Bug fixes. added ability to use l1 loss. varous other tests and improvements

toolkit/data_transfer_object/data_loader.py

@@ -96,6 +96,8 @@ class DataLoaderBatchDTO:
             self.unaugmented_tensor: Union[torch.Tensor, None] = None
             self.unconditional_tensor: Union[torch.Tensor, None] = None
             self.unconditional_latents: Union[torch.Tensor, None] = None
+            self.clip_image_embeds: Union[List[dict], None] = None
+            self.clip_image_embeds_unconditional: Union[List[dict], None] = None
             self.sigmas: Union[torch.Tensor, None] = None  # can be added elseware and passed along training code
             if not is_latents_cached:
                 # only return a tensor if latents are not cached
@@ -183,6 +185,23 @@ class DataLoaderBatchDTO:
                     else:
                         unconditional_tensor.append(x.unconditional_tensor)
                 self.unconditional_tensor = torch.cat([x.unsqueeze(0) for x in unconditional_tensor])
+
+            if any([x.clip_image_embeds is not None for x in self.file_items]):
+                self.clip_image_embeds = []
+                for x in self.file_items:
+                    if x.clip_image_embeds is not None:
+                        self.clip_image_embeds.append(x.clip_image_embeds)
+                    else:
+                        raise Exception("clip_image_embeds is None for some file items")
+
+            if any([x.clip_image_embeds_unconditional is not None for x in self.file_items]):
+                self.clip_image_embeds_unconditional = []
+                for x in self.file_items:
+                    if x.clip_image_embeds_unconditional is not None:
+                        self.clip_image_embeds_unconditional.append(x.clip_image_embeds_unconditional)
+                    else:
+                        raise Exception("clip_image_embeds_unconditional is None for some file items")
+
         except Exception as e:
             print(e)
             raise e