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Remove some useless code.
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@ -7,23 +7,6 @@ from comfy import model_management
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from .ldm.models.diffusion.ddim import DDIMSampler
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from .ldm.models.diffusion.ddim import DDIMSampler
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from .ldm.modules.diffusionmodules.util import make_ddim_timesteps
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from .ldm.modules.diffusionmodules.util import make_ddim_timesteps
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class CFGDenoiser(torch.nn.Module):
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def __init__(self, model):
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super().__init__()
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self.inner_model = model
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def forward(self, x, sigma, uncond, cond, cond_scale):
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if len(uncond[0]) == len(cond[0]) and x.shape[0] * x.shape[2] * x.shape[3] < (96 * 96): #TODO check memory instead
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x_in = torch.cat([x] * 2)
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sigma_in = torch.cat([sigma] * 2)
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cond_in = torch.cat([uncond, cond])
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uncond, cond = self.inner_model(x_in, sigma_in, cond=cond_in).chunk(2)
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else:
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cond = self.inner_model(x, sigma, cond=cond)
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uncond = self.inner_model(x, sigma, cond=uncond)
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return uncond + (cond - uncond) * cond_scale
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#The main sampling function shared by all the samplers
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#The main sampling function shared by all the samplers
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#Returns predicted noise
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#Returns predicted noise
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def sampling_function(model_function, x, timestep, uncond, cond, cond_scale, cond_concat=None, model_options={}):
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def sampling_function(model_function, x, timestep, uncond, cond, cond_scale, cond_concat=None, model_options={}):
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