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@ -80,7 +80,7 @@ class GaussianDiffusionInjector(Injector):
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def forward(self, state):
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gen = self.env['generators'][self.opt['generator']]
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hq = state[self.input]
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assert hq.max() < 1 or hq.min() > -1, "Attempting to train gaussian diffusion on un-normalized inputs. This won't work, silly!"
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assert hq.max() < 1 or hq.min() > -1, f"Attempting to train gaussian diffusion on un-normalized inputs. This won't work, silly! {hq.min()} {hq.max()}"
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with autocast(enabled=self.env['opt']['fp16']):
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if not gen.training or (self.deterministic_timesteps_every != 0 and self.env['step'] % self.deterministic_timesteps_every == 0):
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