Use parameters + buffers when deciding upscale_dtype (#9882)

Sometimes, the decoder might lack parameters and only buffers (e.g., this happens when we manually need to convert all the parameters to buffers — e.g. to avoid packing fp16 and fp32 parameters with FSDP)

src/diffusers/models/autoencoders/autoencoder_kl_temporal_decoder.py

@@ -11,6 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+import itertools
 from typing import Dict, Optional, Tuple, Union
 
 import torch
@@ -94,7 +95,7 @@ class TemporalDecoder(nn.Module):
 
         sample = self.conv_in(sample)
 
-        upscale_dtype = next(iter(self.up_blocks.parameters())).dtype
+        upscale_dtype = next(itertools.chain(self.up_blocks.parameters(), self.up_blocks.buffers())).dtype
         if torch.is_grad_enabled() and self.gradient_checkpointing:
 
             def create_custom_forward(module):