Fixed issues with dataloader bucketing. Allow using standard base image for t2i adapters.

extensions_built_in/sd_trainer/SDTrainer.py

@@ -21,7 +21,8 @@ def flush():
     gc.collect()
 
 adapter_transforms = transforms.Compose([
-    transforms.PILToTensor(),
+    # transforms.PILToTensor(),
+    transforms.ToTensor(),
 ])
 
 
@@ -44,6 +45,13 @@ class SDTrainer(BaseSDTrainProcess):
             flush()
 
     def get_adapter_images(self, batch: 'DataLoaderBatchDTO'):
+        if self.adapter_config.image_dir is None:
+            # adapter needs 0 to 1 values, batch is -1 to 1
+            adapter_batch = batch.tensor.clone().to(
+                self.device_torch, dtype=get_torch_dtype(self.train_config.dtype)
+            )
+            adapter_batch = (adapter_batch + 1) / 2
+            return adapter_batch
         img_ext_list = ['.jpg', '.jpeg', '.png', '.webp']
         adapter_folder_path = self.adapter_config.image_dir
         adapter_images = []