fix grid with lora, add dlss framgen logging, add 8bit minimax variants

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

CHANGELOG.md

@@ -33,7 +33,7 @@ Plus inevitable bug-fixes...
     with support for text-to-image, vq-conditioned text-to-image and image-editing workflows  
     *note* model is extremely quantization sensitive so minimum allowed quant type is `uint8`  
   - [MiniMax-H3](https://huggingface.co/MiniMaxAI/MiniMax-H3) updates  
-    new [SDNQ-uint8](https://huggingface.co/OzzyGT/MiniMax_H3_sdnq_8bit_pruned) pre-quantized *pruned* variants  
+    new [SDNQ-uint8](https://huggingface.co/OzzyGT/MiniMax_H3_sdnq_8bit_pruned) pre-quantized *base* and *pruned* variants  
     new [Nunchaku-Lite](https://huggingface.co/rootonchair/MiniMax-H3-nunchaku-lite-int4) variant  
     new [VDN](https://huggingface.co/OpenVDN/vdn-minimax-h3) *video-delta-net* variant  
 - **LoRA**

data/reference-quantized.json

@@ -275,5 +275,39 @@
     "extras": "sampler: Default",
     "size": 23.70,
     "date": "2026 August"
+  },
+  "MiniMaxAI MiniMax-H3 sdnq-uint8": {
+    "path": "OzzyGT/MiniMax_H3_sdnq_dynamic_8bit",
+    "preview": "MiniMaxAI--MiniMax-H3.jpg",
+    "desc": "Quantization of MiniMaxAI/MiniMax-H3 using SDNQ: dynamic 8-bit uint. Video with synchronized audio; in image tabs the model runs in experimental still mode.",
+    "extras": "sampler: Default",
+    "size": 32.29,
+    "date": "2026 August"
+  },
+  "MiniMaxAI MiniMax-H3 sdnq-uint8 Ref2VA": {
+    "path": "OzzyGT/MiniMax_H3_sdnq_dynamic_8bit",
+    "preview": "MiniMaxAI--MiniMax-H3.jpg",
+    "subfolder": "ref2va",
+    "desc": "Quantization of MiniMaxAI/MiniMax-H3 using SDNQ: dynamic 8-bit uint. Video with synchronized audio; in image tabs the model runs in experimental still mode.",
+    "extras": "sampler: Default",
+    "size": 32.29,
+    "date": "2026 August"
+  },
+  "MiniMaxAI MiniMax-H3 Pruned sdnq-uint8": {
+    "path": "OzzyGT/MiniMax_H3_sdnq_8bit_pruned",
+    "preview": "MiniMaxAI--MiniMax-H3.jpg",
+    "desc": "Quantization of MiniMaxAI/MiniMax-H3 using SDNQ: dynamic 8-bit uint. Video with synchronized audio; in image tabs the model runs in experimental still mode.",
+    "extras": "sampler: Default",
+    "size": 32.29,
+    "date": "2026 August"
+  },
+  "MiniMaxAI MiniMax-H3 Pruned sdnq-uint8 Ref2VA": {
+    "path": "OzzyGT/MiniMax_H3_sdnq_8bit_pruned",
+    "preview": "MiniMaxAI--MiniMax-H3.jpg",
+    "subfolder": "ref2va",
+    "desc": "Quantization of MiniMaxAI/MiniMax-H3 using SDNQ: dynamic 8-bit uint. Video with synchronized audio; in image tabs the model runs in experimental still mode.",
+    "extras": "sampler: Default",
+    "size": 32.29,
+    "date": "2026 August"
   }
 }

modules/image/grid.py

@@ -154,7 +154,7 @@ def get_font(fontsize: float):
 def draw_grid_annotations(im: Image.Image, width: int, height: int, x_texts: list[list[GridAnnotation]], y_texts: list[list[GridAnnotation]], margin=0, title: list[GridAnnotation] | None = None):
     def wrap(drawing: ImageDraw.ImageDraw, text, font, line_length):
         lines = ['']
-        for word in text.split():
+        for word in text.split('/\\'):
             line = f'{lines[-1]} {word}'.strip()
             if drawing.textlength(line, font=font) <= line_length:
                 lines[-1] = line
@@ -162,7 +162,7 @@ def draw_grid_annotations(im: Image.Image, width: int, height: int, x_texts: lis
                 lines.append(word)
         return lines
 
-    def draw_texts(drawing: ImageDraw.ImageDraw, draw_x: float, draw_y: float, lines, initial_fnt: ImageFont.FreeTypeFont, initial_fontsize: int):
+    def draw_texts(drawing: ImageDraw.ImageDraw, draw_x: float, draw_y: float, lines: list[GridAnnotation], initial_fnt: ImageFont.FreeTypeFont, initial_fontsize: int):
         for line in lines:
             font = initial_fnt
             fontsize = initial_fontsize

modules/lora/lora_load.py

@@ -322,6 +322,8 @@ def network_load(names, te_multipliers=None, unet_multipliers=None, dyn_dims=Non
         if net is None:
             failed_to_load_networks.append(name)
             lora_ver = network_on_disk.sd_version if network_on_disk is not None else None
+            if lora_ver is None or len(lora_ver) == 0:
+                lora_ver = "unknown"
             log.error(f'Network load: type=LoRA name="{name}" detected={lora_ver} not loaded')
             continue
         if hasattr(sd_model, 'embedding_db'):

modules/sd_hijack_modular.py

@@ -39,6 +39,8 @@ def modular_step(components: diffusers.modular_pipelines.ModularPipeline, state:
 
 
 def modular_intercept(self, components, state: diffusers.modular_pipelines.modular_pipeline.BlockState, *args, **kwargs):
+    if shared.state.interrupted or shared.state.skipped:
+        raise AssertionError('Interrupted...')
     t0 = time.time()
     block = type(self).__name__
     # run code before block call
@@ -117,6 +119,8 @@ def install_state_hook(pipe):
 
     def set_phase(phase: str, module: torch.nn.Module | None = None):
         # every stage runs inside one pipeline call, so the forward hooks are the only place the current stage is visible
+        if shared.state.interrupted or shared.state.skipped:
+            raise AssertionError('Interrupted...')
         if getattr(pipe, 'sdnext_phase', None) != phase:
             pipe.sdnext_phase = phase
             jobid = getattr(pipe, 'sdnext_phaseid', None) # previous jobid if any

scripts/dlss/framegen.py

@@ -93,8 +93,7 @@ class DLSSFrameGen:
                 capabilities = probe_frame_interpolation_capabilities(options.ai_gpu_uuid)
                 log.debug(f'DLSSFrameGen: capabilities={capabilities}')
                 if not capabilities.available:
-                    raise StandaloneError("feature_unavailable", "FrameGen: unavailable. " + capabilities.detail,
-                    )
+                    raise StandaloneError("feature_unavailable", "FrameGen: unavailable. " + capabilities.detail)
                 plan = choose_interpolation_plan(
                     source_rate,
                     target_rate,
@@ -102,6 +101,7 @@ class DLSSFrameGen:
                     capabilities.native_multiplier,
                     cfr=True,
                 )
+                log.debug(f'DLSSFrameGen: plan={plan}')
                 source_frames = [
                     _TimedFrame(rgb_to_rgba(nchw_image_to_hwc(frames, index, name="frames")), Fraction(index, 1) / source_rate)
                     for index in range(batch)
@@ -146,6 +146,7 @@ class DLSSFrameGen:
             ideal = Fraction(index, 1) / target_rate
             selected = min(frames, key=lambda frame, target=ideal: abs(frame.timestamp - target))
             result.append(_TimedFrame(selected.rgba.copy(), ideal))
+        log.debug(f'DLSSFrameGen: input={len(frames)} resampled={len(result)}')
         return result
 
     @staticmethod
@@ -155,6 +156,7 @@ class DLSSFrameGen:
         try:
             stage_count = plan.cascade_stages or 1
             for stage_index in range(stage_count):
+                log.debug(f'DirectDLSSGSession: index={stage_index + 1} count={stage_count} stage create')
                 generated_count = (
                     plan.generated_per_interval
                     if plan.path == "Native DLSSG"
@@ -195,6 +197,7 @@ class DLSSFrameGen:
             return result
         finally:
             for session in reversed(sessions):
+                log.debug(f'DirectDLSSGSession: session={session} close')
                 try:
                     session.close()
                 except (OSError, RuntimeError, ValueError):

scripts/dlss_ext.py

@@ -62,10 +62,10 @@ def create_ui(parent):
             with gr.Row():
                 fg_enabled = gr.Checkbox(label='FG enable', value=False, elem_id='dlss_fg_enabled')
             with gr.Row():
-                fg_source_fps = gr.Dropdown(label='Source FPS', choices=FPS_CHOICES, value='23.976', elem_id='dlss_fg_source_fps')
-                fg_target_fps = gr.Dropdown(label='Target FPS', choices=FPS_CHOICES, value='60', elem_id='dlss_fg_target_fps')
+                fg_source_fps = gr.Dropdown(label='FG source FPS', choices=FPS_CHOICES, value='23.976', elem_id='dlss_fg_source_fps')
+                fg_target_fps = gr.Dropdown(label='FG target FPS', choices=FPS_CHOICES, value='60', elem_id='dlss_fg_target_fps')
             with gr.Row():
-                fg_engine = gr.Dropdown(label='Engine', choices=['Auto', 'Native DLSSG', 'Cascade'], value='Auto', elem_id='dlss_fg_engine')
+                fg_engine = gr.Dropdown(label='FG engine', choices=['Auto', 'Native DLSSG', 'Cascade'], value='Auto', elem_id='dlss_fg_engine')
 
         with gr.Accordion('DLSS Status', open=True, elem_id='dlss_status'):
             ss_status = gr.JSON({ 'Status': 'unknown' if len(shared.opts.dlss_pkg_path) < 4 else 'stored'})
@@ -231,9 +231,10 @@ def framegen(pkg_path, images, fg_source_fps, fg_target_fps, fg_engine):
         if debug:
             log.trace(f'DLSS: method=FrameGen input={frames.shape} options={options}')
         response = c.controller.call(
-            pkg_path, 'framegen',
+            pkg_path,
+            'framegen',
             { 'frames': frames, 'source_fps': fg_source_fps, 'target_fps': fg_target_fps, 'options': options },
-            timeout=300.0,
+            timeout=600.0,
         )
         if response.get('status') != 'ok':
             error = response.get('error') or {}
@@ -333,10 +334,11 @@ def dlss(p: processing.StableDiffusionProcessing | None, pp: processing.Processe
         t0 = time.time()
         if p:
             p.extra_generation_params["DLSSFrameGen"] = True
-        log.info(f'DLSS: method=FrameGen source={fg_source_fps} target={fg_target_fps} engine={fg_engine}')
+        log.info(f'DLSS: method=FrameGen source={fg_source_fps} target={fg_target_fps} engine="{fg_engine}"')
         output = framegen(pkg_path, current_images, fg_source_fps, fg_target_fps, fg_engine)
         if debug:
-            log.trace(f'DLSS: method=FrameGen images={len(output) if output else 0} time={time.time() - t0:.3f}')
+            t1 = time.time()
+            log.trace(f'DLSS: method=FrameGen frames={len(output) if output else 0} time={t1 - t0:.3f}')
         if output:
             images = output
             current_images = output

scripts/xyz_grid.py

@@ -330,6 +330,7 @@ class XYZGridScript(scripts_manager.Script):
                 return processing.Processed(p, [], p.seed, ""), 0
             p.xyz = True
             pc = copy(p)
+            pc.network_data = None
             pc.override_settings_restore_afterwards = False
             pc.styles = pc.styles[:]
             x_opt.apply(pc, x, xs)

scripts/xyz_grid_on.py

@@ -352,6 +352,7 @@ class XYZGridScript(scripts_manager.Script):
                     return processing.Processed(p, [], p.seed, ""), 0
             p.xyz = True
             pc = copy(p)
+            pc.network_data = None
             pc.override_settings_restore_afterwards = False
             pc.styles = pc.styles[:]
             if no_fixed_seeds: