From 15080055bf4330a806c409d3ca69ec5b0eab99f2 Mon Sep 17 00:00:00 2001
From: Volpeon <git@volpeon.ink>
Date: Thu, 22 Jun 2023 11:22:28 +0200
Subject: Update

---
 train_dreambooth.py             | 15 ++-------------
 training/strategy/dreambooth.py | 11 +++++++----
 2 files changed, 9 insertions(+), 17 deletions(-)

diff --git a/train_dreambooth.py b/train_dreambooth.py
index 939a8f3..ab3ed16 100644
--- a/train_dreambooth.py
+++ b/train_dreambooth.py
@@ -217,11 +217,6 @@ def parse_args():
         default=None,
         help="The embeddings directory where Textual Inversion embeddings are stored.",
     )
-    parser.add_argument(
-        "--train_dir_embeddings",
-        action="store_true",
-        help="Train embeddings loaded from embeddings directory.",
-    )
     parser.add_argument(
         "--collection",
         type=str,
@@ -696,19 +691,13 @@ def main():
             tokenizer, embeddings, embeddings_dir
         )
 
-        placeholder_tokens = added_tokens
-        placeholder_token_ids = added_ids
-
         print(
             f"Added {len(added_tokens)} tokens from embeddings dir: {list(zip(added_tokens, added_ids))}"
         )
 
-        if args.train_dir_embeddings:
-            print("Training embeddings from embeddings dir")
-        else:
-            embeddings.persist()
+        embeddings.persist()
 
-    if len(args.placeholder_tokens) != 0 and not args.train_dir_embeddings:
+    if len(args.placeholder_tokens) != 0:
         placeholder_token_ids, initializer_token_ids = add_placeholder_tokens(
             tokenizer=tokenizer,
             embeddings=embeddings,
diff --git a/training/strategy/dreambooth.py b/training/strategy/dreambooth.py
index 43fe838..35cccbb 100644
--- a/training/strategy/dreambooth.py
+++ b/training/strategy/dreambooth.py
@@ -203,10 +203,13 @@ def dreambooth_prepare(
         text_encoder, unet, optimizer, train_dataloader, val_dataloader, lr_scheduler
     )
 
-    for layer in text_encoder.text_model.encoder.layers[
-        : (-1 * text_encoder_unfreeze_last_n_layers)
-    ]:
-        layer.requires_grad_(False)
+    if text_encoder_unfreeze_last_n_layers == 0:
+        text_encoder.text_model.encoder.requires_grad_(False)
+    elif text_encoder_unfreeze_last_n_layers > 0:
+        for layer in text_encoder.text_model.encoder.layers[
+            : (-1 * text_encoder_unfreeze_last_n_layers)
+        ]:
+            layer.requires_grad_(False)
 
     text_encoder.text_model.embeddings.requires_grad_(False)
 
-- 
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