fix(diffusers): remain consistent with diffusers

mindone/diffusers/models/autoencoders/autoencoder_asym_kl.py

@@ -13,6 +13,8 @@
 # limitations under the License.
 from typing import Optional, Tuple, Union
 
+import numpy as np
+
 import mindspore as ms
 from mindspore import nn
 
@@ -138,6 +140,7 @@ def _decode(
     def decode(
         self,
         z: ms.Tensor,
+        generator: Optional[np.random.Generator] = None,
         image: Optional[ms.Tensor] = None,
         mask: Optional[ms.Tensor] = None,
         return_dict: bool = False,

mindone/diffusers/models/autoencoders/vae.py

@@ -380,7 +380,9 @@ def __init__(
                 )
             in_ch_ = out_ch_
 
-        self.layers = nn.SequentialCell(*layers)
+        # nn.SequentialCell does not support the len(self.layers) method nor does it support self.layers[l],
+        # therefore, we use nn.CellList instead.
+        self.layers = nn.CellList(layers)
 
     def construct(self, x: ms.Tensor, mask=None) -> ms.Tensor:
         r"""The forward method of the `MaskConditionEncoder` class."""