fusionlab.segmentation.unet2plus.unet2plus module#

class fusionlab.segmentation.unet2plus.unet2plus.BasicBlock(cin, cout, spatial_dims=2)[source]#

Bases: Sequential

class fusionlab.segmentation.unet2plus.unet2plus.Bridger[source]#

Bases: Module

forward(x)[source]#

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

training: bool#
class fusionlab.segmentation.unet2plus.unet2plus.Decoder(base_dim, spatial_dims=2)[source]#

Bases: Module

forward(x)[source]#

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

training: bool#
class fusionlab.segmentation.unet2plus.unet2plus.Encoder(cin, base_dim, spatial_dims=2)[source]#

Bases: Module

__init__(cin, base_dim, spatial_dims=2)[source]#

UNet Encoder :param cin: input channels :type cin: int :param base_dim: 1st stage dim of conv output :type base_dim: int

forward(x)[source]#

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

training: bool#
class fusionlab.segmentation.unet2plus.unet2plus.Head(cin, cout, spatial_dims=2)[source]#

Bases: Sequential

__init__(cin, cout, spatial_dims=2)[source]#

Basic Identity :param int cin: input channel :param int cout: output channel

class fusionlab.segmentation.unet2plus.unet2plus.UNet2plus(cin, num_cls, base_dim, spatial_dims=2)[source]#

Bases: SegmentationModel

training: bool#