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https://github.com/invoke-ai/InvokeAI
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fix off-by-one error
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7a3eae4572
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@ -45,7 +45,6 @@ class KSampler(Sampler):
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ddim_eta=0.0,
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verbose=False,
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):
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ddim_num_steps += 1
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outer_model = self.model
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self.model = outer_model.inner_model
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super().make_schedule(
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@ -56,16 +55,6 @@ class KSampler(Sampler):
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)
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self.model = outer_model
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self.ddim_num_steps = ddim_num_steps
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# not working quite right
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# sigmas = K.sampling.get_sigmas_karras(
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# n=ddim_num_steps,
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# sigma_min=self.model.sigmas[0].item(),
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# sigma_max=self.model.sigmas[-1].item(),
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# rho=7.,
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# device=self.device,
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# # Birch-san recommends this, but it doesn't match the call signature in his branch of k-diffusion
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# # concat_zero=False
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# )
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sigmas = self.model.get_sigmas(ddim_num_steps)
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self.sigmas = sigmas
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@ -102,14 +91,14 @@ class KSampler(Sampler):
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# this has to come in the same format as the conditioning, # e.g. as encoded tokens, ...
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**kwargs,
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):
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S += 1
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def route_callback(k_callback_values):
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if img_callback is not None:
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img_callback(k_callback_values['x'],k_callback_values['i'])
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# sigmas = self.model.get_sigmas(S)
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# sigmas are now set up in make_schedule - we take the last steps items
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sigmas = self.sigmas[-S:]
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sigmas = self.sigmas[-S-1:]
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if x_T is not None:
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x = x_T * sigmas[0]
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else:
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