monkeypatch numpy for gradio

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

CHANGELOG.md

@@ -93,7 +93,8 @@ Although upgrades and existing installations are tested and should work fine!
   - override `gradio` installer  
   - major refactoring of requirements and dependencies to unblock `numpy>=2.1.0`  
   - patch `insightface`  
-  - patch `facelib`
+  - patch `facelib`  
+  - patch `numpy`  
   - stronger lint rules  
     add separate `npm run lint`, `npm run todo`, `npm run test`, `npm run format` macros  
 

TODO.md

@@ -4,16 +4,15 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
 
 ## Current
 
+- Bug: FramePack with SQND  
+
 ## Future Candidates
 
 - Feature: Common repo for `T5` and `CLiP`  
 - Feature: LoRA add OMI format support for SD35/FLUX.1  
 - Feature: Merge FramePack into core  
 - Refactor: sampler options  
-- Refactor: cleanup `/repositories/codeformer`  
-- Remove: Agent Scheduler  
 - Video: API support  
-- ModernUI: Lite vs Expert mode  
 
 ### Blocked items
 
@@ -32,6 +31,8 @@ Main ToDo list can be found at [GitHub projects](https://github.com/users/vladma
 - [Nunchaku PulID](https://github.com/mit-han-lab/nunchaku/pull/274)  
 - [Dream0 guidance](https://huggingface.co/ByteDance/DreamO)  
 - [SUPIR upscaler](https://github.com/Fanghua-Yu/SUPIR)  
+- Remove: Agent Scheduler  
+- ModernUI: Lite vs Expert mode  
 
 ### Future Considerations
 - [TensorRT](https://github.com/huggingface/diffusers/pull/11173)  

modules/loader.py

@@ -18,10 +18,16 @@ np = None
 try:
     import numpy as np # pylint: disable=W0611,C0411
     import numpy.random # pylint: disable=W0611,C0411 # this causes failure if numpy version changed
+    def obj2sctype(obj):
+        return np.dtype(obj).type
+    np.obj2sctype = obj2sctype # noqa: NPY201
+    np.bool8 = np.bool
+    np.float_ = np.float64 # noqa: NPY201
 except Exception as e:
     errors.log.error(f'Loader: numpy=={np.__version__ if np is not None else None} {e}')
     errors.log.error('Please restart the app to fix this issue')
     sys.exit(1)
+timer.startup.record("numpy")
 
 try:
     import scipy # pylint: disable=W0611,C0411
@@ -29,6 +35,7 @@ except Exception as e:
     errors.log.error(f'Loader: scipy=={np.__version__ if np is not None else None} {e}')
     errors.log.error('Please restart the app to fix this issue')
     sys.exit(1)
+timer.startup.record("scipy")
 
 import torch # pylint: disable=C0411
 if torch.__version__.startswith('2.5.0'):
@@ -64,12 +71,12 @@ if ".dev" in torch.__version__ or "+git" in torch.__version__:
     torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0)
 timer.startup.record("torch")
 
-
 try:
     import bitsandbytes # pylint: disable=W0611,C0411
 except Exception:
     from diffusers.utils import import_utils
     import_utils._bitsandbytes_available = False # pylint: disable=protected-access
+timer.startup.record("bnb")
 
 import transformers # pylint: disable=W0611,C0411
 from transformers import logging as transformers_logging # pylint: disable=W0611,C0411

modules/sdnq/__init__.py

@@ -54,7 +54,10 @@ def sdnq_quantize_layer(layer, weights_dtype="int8", torch_dtype=None, group_siz
         else:
             is_linear_type = True
             reduction_axes = -1
-            output_channel_size, channel_size = layer.weight.shape
+            try:
+                output_channel_size, channel_size = layer.weight.shape
+            except Exception as e:
+                raise ValueError(f"SDNQ: layer_class_name={layer_class_name} layer_weight_shape={layer.weight.shape} weights_dtype={weights_dtype} unsupported") from e
             if use_quantized_matmul:
                 use_quantized_matmul = weights_dtype in quantized_matmul_dtypes and channel_size >= 32 and output_channel_size >= 32
                 if use_quantized_matmul: