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https://github.com/kohya-ss/sd-scripts.git
synced 2026-04-10 06:54:17 +00:00
update as official impl
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@@ -998,21 +998,25 @@ class SdxlUNet2DConditionModel(nn.Module):
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# FreeU
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self.freeU = False
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self.freeUSl = 0.5
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self.freeURThres = 0.5
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self.freeUBl = 0.5
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self.freeUB1 = 1.0
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self.freeUB2 = 1.0
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self.freeUS1 = 1.0
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self.freeUS2 = 1.0
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self.freeURThres = 1
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# implementation of FreeU
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# FreeU: Free Lunch in Diffusion U-Net https://arxiv.org/abs/2309.11497
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def set_free_u_enabled(self, enabled: bool, bl=0.5, sl=0.5, rthresh=0.5):
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print(f"FreeU: {enabled}, bl={bl}, sl={sl}, rthresh={rthresh}")
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def set_free_u_enabled(self, enabled: bool, b1=1.0, b2=1.0, s1=1.0, s2=1.0, rthresh=1):
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print(f"FreeU: {enabled}, b1={b1}, b2={b2}, s1={s1}, s2={s2}, rthresh={rthresh}")
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self.freeU = enabled
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self.freeUSl = sl
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self.freeUB1 = b1
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self.freeUB2 = b2
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self.freeUS1 = s1
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self.freeUS2 = s2
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self.freeURThres = rthresh
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self.freeUBl = bl
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def spectral_modulation(self, skip_feature, sl=0.5, rthresh=0.5):
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def spectral_modulation(self, skip_feature, sl=1.0, rthresh=1):
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"""
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スキップ特徴を周波数領域で修正する関数
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@@ -1024,6 +1028,9 @@ class SdxlUNet2DConditionModel(nn.Module):
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import torch.fft
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r"""
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# 論文に従った実装
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org_dtype = skip_feature.dtype
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if org_dtype == torch.bfloat16:
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skip_feature = skip_feature.to(torch.float32)
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@@ -1060,9 +1067,35 @@ class SdxlUNet2DConditionModel(nn.Module):
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modified_skip_feature = torch.fft.ifftn(F_prime, dim=(2, 3))
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modified_skip_feature = modified_skip_feature.real # 実部のみを取得
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"""
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if org_dtype == torch.bfloat16:
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modified_skip_feature = modified_skip_feature.to(org_dtype)
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# 公式リポジトリの実装
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org_dtype = skip_feature.dtype
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x = skip_feature
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threshold = rthresh
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scale = sl
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# FFT
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x_freq = torch.fft.fftn(x.float(), dim=(-2, -1))
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x_freq = torch.fft.fftshift(x_freq, dim=(-2, -1))
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B, C, H, W = x_freq.shape
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mask = torch.ones((B, C, H, W), device=x.device)
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crow, ccol = H // 2, W // 2
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mask[..., crow - threshold : crow + threshold, ccol - threshold : ccol + threshold] = scale
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x_freq = x_freq * mask
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# IFFT
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x_freq = torch.fft.ifftshift(x_freq, dim=(-2, -1))
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x_filtered = torch.fft.ifftn(x_freq, dim=(-2, -1)).real
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modified_skip_feature = x_filtered
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# if org_dtype == torch.bfloat16:
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modified_skip_feature = modified_skip_feature.to(org_dtype)
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return modified_skip_feature
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@@ -1151,7 +1184,12 @@ class SdxlUNet2DConditionModel(nn.Module):
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h = call_module(module, h, emb, context)
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if self.freeU:
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h_mod = self.spectral_modulation(h, self.freeUSl, self.freeURThres)
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ch = h.shape[1]
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s = self.freeUS1 if ch == 1280 else (self.freeUS2 if ch == 640 else 1.0)
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if s == 1.0:
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h_mod = h
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else:
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h_mod = self.spectral_modulation(h, s, self.freeURThres)
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hs.append(h_mod)
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else:
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hs.append(h)
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@@ -1161,7 +1199,12 @@ class SdxlUNet2DConditionModel(nn.Module):
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for module in self.output_blocks:
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if self.freeU:
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ch = h.shape[1]
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h[:, : ch // 2] = h[:, : ch // 2] * self.freeUBl
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if ch == 1280:
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h[:, : ch // 2] = h[:, : ch // 2] * self.freeUB1
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elif ch == 640:
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h[:, : ch // 2] = h[:, : ch // 2] * self.freeUB2
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# else:
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# print(f"disable freeU: {ch}")
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h = torch.cat([h, hs.pop()], dim=1)
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h = call_module(module, h, emb, context)
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@@ -1523,7 +1523,7 @@ def main(args):
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# freeU
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# unet.set_free_u_enabled(False, 1.0, 1.0, 0)
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unet.set_free_u_enabled(True, 1.4, 1.0, 10)
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unet.set_free_u_enabled(True, 1.1, 1.2, 0.9, 0.2)
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# networkを組み込む
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if args.network_module:
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