mmagic.engine.optimizers.singan_optimizer_constructor

Module Contents

Classes

SinGANOptimWrapperConstructor

OptimizerConstructor for SinGAN models. Set optimizers for each

class mmagic.engine.optimizers.singan_optimizer_constructor.SinGANOptimWrapperConstructor(optim_wrapper_cfg: dict, paramwise_cfg: Optional[dict] = None)

OptimizerConstructor for SinGAN models. Set optimizers for each submodule of SinGAN. All submodule must be contained in a torch.nn.ModuleList named ‘blocks’. And we access each submodule by MODEL.blocks[SCALE], where MODEL is generator or discriminator, and the scale is the index of the resolution scale.

More detail about the resolution scale and naming rule please refers to SinGANMultiScaleGenerator and SinGANMultiScaleDiscriminator.

Example

>>> # build SinGAN model
>>> model = dict(
>>>     type='SinGAN',
>>>     data_preprocessor=dict(
>>>         type='GANDataPreprocessor',
>>>         non_image_keys=['input_sample']),
>>>     generator=dict(
>>>         type='SinGANMultiScaleGenerator',
>>>         in_channels=3,
>>>         out_channels=3,
>>>         num_scales=2),
>>>     discriminator=dict(
>>>         type='SinGANMultiScaleDiscriminator',
>>>         in_channels=3,
>>>         num_scales=3))
>>> singan = MODELS.build(model)
>>> # build constructor
>>> optim_wrapper = dict(
>>>     generator=dict(optimizer=dict(type='Adam', lr=0.0005,
>>>                                   betas=(0.5, 0.999))),
>>>     discriminator=dict(
>>>         optimizer=dict(type='Adam', lr=0.0005,
>>>                        betas=(0.5, 0.999))))
>>> optim_wrapper_dict_builder = SinGANOptimWrapperConstructor(
>>>     optim_wrapper)
>>> # build optim wrapper dict
>>> optim_wrapper_dict = optim_wrapper_dict_builder(singan)

Parameters

• optim_wrapper_cfg (dict) – Config of the optimizer wrapper.

• paramwise_cfg (Optional[dict]) – Parameter-wise options.

__call__(module: torch.nn.Module) → mmengine.optim.OptimWrapperDict

Build optimizer and return a optimizerwrapperdict.