Fixes LDSR upscaler producing black bars

        down_sample_rate = target_scale / 4

        wd = width_og * down_sample_rate

        hd = height_og * down_sample_rate

        width_downsampled_pre = int(wd)

        height_downsampled_pre = int(hd)

        width_downsampled_pre = int(np.ceil(wd))

        height_downsampled_pre = int(np.ceil(hd))

        if down_sample_rate != 1:

            print(

            im_og = im_og.resize((width_downsampled_pre, height_downsampled_pre), Image.LANCZOS)

        else:

            print(f"Down sample rate is 1 from {target_scale} / 4 (Not downsampling)")

        logs = self.run(model["model"], im_og, diffusion_steps, eta)

        # pad width and height to multiples of 64, pads with the edge values of image to avoid artifacts

        pad_w, pad_h = np.max(((2, 2), np.ceil(np.array(im_og.size) / 64).astype(int)), axis=0) * 64 - im_og.size

        im_padded = Image.fromarray(np.pad(np.array(im_og), ((0, pad_h), (0, pad_w), (0, 0)), mode='edge'))

        logs = self.run(model["model"], im_padded, diffusion_steps, eta)

        sample = logs["sample"]

        sample = sample.detach().cpu()

        sample = np.transpose(sample, (0, 2, 3, 1))

        a = Image.fromarray(sample[0])

        # remove padding

        a = a.crop((0, 0) + tuple(np.array(im_og.size) * 4))

        del model

        gc.collect()

        torch.cuda.empty_cache()