1 files changed, 5 insertions, 5 deletions
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index fa4bbe00..529ed3e2 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -153,7 +153,7 @@ class EmbeddingDatabase:
         return None, None
 
 
-def create_embedding(name, num_vectors_per_token, init_text='*'):
+def create_embedding(name, num_vectors_per_token, overwrite_old, init_text='*'):
     cond_model = shared.sd_model.cond_stage_model
     embedding_layer = cond_model.wrapped.transformer.text_model.embeddings
 
@@ -165,7 +165,8 @@ def create_embedding(name, num_vectors_per_token, init_text='*'):
         vec[i] = embedded[i * int(embedded.shape[0]) // num_vectors_per_token]
 
     fn = os.path.join(shared.cmd_opts.embeddings_dir, f"{name}.pt")
-    assert not os.path.exists(fn), f"file {fn} already exists"
+    if not overwrite_old:
+        assert not os.path.exists(fn), f"file {fn} already exists"
 
     embedding = Embedding(vec, name)
     embedding.step = 0
@@ -271,10 +272,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
 
             losses[embedding.step % losses.shape[0]] = loss.item()
 
+            optimizer.zero_grad()
             loss.backward()
-            if ((i + 1) % gradient_accumulation == 0) or (i + 1 == steps - ititial_step):
-                optimizer.step()
-                optimizer.zero_grad()
+            optimizer.step()
 
 
         epoch_num = embedding.step // len(ds)