From b3f0cf8e9e07ad002f9df07981e2eecaf0569191 Mon Sep 17 00:00:00 2001 From: Shuai Yang <596836482@qq.com> Date: Mon, 6 Mar 2023 17:30:54 +0800 Subject: [PATCH] Update dualstylegan.py --- model/dualstylegan.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/model/dualstylegan.py b/model/dualstylegan.py index bbf6989..8742238 100644 --- a/model/dualstylegan.py +++ b/model/dualstylegan.py @@ -51,7 +51,7 @@ def __init__(self, size, style_dim, n_mlp, channel_multiplier=2, twoRes=True, re layers = [PixelNorm()] for i in range(n_mlp-6): layers.append(EqualLinear(512, 512, lr_mul=0.01, activation="fused_lrelu")) - # color transform blocks T_c + # structure transform blocks T_s self.style = nn.Sequential(*layers) # StyleGAN2 self.generator = Generator(size, style_dim, n_mlp, channel_multiplier) @@ -66,7 +66,7 @@ def __init__(self, size, style_dim, n_mlp, channel_multiplier=2, twoRes=True, re self.res.append(AdaResBlock(out_channel)) self.res.append(AdaResBlock(out_channel)) else: - # structure transform block T_s + # color transform block T_c self.res.append(EqualLinear(512, 512)) # FC layer is initialized with identity matrices, meaning no changes to the input latent code self.res[-1].weight.data = torch.eye(512) * 512.0**0.5 + torch.randn(512, 512) * 0.01 @@ -200,4 +200,4 @@ def mean_latent(self, n_latent): return self.generator.mean_latent(n_latent) def get_latent(self, input): - return self.generator.style(input) \ No newline at end of file + return self.generator.style(input)