Improvements to dataloader

toolkit/config_modules.py

@@ -524,6 +524,9 @@ class DatasetConfig:
         self.replacements: List[str] = kwargs.get('replacements', [])
         self.loss_multiplier: float = kwargs.get('loss_multiplier', 1.0)
 
+        self.num_workers: int = kwargs.get('num_workers', 4)
+        self.prefetch_factor: int = kwargs.get('prefetch_factor', 2)
+
 
 def preprocess_dataset_raw_config(raw_config: List[dict]) -> List[dict]:
     """

toolkit/data_loader.py

@@ -585,7 +585,8 @@ def get_dataloader_from_datasets(
             drop_last=False,
             shuffle=True,
             collate_fn=dto_collation,  # Use the custom collate function
-            num_workers=8
+            num_workers=dataset_config_list[0].num_workers,
+            prefetch_factor=dataset_config_list[0].prefetch_factor,
         )
     else:
         data_loader = DataLoader(

toolkit/data_transfer_object/data_loader.py

@@ -220,11 +220,7 @@ class DataLoaderBatchDTO:
             to_replace_list=None,
             add_if_not_present=True
     ):
-        return [x.get_caption(
-            trigger=trigger,
-            to_replace_list=to_replace_list,
-            add_if_not_present=add_if_not_present
-        ) for x in self.file_items]
+        return [x.caption for x in self.file_items]
 
     def get_caption_short_list(
             self,
@@ -232,12 +228,7 @@ class DataLoaderBatchDTO:
             to_replace_list=None,
             add_if_not_present=True
     ):
-        return [x.get_caption(
-            trigger=trigger,
-            to_replace_list=to_replace_list,
-            add_if_not_present=add_if_not_present,
-            short_caption=True
-        ) for x in self.file_items]
+        return [x.caption_short for x in self.file_items]
 
     def cleanup(self):
         del self.latents

toolkit/dataloader_mixins.py

@@ -263,6 +263,8 @@ class CaptionProcessingDTOMixin:
             super().__init__(*args, **kwargs)
             self.raw_caption: str = None
             self.raw_caption_short: str = None
+            self.caption: str = None
+            self.caption_short: str = None
 
     # todo allow for loading from sd-scripts style dict
     def load_caption(self: 'FileItemDTO', caption_dict: Union[dict, None]):
@@ -308,6 +310,10 @@ class CaptionProcessingDTOMixin:
             self.raw_caption = prompt
             self.raw_caption_short = short_caption
 
+        self.caption = self.get_caption()
+        if self.raw_caption_short is not None:
+            self.caption_short = self.get_caption(short_caption=True)
+
     def get_caption(
             self: 'FileItemDTO',
             trigger=None,
@@ -367,12 +373,13 @@ class CaptionProcessingDTOMixin:
                 num_triggers = random.randint(0, num_triggers)
 
             if num_triggers > 0:
+                triggers = random.sample(self.dataset_config.random_triggers, num_triggers)
+                caption = caption + ', ' + ', '.join(triggers)
                 # add random triggers
-                for i in range(num_triggers):
-
-
-
-                    caption = caption + ', ' + random.choice(self.dataset_config.random_triggers)
+                # for i in range(num_triggers):
+                #     # fastest method
+                #     trigger = self.dataset_config.random_triggers[int(random.random() * (len(self.dataset_config.random_triggers)))]
+                #     caption = caption + ', ' + trigger
 
         if self.dataset_config.shuffle_tokens:
             # shuffle again

toolkit/stable_diffusion_model.py

@@ -330,6 +330,7 @@ class StableDiffusion:
                     requires_safety_checker=False,
                     safety_checker=None,
                     variant="fp16",
+                    trust_remote_code=True,
                     **load_args
                 ).to(self.device_torch)
             else:
@@ -341,6 +342,7 @@ class StableDiffusion:
                     requires_safety_checker=False,
                     torch_dtype=self.torch_dtype,
                     safety_checker=None,
+                    trust_remote_code=True,
                     **load_args
                 ).to(self.device_torch)
             flush()