Merge branch 'master' into master

1 files changed, 14 insertions, 7 deletions

diff --git a/modules/extras.py b/modules/extras.py
index 36123aa5..d8ece955 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -6,7 +6,7 @@ import shutil
 import torch

 import tqdm

 

-from modules import shared, images, sd_models, sd_vae

+from modules import shared, images, sd_models, sd_vae, sd_models_config

 from modules.ui_common import plaintext_to_html

 import gradio as gr

 import safetensors.torch

@@ -37,7 +37,7 @@ def run_pnginfo(image):
 

 def create_config(ckpt_result, config_source, a, b, c):

     def config(x):

-        res = sd_models.find_checkpoint_config(x) if x else None

+        res = sd_models_config.find_checkpoint_config_near_filename(x) if x else None

         return res if res != shared.sd_default_config else None

 

     if config_source == 0:

@@ -132,6 +132,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
     tertiary_model_info = sd_models.checkpoints_list[tertiary_model_name] if theta_func1 else None

 

     result_is_inpainting_model = False

+    result_is_instruct_pix2pix_model = False

 

     if theta_func2:

         shared.state.textinfo = f"Loading B"

@@ -185,14 +186,19 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
             if a.shape != b.shape and a.shape[0:1] + a.shape[2:] == b.shape[0:1] + b.shape[2:]:

                 if a.shape[1] == 4 and b.shape[1] == 9:

                     raise RuntimeError("When merging inpainting model with a normal one, A must be the inpainting model.")

+                if a.shape[1] == 4 and b.shape[1] == 8:

+                    raise RuntimeError("When merging instruct-pix2pix model with a normal one, A must be the instruct-pix2pix model.")

 

-                assert a.shape[1] == 9 and b.shape[1] == 4, f"Bad dimensions for merged layer {key}: A={a.shape}, B={b.shape}"

-

-                theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)

-                result_is_inpainting_model = True

+                if a.shape[1] == 8 and b.shape[1] == 4:#If we have an Instruct-Pix2Pix model...

+                    theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)#Merge only the vectors the models have in common.  Otherwise we get an error due to dimension mismatch.

+                    result_is_instruct_pix2pix_model = True

+                else:

+                    assert a.shape[1] == 9 and b.shape[1] == 4, f"Bad dimensions for merged layer {key}: A={a.shape}, B={b.shape}"

+                    theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)

+                    result_is_inpainting_model = True

             else:

                 theta_0[key] = theta_func2(a, b, multiplier)

-

+            

             theta_0[key] = to_half(theta_0[key], save_as_half)

 

         shared.state.sampling_step += 1

@@ -226,6 +232,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
 

     filename = filename_generator() if custom_name == '' else custom_name

     filename += ".inpainting" if result_is_inpainting_model else ""

+    filename += ".instruct-pix2pix" if result_is_instruct_pix2pix_model else ""

     filename += "." + checkpoint_format

 

     output_modelname = os.path.join(ckpt_dir, filename)