Loading weights: 100%|██████████████████████████████████████████████████████████| 1425/1425 [00:00<00:00, 30210.08it/s]
Loading pipeline components...: 60%|███████████████████████████████▏ | 3/5 [00:01<00:00, 2.26it/s]
01:21.969 operator | ERROR Python: Traceback (most recent call last):
| File "..\site-packages\huggingface_hub\utils\_validators.py", line 88, in _inner_fn
| return fn(*args, **kwargs)
| File "..\site-packages\diffusers\pipelines\pipeline_utils.py", line 1057, in from_pretrained
| loaded_sub_model = load_sub_model(
| library_name=library_name,
| ...<24 lines>...
| trust_remote_code=trust_remote_code,
| )
| File "..\site-packages\diffusers\pipelines\pipeline_loading_utils.py", line 910, in load_sub_model
| loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
| File "..\site-packages\huggingface_hub\utils\_validators.py", line 88, in _inner_fn
| return fn(*args, **kwargs)
| File "..\site-packages\diffusers\models\modeling_utils.py", line 1393, in from_pretrained
| hf_quantizer.preprocess_model(
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
| model=model,
| ^^^^^^^^^^^^
| device_map=device_map,
| ^^^^^^^^^^^^^^^^^^^^^^
| keep_in_fp32_modules=keep_in_fp32_modules,
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
| )
| ^
| File "..\site-packages\diffusers\quantizers\base.py", line 204, in preprocess_model
| return self._process_model_before_weight_loading(model, **kwargs)
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
| File "..\site-packages\sdnq\quantizer.py", line 664, in _process_model_before_weight_loading
| model = sdnq_post_load_quant(model, torch_dtype=self.torch_dtype, pre_quantized=True, **get_quant_args_from_config(self.quantization_config))
| File "..\site-packages\torch\utils\_contextlib.py", line 120, in decorate_context
| return func(*args, **kwargs)
| File "..\site-packages\sdnq\quantizer.py", line 514, in sdnq_post_load_quant
| model, quantization_config = apply_sdnq_to_module(model, quantization_config, torch_dtype=torch_dtype)
| ~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
| File "..\site-packages\torch\utils\_contextlib.py", line 120, in decorate_context
| return func(*args, **kwargs)
| File "..\site-packages\sdnq\quantizer.py", line 439, in apply_sdnq_to_module
| module, quantization_config = apply_sdnq_to_module(module, quantization_config, torch_dtype=torch_dtype, full_param_name=param_name)
| ~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
| File "..\site-packages\torch\utils\_contextlib.py", line 120, in decorate_context
| return func(*args, **kwargs)
| File "..\site-packages\sdnq\quantizer.py", line 434, in apply_sdnq_to_module
| module, quantization_config = sdnq_quantize_layer(module, quantization_config, torch_dtype=torch_dtype, param_name=param_name)
| ~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
| File "..\site-packages\torch\utils\_contextlib.py", line 120, in decorate_context
| return func(*args, **kwargs)
| File "..\site-packages\sdnq\quantizer.py", line 384, in sdnq_quantize_layer
| weight_data = sdnq_quantize_layer_weight(layer.weight, **quant_kwargs)
| File "..\site-packages\torch\utils\_contextlib.py", line 120, in decorate_context
| return func(*args, **kwargs)
| File "..\site-packages\sdnq\quantizer.py", line 145, in sdnq_quantize_layer_weight
| weight, use_hadamard, hadamard_group_size = apply_hadamard(weight, group_size=hadamard_group_size, hadamard=hadamard, layer_class_name=layer_class_name)
| ~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
| File "..\site-packages\torch\utils\_contextlib.py", line 120, in decorate_context
| return func(*args, **kwargs)
| File "..\site-packages\sdnq\quant_utils.py", line 164, in apply_hadamard
| weight = rotate_hadamard(weight, group_size=group_size, hadamard=hadamard, is_conv=is_conv)
| File "..\site-packages\torch\utils\_contextlib.py", line 120, in decorate_context
| return func(*args, **kwargs)
| File "..\site-packages\sdnq\quant_utils.py", line 129, in rotate_hadamard
| hadamard = get_hadamard(group_size, dtype=weight.dtype, device=weight.device)
| File "..\site-packages\torch\utils\_contextlib.py", line 120, in decorate_context
| return func(*args, **kwargs)
| File "..\site-packages\sdnq\quant_utils.py", line 121, in get_hadamard
| H = build_hadamard(n, dtype=dtype, device=device)
| File "..\site-packages\torch\utils\_contextlib.py", line 120, in decorate_context
| return func(*args, **kwargs)
| File "..\site-packages\sdnq\quant_utils.py", line 108, in build_hadamard
| raise RuntimeError("Hadamard Group Size must be a power of 2.")
| RuntimeError: Hadamard Group Size must be a power of 2.
Running this snippet: https://github.com/asomoza/diffusers-recipes/blob/main/models/krea2_turbo/scripts/t2i_sdnq.py gave me the following error: