Method sample

ldm/models/diffusion/ddpm.py:357–361

(self, batch_size=16, return_intermediates=False)

    @torch.no_grad()
    def sample(self, batch_size=16, return_intermediates=False):
        image_size = self.image_size
        channels = self.channels
        return self.p_sample_loop((batch_size, channels, image_size, image_size),
                                  return_intermediates=return_intermediates)

    def q_sample(self, x_start, t, noise=None):
        noise = default(noise, lambda: torch.randn_like(x_start))