Merge branch 'AUTOMATIC1111:master' into master

1 files changed, 4 insertions, 1 deletions

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index 4eb75cb5..e28c357a 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -269,6 +269,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
 

    # dataset loading may take a while, so input validations and early returns should be done before this

     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."

+    old_parallel_processing_allowed = shared.parallel_processing_allowed

     

     pin_memory = shared.opts.pin_memory

     

@@ -279,6 +280,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
     dl = modules.textual_inversion.dataset.PersonalizedDataLoader(ds, latent_sampling_method=latent_sampling_method, batch_size=ds.batch_size, pin_memory=pin_memory)

 

     if unload:

+        shared.parallel_processing_allowed = False

         shared.sd_model.first_stage_model.to(devices.cpu)

 

     embedding.vec.requires_grad = True

@@ -316,7 +318,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
                 if shared.state.interrupted:

                     break

 

-                with torch.autocast("cuda"):

+                with devices.autocast():

                     # c = stack_conds(batch.cond).to(devices.device)

                     # mask = torch.tensor(batch.emb_index).to(devices.device, non_blocking=pin_memory)

                     # print(mask)

@@ -450,6 +452,7 @@ Last saved image: {html.escape(last_saved_image)}<br/>
         pbar.leave = False

         pbar.close()

         shared.sd_model.first_stage_model.to(devices.device)

+        shared.parallel_processing_allowed = old_parallel_processing_allowed

 

     return embedding, filename