Add --valid_set_repeat

3 files changed, 37 insertions, 1 deletions

diff --git a/data/csv.py b/data/csv.py
index 2f0a392..584a40c 100644
--- a/data/csv.py
+++ b/data/csv.py
@@ -125,6 +125,7 @@ class VlpnDataModule():
         interpolation: str = "bicubic",
         template_key: str = "template",
         valid_set_size: Optional[int] = None,
+        valid_set_repeat: int = 1,
         seed: Optional[int] = None,
         filter: Optional[Callable[[VlpnDataItem], bool]] = None,
         collate_fn=None,
@@ -152,6 +153,7 @@ class VlpnDataModule():
         self.template_key = template_key
         self.interpolation = interpolation
         self.valid_set_size = valid_set_size
+        self.valid_set_repeat = valid_set_repeat
         self.seed = seed
         self.filter = filter
         self.collate_fn = collate_fn
@@ -243,6 +245,7 @@ class VlpnDataModule():
 
         val_dataset = VlpnDataset(
             self.data_val, self.prompt_processor,
+            repeat=self.valid_set_repeat,
             batch_size=self.batch_size, generator=generator,
             size=self.size, interpolation=self.interpolation,
         )
@@ -267,6 +270,7 @@ class VlpnDataset(IterableDataset):
         bucket_step_size: int = 64,
         bucket_max_pixels: Optional[int] = None,
         progressive_buckets: bool = False,
+        repeat: int = 1,
         batch_size: int = 1,
         num_class_images: int = 0,
         size: int = 768,
@@ -275,7 +279,7 @@ class VlpnDataset(IterableDataset):
         interpolation: str = "bicubic",
         generator: Optional[torch.Generator] = None,
     ):
-        self.items = items
+        self.items = items * repeat
         self.batch_size = batch_size
 
         self.prompt_processor = prompt_processor
diff --git a/train_dreambooth.py b/train_dreambooth.py
index d396249..aa5ff01 100644
--- a/train_dreambooth.py
+++ b/train_dreambooth.py
@@ -384,6 +384,12 @@ def parse_args():
         help="Number of images in the validation dataset."
     )
     parser.add_argument(
+        "--valid_set_repeat",
+        type=int,
+        default=None,
+        help="Times the images in the validation dataset are repeated."
+    )
+    parser.add_argument(
         "--train_batch_size",
         type=int,
         default=1,
@@ -451,6 +457,9 @@ def parse_args():
     if isinstance(args.exclude_collections, str):
         args.exclude_collections = [args.exclude_collections]
 
+    if args.valid_set_repeat is None:
+        args.valid_set_repeat = args.train_batch_size
+
     if args.output_dir is None:
         raise ValueError("You must specify --output_dir")
 
@@ -764,6 +773,7 @@ def main():
         dropout=args.tag_dropout,
         template_key=args.train_data_template,
         valid_set_size=args.valid_set_size,
+        valid_set_repeat=args.valid_set_repeat,
         num_workers=args.dataloader_num_workers,
         seed=args.seed,
         filter=keyword_filter,
diff --git a/train_ti.py b/train_ti.py
index 03f52c4..7784d04 100644
--- a/train_ti.py
+++ b/train_ti.py
@@ -381,6 +381,12 @@ def parse_args():
         help="Number of images in the validation dataset."
     )
     parser.add_argument(
+        "--valid_set_repeat",
+        type=int,
+        default=None,
+        help="Times the images in the validation dataset are repeated."
+    )
+    parser.add_argument(
         "--train_batch_size",
         type=int,
         default=1,
@@ -399,6 +405,12 @@ def parse_args():
         help="The weight of prior preservation loss."
     )
     parser.add_argument(
+        "--max_grad_norm",
+        default=3.0,
+        type=float,
+        help="Max gradient norm."
+    )
+    parser.add_argument(
         "--noise_timesteps",
         type=int,
         default=1000,
@@ -465,6 +477,9 @@ def parse_args():
     if isinstance(args.exclude_collections, str):
         args.exclude_collections = [args.exclude_collections]
 
+    if args.valid_set_repeat is None:
+        args.valid_set_repeat = args.train_batch_size
+
     if args.output_dir is None:
         raise ValueError("You must specify --output_dir")
 
@@ -735,6 +750,7 @@ def main():
         dropout=args.tag_dropout,
         template_key=args.train_data_template,
         valid_set_size=args.valid_set_size,
+        valid_set_repeat=args.valid_set_repeat,
         num_workers=args.dataloader_num_workers,
         seed=args.seed,
         filter=keyword_filter,
@@ -961,6 +977,12 @@ def main():
 
                         accelerator.backward(loss)
 
+                        if accelerator.sync_gradients:
+                            accelerator.clip_grad_norm_(
+                                text_encoder.text_model.embeddings.temp_token_embedding.parameters(),
+                                args.max_grad_norm
+                            )
+
                         optimizer.step()
                         if not accelerator.optimizer_step_was_skipped:
                             lr_scheduler.step()