add pbar back to preloading, remove cruft from testing loss stuff

data/dataset.py

@@ -9,6 +9,8 @@ from data.image_train_item import ImageCaption, ImageTrainItem
 from utils.fs_helpers import *
 from typing import TypeVar, Iterable
 
+from tqdm import tqdm
+
 
 def overlay(overlay, base):
     return overlay if overlay is not None else base
@@ -216,7 +218,7 @@ class Dataset:
     
     def image_train_items(self, aspects):
         items = []
-        for image in self.image_configs:
+        for image in tqdm(self.image_configs, desc="preloading", dynamic_ncols=True):
             config = self.image_configs[image]
             if len(config.main_prompts) > 1:
                 logging.warning(f" *** Found multiple multiple main_prompts for image {image}, but only one will be applied: {config.main_prompts}")

train.py

@@ -811,12 +811,6 @@ def main(args):
 
                 model_pred, target = get_model_prediction_and_target(batch["image"], batch["tokens"], args.zero_frequency_noise_ratio)
 
-                # with torch.no_grad():
-                #     loss_l1 = F.l1_loss(model_pred.float(), target.float(), reduction="mean")
-                #     log_writer.add_scalar(tag="loss/l1", scalar_value=loss_l1, global_step=global_step)
-                #     loss_hinge = F.hinge_embedding_loss(model_pred.float(), target.float(), reduction="mean")
-                #     log_writer.add_scalar(tag="loss/hinge", scalar_value=loss_hinge, global_step=global_step)
-                
                 loss = F.mse_loss(model_pred.float(), target.float(), reduction="mean")
 
                 del target, model_pred