Merge branch 'release_candidate'

1 files changed, 42 insertions, 11 deletions

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 36f643e1..b1afbaa7 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -15,9 +15,9 @@ import ldm.modules.midas as midas
 from ldm.util import instantiate_from_config

 

 from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config

-from modules.paths import models_path

 from modules.sd_hijack_inpainting import do_inpainting_hijack

 from modules.timer import Timer

+import tomesd

 

 model_dir = "Stable-diffusion"

 model_path = os.path.abspath(os.path.join(paths.models_path, model_dir))

@@ -87,8 +87,7 @@ class CheckpointInfo:
 

 try:

     # this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start.

-

-    from transformers import logging, CLIPModel

+    from transformers import logging, CLIPModel  # noqa: F401

 

     logging.set_verbosity_error()

 except Exception:

@@ -99,7 +98,6 @@ def setup_model():
     if not os.path.exists(model_path):

         os.makedirs(model_path)

 

-    list_models()

     enable_midas_autodownload()

 

 

@@ -167,7 +165,7 @@ def model_hash(filename):
 

 def select_checkpoint():

     model_checkpoint = shared.opts.sd_model_checkpoint

-        

+

     checkpoint_info = checkpoint_alisases.get(model_checkpoint, None)

     if checkpoint_info is not None:

         return checkpoint_info

@@ -239,7 +237,7 @@ def read_metadata_from_safetensors(filename):
             if isinstance(v, str) and v[0:1] == '{':

                 try:

                     res[k] = json.loads(v)

-                except Exception as e:

+                except Exception:

                     pass

 

         return res

@@ -374,7 +372,7 @@ def enable_midas_autodownload():
         if not os.path.exists(path):

             if not os.path.exists(midas_path):

                 mkdir(midas_path)

-    

+

             print(f"Downloading midas model weights for {model_type} to {path}")

             request.urlretrieve(midas_urls[model_type], path)

             print(f"{model_type} downloaded")

@@ -410,11 +408,18 @@ sd2_clip_weight = 'cond_stage_model.model.transformer.resblocks.0.attn.in_proj_w
 class SdModelData:

     def __init__(self):

         self.sd_model = None

+        self.was_loaded_at_least_once = False

         self.lock = threading.Lock()

 

     def get_sd_model(self):

+        if self.was_loaded_at_least_once:

+            return self.sd_model

+

         if self.sd_model is None:

             with self.lock:

+                if self.sd_model is not None or self.was_loaded_at_least_once:

+                    return self.sd_model

+

                 try:

                     load_model()

                 except Exception as e:

@@ -467,7 +472,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
     try:

         with sd_disable_initialization.DisableInitialization(disable_clip=clip_is_included_into_sd):

             sd_model = instantiate_from_config(sd_config.model)

-    except Exception as e:

+    except Exception:

         pass

 

     if sd_model is None:

@@ -493,6 +498,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
 

     sd_model.eval()

     model_data.sd_model = sd_model

+    model_data.was_loaded_at_least_once = True

 

     sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True)  # Reload embeddings after model load as they may or may not fit the model

 

@@ -538,13 +544,12 @@ def reload_model_weights(sd_model=None, info=None):
 

     if sd_model is None or checkpoint_config != sd_model.used_config:

         del sd_model

-        checkpoints_loaded.clear()

         load_model(checkpoint_info, already_loaded_state_dict=state_dict)

         return model_data.sd_model

 

     try:

         load_model_weights(sd_model, checkpoint_info, state_dict, timer)

-    except Exception as e:

+    except Exception:

         print("Failed to load checkpoint, restoring previous")

         load_model_weights(sd_model, current_checkpoint_info, None, timer)

         raise

@@ -565,7 +570,7 @@ def reload_model_weights(sd_model=None, info=None):
 

 

 def unload_model_weights(sd_model=None, info=None):

-    from modules import lowvram, devices, sd_hijack

+    from modules import devices, sd_hijack

     timer = Timer()

 

     if model_data.sd_model:

@@ -580,3 +585,29 @@ def unload_model_weights(sd_model=None, info=None):
     print(f"Unloaded weights {timer.summary()}.")

 

     return sd_model

+

+

+def apply_token_merging(sd_model, token_merging_ratio):

+    """

+    Applies speed and memory optimizations from tomesd.

+    """

+

+    current_token_merging_ratio = getattr(sd_model, 'applied_token_merged_ratio', 0)

+

+    if current_token_merging_ratio == token_merging_ratio:

+        return

+

+    if current_token_merging_ratio > 0:

+        tomesd.remove_patch(sd_model)

+

+    if token_merging_ratio > 0:

+        tomesd.apply_patch(

+            sd_model,

+            ratio=token_merging_ratio,

+            use_rand=False,  # can cause issues with some samplers

+            merge_attn=True,

+            merge_crossattn=False,

+            merge_mlp=False

+        )

+

+    sd_model.applied_token_merged_ratio = token_merging_ratio