114 lines
4.7 KiB
Python
114 lines
4.7 KiB
Python
#code originally taken from: https://github.com/ChenyangSi/FreeU (under MIT License)
|
|
|
|
import torch
|
|
|
|
|
|
def Fourier_filter(x, threshold, scale):
|
|
# FFT
|
|
x_freq = torch.fft.fftn(x.float(), dim=(-2, -1))
|
|
x_freq = torch.fft.fftshift(x_freq, dim=(-2, -1))
|
|
|
|
B, C, H, W = x_freq.shape
|
|
mask = torch.ones((B, C, H, W), device=x.device)
|
|
|
|
crow, ccol = H // 2, W //2
|
|
mask[..., crow - threshold:crow + threshold, ccol - threshold:ccol + threshold] = scale
|
|
x_freq = x_freq * mask
|
|
|
|
# IFFT
|
|
x_freq = torch.fft.ifftshift(x_freq, dim=(-2, -1))
|
|
x_filtered = torch.fft.ifftn(x_freq, dim=(-2, -1)).real
|
|
|
|
return x_filtered.to(x.dtype)
|
|
|
|
|
|
class FreeU:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {"required": { "model": ("MODEL",),
|
|
"b1": ("FLOAT", {"default": 1.1, "min": 0.0, "max": 10.0, "step": 0.01}),
|
|
"b2": ("FLOAT", {"default": 1.2, "min": 0.0, "max": 10.0, "step": 0.01}),
|
|
"s1": ("FLOAT", {"default": 0.9, "min": 0.0, "max": 10.0, "step": 0.01}),
|
|
"s2": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 10.0, "step": 0.01}),
|
|
}}
|
|
RETURN_TYPES = ("MODEL",)
|
|
FUNCTION = "patch"
|
|
|
|
CATEGORY = "model_patches"
|
|
|
|
def patch(self, model, b1, b2, s1, s2):
|
|
model_channels = model.model.model_config.unet_config["model_channels"]
|
|
scale_dict = {model_channels * 4: (b1, s1), model_channels * 2: (b2, s2)}
|
|
on_cpu_devices = {}
|
|
|
|
def output_block_patch(h, hsp, transformer_options):
|
|
scale = scale_dict.get(h.shape[1], None)
|
|
if scale is not None:
|
|
h[:,:h.shape[1] // 2] = h[:,:h.shape[1] // 2] * scale[0]
|
|
if hsp.device not in on_cpu_devices:
|
|
try:
|
|
hsp = Fourier_filter(hsp, threshold=1, scale=scale[1])
|
|
except:
|
|
print("Device", hsp.device, "does not support the torch.fft functions used in the FreeU node, switching to CPU.")
|
|
on_cpu_devices[hsp.device] = True
|
|
hsp = Fourier_filter(hsp.cpu(), threshold=1, scale=scale[1]).to(hsp.device)
|
|
else:
|
|
hsp = Fourier_filter(hsp.cpu(), threshold=1, scale=scale[1]).to(hsp.device)
|
|
|
|
return h, hsp
|
|
|
|
m = model.clone()
|
|
m.set_model_output_block_patch(output_block_patch)
|
|
return (m, )
|
|
|
|
class FreeU_V2:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {"required": { "model": ("MODEL",),
|
|
"b1": ("FLOAT", {"default": 1.3, "min": 0.0, "max": 10.0, "step": 0.01}),
|
|
"b2": ("FLOAT", {"default": 1.4, "min": 0.0, "max": 10.0, "step": 0.01}),
|
|
"s1": ("FLOAT", {"default": 0.9, "min": 0.0, "max": 10.0, "step": 0.01}),
|
|
"s2": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 10.0, "step": 0.01}),
|
|
}}
|
|
RETURN_TYPES = ("MODEL",)
|
|
FUNCTION = "patch"
|
|
|
|
CATEGORY = "model_patches"
|
|
|
|
def patch(self, model, b1, b2, s1, s2):
|
|
model_channels = model.model.model_config.unet_config["model_channels"]
|
|
scale_dict = {model_channels * 4: (b1, s1), model_channels * 2: (b2, s2)}
|
|
on_cpu_devices = {}
|
|
|
|
def output_block_patch(h, hsp, transformer_options):
|
|
scale = scale_dict.get(h.shape[1], None)
|
|
if scale is not None:
|
|
hidden_mean = h.mean(1).unsqueeze(1)
|
|
B = hidden_mean.shape[0]
|
|
hidden_max, _ = torch.max(hidden_mean.view(B, -1), dim=-1, keepdim=True)
|
|
hidden_min, _ = torch.min(hidden_mean.view(B, -1), dim=-1, keepdim=True)
|
|
hidden_mean = (hidden_mean - hidden_min.unsqueeze(2).unsqueeze(3)) / (hidden_max - hidden_min).unsqueeze(2).unsqueeze(3)
|
|
|
|
h[:,:h.shape[1] // 2] = h[:,:h.shape[1] // 2] * ((scale[0] - 1 ) * hidden_mean + 1)
|
|
|
|
if hsp.device not in on_cpu_devices:
|
|
try:
|
|
hsp = Fourier_filter(hsp, threshold=1, scale=scale[1])
|
|
except:
|
|
print("Device", hsp.device, "does not support the torch.fft functions used in the FreeU node, switching to CPU.")
|
|
on_cpu_devices[hsp.device] = True
|
|
hsp = Fourier_filter(hsp.cpu(), threshold=1, scale=scale[1]).to(hsp.device)
|
|
else:
|
|
hsp = Fourier_filter(hsp.cpu(), threshold=1, scale=scale[1]).to(hsp.device)
|
|
|
|
return h, hsp
|
|
|
|
m = model.clone()
|
|
m.set_model_output_block_patch(output_block_patch)
|
|
return (m, )
|
|
|
|
NODE_CLASS_MAPPINGS = {
|
|
"FreeU": FreeU,
|
|
"FreeU_V2": FreeU_V2,
|
|
}
|