Merge branch 'AUTOMATIC1111:master' into master

1 files changed, 13 insertions, 4 deletions

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 841402e8..9355f1e1 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -230,15 +230,19 @@ def select_checkpoint():
     return checkpoint_info

 

 

-checkpoint_dict_replacements = {

+checkpoint_dict_replacements_sd1 = {

     'cond_stage_model.transformer.embeddings.': 'cond_stage_model.transformer.text_model.embeddings.',

     'cond_stage_model.transformer.encoder.': 'cond_stage_model.transformer.text_model.encoder.',

     'cond_stage_model.transformer.final_layer_norm.': 'cond_stage_model.transformer.text_model.final_layer_norm.',

 }

 

+checkpoint_dict_replacements_sd2_turbo = { # Converts SD 2.1 Turbo from SGM to LDM format.

+    'conditioner.embedders.0.': 'cond_stage_model.',

+}

+

 

-def transform_checkpoint_dict_key(k):

-    for text, replacement in checkpoint_dict_replacements.items():

+def transform_checkpoint_dict_key(k, replacements):

+    for text, replacement in replacements.items():

         if k.startswith(text):

             k = replacement + k[len(text):]

 

@@ -249,9 +253,14 @@ def get_state_dict_from_checkpoint(pl_sd):
     pl_sd = pl_sd.pop("state_dict", pl_sd)

     pl_sd.pop("state_dict", None)

 

+    is_sd2_turbo = 'conditioner.embedders.0.model.ln_final.weight' in pl_sd and pl_sd['conditioner.embedders.0.model.ln_final.weight'].size()[0] == 1024

+

     sd = {}

     for k, v in pl_sd.items():

-        new_key = transform_checkpoint_dict_key(k)

+        if is_sd2_turbo:

+            new_key = transform_checkpoint_dict_key(k, checkpoint_dict_replacements_sd2_turbo)

+        else:

+            new_key = transform_checkpoint_dict_key(k, checkpoint_dict_replacements_sd1)

 

         if new_key is not None:

             sd[new_key] = v