diff --git a/library/strategy_sd.py b/library/strategy_sd.py
index a44fc409..48808db1 100644
--- a/library/strategy_sd.py
+++ b/library/strategy_sd.py
@@ -2,6 +2,7 @@ import glob
 import os
 from typing import Any, List, Optional, Tuple, Union
 
+import numpy as np
 import torch
 from transformers import CLIPTokenizer
 from library import train_util
@@ -157,7 +158,12 @@ class SdSdxlLatentsCachingStrategy(LatentsCachingStrategy):
         return os.path.splitext(absolute_path)[0] + f"_{image_size[0]:04d}x{image_size[1]:04d}" + self.suffix
 
     def is_disk_cached_latents_expected(self, bucket_reso: Tuple[int, int], npz_path: str, flip_aug: bool, alpha_mask: bool):
-        return self._default_is_disk_cached_latents_expected(8, bucket_reso, npz_path, flip_aug, alpha_mask)
+        return self._default_is_disk_cached_latents_expected(8, bucket_reso, npz_path, flip_aug, alpha_mask, multi_resolution=True)
+
+    def load_latents_from_disk(
+        self, npz_path: str, bucket_reso: Tuple[int, int]
+    ) -> Tuple[Optional[np.ndarray], Optional[List[int]], Optional[List[int]], Optional[np.ndarray], Optional[np.ndarray]]:
+        return self._default_load_latents_from_disk(8, npz_path, bucket_reso)
 
     # TODO remove circular dependency for ImageInfo
     def cache_batch_latents(self, vae, image_infos: List, flip_aug: bool, alpha_mask: bool, random_crop: bool):
@@ -165,7 +171,7 @@ class SdSdxlLatentsCachingStrategy(LatentsCachingStrategy):
         vae_device = vae.device
         vae_dtype = vae.dtype
 
-        self._default_cache_batch_latents(encode_by_vae, vae_device, vae_dtype, image_infos, flip_aug, alpha_mask, random_crop)
+        self._default_cache_batch_latents(encode_by_vae, vae_device, vae_dtype, image_infos, flip_aug, alpha_mask, random_crop, multi_resolution=True)
 
         if not train_util.HIGH_VRAM:
             train_util.clean_memory_on_device(vae.device)