse.utils.tune)