update transformers and fix quant params

Signed-off-by: Vladimir Mandic <mandic00@live.com>

installer.py

@@ -637,7 +637,7 @@ def check_transformers():
         target_transformers = '4.52.4'
         target_tokenizers = '0.21.4'
     else:
-        target_transformers = '4.56.2'
+        target_transformers = '4.57.1'
         target_tokenizers = '0.22.1'
     if (pkg_transformers is None) or ((pkg_transformers.version != target_transformers) or (pkg_tokenizers is None) or ((pkg_tokenizers.version != target_tokenizers) and (not args.experimental))):
         if pkg_transformers is None:

modules/ltx/ltx_process.py

@@ -66,7 +66,10 @@ def run_ltx(task_id,
         progress.finish_task(task_id)
         yield None, f'LTX Error: {str(e)}'
 
-    from diffusers import LTXConditionPipeline # pylint: disable=unused-import
+    if model is None or len(model) == 0:
+        yield from abort('Video: no model selected', ok=True)
+        return
+    # from diffusers import LTXConditionPipeline # pylint: disable=unused-import
     check_av()
     progress.add_task_to_queue(task_id)
     with queue_lock:
@@ -76,6 +79,10 @@ def run_ltx(task_id,
         yield None, 'LTX: Loading...'
         engine = 'LTX Video'
         load_model(engine, model)
+        debug(f'Video: cls={shared.sd_model.__class__.__name__} op=init model="{model}"')
+        if not shared.sd_model.__class__.__name__.startswith("LTX"):
+            yield from abort(f'Video: cls={shared.sd_model.__class__.__name__} selected model is not LTX model', ok=True)
+            return
 
         videojob = shared.state.begin('Video', task_id=task_id)
         shared.state.job_count = 1

modules/ltx/ltx_util.py

@@ -8,6 +8,8 @@ loaded_model: str = None
 
 
 def get_bucket(size: int):
+    if not hasattr(shared.sd_model, 'vae_temporal_compression_ratio'):
+        return int(size) - (int(size) % 16)
     return int(size) - (int(size) % shared.sd_model.vae_temporal_compression_ratio)
 
 
@@ -19,6 +21,10 @@ def load_model(engine: str, model: str):
     global loaded_model # pylint: disable=global-statement
     if loaded_model == model:
         return
+    if model is None or model == '' or model=='None':
+        loaded_model = None
+        shared.sd_model = None
+        return
     t0 = time.time()
     from modules.video_models import models_def, video_load
     selected: models_def.Model = [m for m in models_def.models[engine] if m.name == model][0]

modules/sdnq/quantizer.py

@@ -497,7 +497,7 @@ class SDNQQuantizer(DiffusersQuantizer, HfQuantizer):
         param_value: torch.FloatTensor,
         param_name: str,
         target_device: torch.device,
-        state_dict: Dict[str, Any],
+        # state_dict: Dict[str, Any], # removed in transformers==4.57
         *args, **kwargs, # pylint: disable=unused-argument
     ):
         if self.pre_quantized:

modules/video_models/video_load.py

@@ -8,7 +8,7 @@ loaded_model = None
 
 
 def load_model(selected: models_def.Model):
-    if selected is None:
+    if selected is None or selected.te_cls is None or selected.dit_cls is None:
         return ''
     global loaded_model # pylint: disable=global-statement
     if loaded_model == selected.name:

requirements.txt

@@ -35,8 +35,8 @@ rich==14.1.0
 safetensors==0.6.2
 tensordict==0.8.3
 peft==0.17.1
-httpx==0.24.1
-compel==2.1.1
+httpx==0.28.1
+compel==2.2.1
 torchsde==0.2.6
 antlr4-python3-runtime==4.9.3
 requests==2.32.4