def predict_start_from_noise()

in agents/diffusion.py [0:0]

• 12 lines of code
• 2 McCabe index (conditional complexity)

    def predict_start_from_noise(self, x_t, t, noise):
        '''
            if self.predict_epsilon, model output is (scaled) noise;
            otherwise, model predicts x0 directly
        '''
        if self.predict_epsilon:
            return (
                    extract(self.sqrt_recip_alphas_cumprod, t, x_t.shape) * x_t -
                    extract(self.sqrt_recipm1_alphas_cumprod, t, x_t.shape) * noise
            )
        else:
            return noise