Method eps

k_diffusion/sampling.py:349–356

(self, eps_cache, key, x, t, *args, **kwargs)

        return t.neg().exp()

    def eps(self, eps_cache, key, x, t, *args, **kwargs):
        if key in eps_cache:
            return eps_cache[key], eps_cache
        sigma = self.sigma(t) * x.new_ones([x.shape[0]])
        eps = (x - self.model(x, sigma, *args, **self.extra_args, **kwargs)) / self.sigma(t)
        if self.eps_callback is not None:
            self.eps_callback()
        return eps, {key: eps, **eps_cache}

    def dpm_solver_1_step(self, x, t, t_next, eps_cache=None):
        eps_cache = {} if eps_cache is None else eps_cache