diff --git a/extensions_built_in/sd_trainer/SDTrainer.py b/extensions_built_in/sd_trainer/SDTrainer.py
index e82842d1..732021fe 100644
--- a/extensions_built_in/sd_trainer/SDTrainer.py
+++ b/extensions_built_in/sd_trainer/SDTrainer.py
@@ -163,7 +163,7 @@ class SDTrainer(BaseSDTrainProcess):
         loss = loss * mask_multiplier
 
         prior_loss = None
-        if self.train_config.inverted_mask_prior and prior_pred is not None:
+        if self.train_config.inverted_mask_prior and prior_pred is not None and prior_mask_multiplier is not None:
             # to a loss to unmasked areas of the prior for unmasked regularization
             prior_loss = torch.nn.functional.mse_loss(
                 prior_pred.float(),
diff --git a/toolkit/ip_adapter.py b/toolkit/ip_adapter.py
index 2f49fa21..efa9ac07 100644
--- a/toolkit/ip_adapter.py
+++ b/toolkit/ip_adapter.py
@@ -184,8 +184,8 @@ class IPAdapter(torch.nn.Module):
                 self.clip_image_processor = SAFEImageProcessor()
             self.image_encoder = SAFEVisionModel(
                 in_channels=3,
-                num_tokens=self.config.num_tokens if self.config.adapter_type == 'ip+' else 1,
-                num_vectors=sd.unet.config['cross_attention_dim'] if self.config.adapter_type == 'ip+' else self.config.safe_channels,
+                num_tokens=8,
+                num_vectors=sd.unet.config['cross_attention_dim'],
                 reducer_channels=self.config.safe_reducer_channels,
                 channels=self.config.safe_channels,
                 downscale_factor=8