mmagic.models.editors.cyclegan.cyclegan_generator

Module Contents

Classes

ResnetGenerator

Construct a Resnet-based generator that consists of residual blocks

class mmagic.models.editors.cyclegan.cyclegan_generator.ResnetGenerator(in_channels, out_channels, base_channels=64, norm_cfg=dict(type='IN'), use_dropout=False, num_blocks=9, padding_mode='reflect', init_cfg=dict(type='normal', gain=0.02))

Bases: mmengine.model.BaseModule

Construct a Resnet-based generator that consists of residual blocks between a few downsampling/upsampling operations.

Parameters

• in_channels (int) – Number of channels in input images.

• out_channels (int) – Number of channels in output images.

• base_channels (int) – Number of filters at the last conv layer. Default: 64.

• norm_cfg (dict) – Config dict to build norm layer. Default: dict(type=’IN’).

• use_dropout (bool) – Whether to use dropout layers. Default: False.

• num_blocks (int) – Number of residual blocks. Default: 9.

• padding_mode (str) – The name of padding layer in conv layers: ‘reflect’ | ‘replicate’ | ‘zeros’. Default: ‘reflect’.

• init_cfg (dict) – Config dict for initialization. type: The name of our initialization method. Default: ‘normal’. gain: Scaling factor for normal, xavier and orthogonal. Default: 0.02.

forward(x)

Forward function.

Parameters

x (Tensor) – Input tensor with shape (n, c, h, w).

Returns

Forward results.

Return type

Tensor

init_weights()

Initialize weights for the model.