mmagic.models.editors.mspie.mspie_stylegan2_modules
¶
Module Contents¶
Classes¶
Modulated Conv2d in StyleGANv2 with Positional Encoding (PE). |
|
Modulated Style Convolution with Positional Encoding. |
Attributes¶
- class mmagic.models.editors.mspie.mspie_stylegan2_modules.ModulatedPEConv2d(in_channels, out_channels, kernel_size, style_channels, demodulate=True, upsample=False, downsample=False, blur_kernel=[1, 3, 3, 1], equalized_lr_cfg=dict(mode='fan_in', lr_mul=1.0, gain=1.0), style_mod_cfg=dict(bias_init=1.0), style_bias=0.0, eps=1e-08, no_pad=False, deconv2conv=False, interp_pad=None, up_config=dict(scale_factor=2, mode='nearest'), up_after_conv=False)[source]¶
Bases:
mmengine.model.BaseModule
Modulated Conv2d in StyleGANv2 with Positional Encoding (PE).
This module is modified from the
ModulatedConv2d
in StyleGAN2 to support the experiments in: Positional Encoding as Spatial Inductive Bias in GANs, CVPR’2021.- Parameters
in_channels (int) – Input channels.
out_channels (int) – Output channels.
kernel_size (int) – Kernel size, same as
nn.Con2d
.style_channels (int) – Channels for the style codes.
demodulate (bool, optional) – Whether to adopt demodulation. Defaults to True.
upsample (bool, optional) – Whether to adopt upsampling in features. Defaults to False.
downsample (bool, optional) – Whether to adopt downsampling in features. Defaults to False.
blur_kernel (list[int], optional) – Blurry kernel. Defaults to [1, 3, 3, 1].
equalized_lr_cfg (dict | None, optional) – Configs for equalized lr. Defaults to dict(mode=’fan_in’, lr_mul=1., gain=1.).
style_mod_cfg (dict, optional) – Configs for style modulation module. Defaults to dict(bias_init=1.).
style_bias (float, optional) – Bias value for style code. Defaults to 0..
eps (float, optional) – Epsilon value to avoid computation error. Defaults to 1e-8.
no_pad (bool, optional) – Whether to removing the padding in convolution. Defaults to False.
deconv2conv (bool, optional) – Whether to substitute the transposed conv with (conv2d, upsampling). Defaults to False.
interp_pad (int | None, optional) – The padding number of interpolation pad. Defaults to None.
up_config (dict, optional) – Upsampling config. Defaults to dict(scale_factor=2, mode=’nearest’).
up_after_conv (bool, optional) – Whether to adopt upsampling after convolution. Defaults to False.
- class mmagic.models.editors.mspie.mspie_stylegan2_modules.ModulatedPEStyleConv(in_channels, out_channels, kernel_size, style_channels, upsample=False, blur_kernel=[1, 3, 3, 1], demodulate=True, style_mod_cfg=dict(bias_init=1.0), style_bias=0.0, **kwargs)[source]¶
Bases:
mmengine.model.BaseModule
Modulated Style Convolution with Positional Encoding.
This module is modified from the
ModulatedStyleConv
in StyleGAN2 to support the experiments in: Positional Encoding as Spatial Inductive Bias in GANs, CVPR’2021.- Parameters
in_channels (int) – Input channels.
out_channels (int) – Output channels.
kernel_size (int) – Kernel size, same as
nn.Con2d
.style_channels (int) – Channels for the style codes.
demodulate (bool, optional) – Whether to adopt demodulation. Defaults to True.
upsample (bool, optional) – Whether to adopt upsampling in features. Defaults to False.
downsample (bool, optional) – Whether to adopt downsampling in features. Defaults to False.
blur_kernel (list[int], optional) – Blurry kernel. Defaults to [1, 3, 3, 1].
equalized_lr_cfg (dict | None, optional) – Configs for equalized lr. Defaults to dict(mode=’fan_in’, lr_mul=1., gain=1.).
style_mod_cfg (dict, optional) – Configs for style modulation module. Defaults to dict(bias_init=1.).
style_bias (float, optional) – Bias value for style code. Defaults to 0..
- forward(x, style, noise=None, return_noise=False)[source]¶
Forward Function.
- Parameters
x ([Tensor) – Input features with shape of (N, C, H, W).
style (Tensor) – Style latent with shape of (N, C).
noise (Tensor, optional) – Noise for injection. Defaults to None.
return_noise (bool, optional) – Whether to return noise tensors. Defaults to False.
- Returns
Output features with shape of (N, C, H, W)
- Return type
Tensor