Fixes for most recent webui

with ensuring compatibility for previous webui

patches/clip_hijack.py

@@ -1,5 +1,19 @@
 from modules import sd_hijack_clip, sd_hijack, shared
-from modules.sd_hijack import StableDiffusionModelHijack, EmbeddingsWithFixes, apply_optimizations, fix_checkpoint
+from modules.sd_hijack import StableDiffusionModelHijack, EmbeddingsWithFixes, apply_optimizations
+try:
+    from modules.sd_hijack import fix_checkpoint
+    def clear_any_hijacks():
+        StableDiffusionModelHijack.hijack = default_hijack
+except (ModuleNotFoundError, ImportError):
+    from modules.sd_hijack_checkpoint import add, remove
+    def fix_checkpoint():
+        add()
+
+    def clear_any_hijacks():
+        remove()
+        StableDiffusionModelHijack.hijack = default_hijack
+
+
 import ldm.modules.encoders.modules
 
 default_hijack = StableDiffusionModelHijack.hijack
@@ -16,8 +30,7 @@ def trigger_sd_hijack(enabled, pretrained_key):
         StableDiffusionModelHijack.hijack = default_hijack
 
 
-def clear_any_hijacks():
-    StableDiffusionModelHijack.hijack = default_hijack
+
 
 def create_lambda(model):
     def hijack_lambda(self, m):
@@ -43,6 +56,7 @@ def create_lambda(model):
 
             fix_checkpoint()
 
+
             def flatten(el):
                 flattened = [flatten(children) for children in el.children()]
                 res = [el]

patches/external_pr/hypernetwork.py

@@ -291,7 +291,8 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
     last_saved_file = "<none>"
     last_saved_image = "<none>"
     forced_filename = "<none>"
-
+    if hasattr(sd_hijack_checkpoint, 'add'):
+        sd_hijack_checkpoint.add()
     pbar = tqdm.tqdm(total=steps - initial_step)
     try:
         for i in range((steps - initial_step) * gradient_step):
@@ -466,6 +467,8 @@ Last saved image: {html.escape(last_saved_image)}<br/>
         pbar.close()
         hypernetwork.eval()
         shared.parallel_processing_allowed = old_parallel_processing_allowed
+        if hasattr(sd_hijack_checkpoint, 'remove'):
+            sd_hijack_checkpoint.remove()
     report_statistics(loss_dict)
     filename = os.path.join(shared.cmd_opts.hypernetwork_dir, f'{hypernetwork_name}.pt')
     hypernetwork.optimizer_name = optimizer_name
@@ -755,7 +758,8 @@ def internal_clean_training(hypernetwork_name, data_root, log_directory,
     last_saved_file = "<none>"
     last_saved_image = "<none>"
     forced_filename = "<none>"
-
+    if hasattr(sd_hijack_checkpoint, 'add'):
+        sd_hijack_checkpoint.add()
     pbar = tqdm.tqdm(total=steps - initial_step)
     try:
         for i in range((steps - initial_step) * gradient_step):
@@ -930,6 +934,8 @@ Last saved image: {html.escape(last_saved_image)}<br/>
         pbar.close()
         hypernetwork.eval()
         shared.parallel_processing_allowed = old_parallel_processing_allowed
+        if hasattr(sd_hijack_checkpoint, 'remove'):
+            sd_hijack_checkpoint.remove()
         if shared.opts.training_enable_tensorboard:
             tensorboard_log_hyperparameter(tensorboard_writer, lr=learn_rate,
                                            GA_steps=gradient_step,

patches/external_pr/textual_inversion.py

@@ -14,7 +14,7 @@ from .dataset import PersonalizedBase, PersonalizedDataLoader
 from ..scheduler import CosineAnnealingWarmUpRestarts
 from ..hnutil import optim_to
 
-from modules import shared, devices, sd_models, images, processing, sd_samplers, sd_hijack
+from modules import shared, devices, sd_models, images, processing, sd_samplers, sd_hijack, sd_hijack_checkpoint
 from modules.textual_inversion.image_embedding import caption_image_overlay, insert_image_data_embed, embedding_to_b64
 from modules.textual_inversion.learn_schedule import LearnRateScheduler
 from modules.textual_inversion.textual_inversion import save_embedding
@@ -299,6 +299,8 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
     img_c = None
 
     pbar = tqdm.tqdm(total=steps - initial_step)
+    if hasattr(sd_hijack_checkpoint, 'add'):
+        sd_hijack_checkpoint.add()
     try:
         for i in range((steps - initial_step) * gradient_step):
             if scheduler.finished:
@@ -490,4 +492,6 @@ Last saved image: {html.escape(last_saved_image)}<br/>
         pbar.close()
         shared.sd_model.first_stage_model.to(devices.device)
         shared.parallel_processing_allowed = old_parallel_processing_allowed
+        if hasattr(sd_hijack_checkpoint, 'remove'):
+            sd_hijack_checkpoint.remove()
     return embedding, filename

patches/hypernetwork.py

@@ -16,7 +16,7 @@ import scripts.xy_grid
 from modules.shared import opts
 try:
     from modules.hashes import sha256
-except ImportError or ModuleNotFoundError:
+except (ImportError, ModuleNotFoundError):
     print("modules.hashes is not found, will use backup module from extension!")
     from .hashes_backup import sha256