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Getting the following error. Other models works on the GPU and hence the issue is not with GPU or the drivers. This is a INT8 quantized model.
onednn_verbose,info,oneDNN v3.6.0 (commit 4ccd07e3a10e1c08075cf824ac14708245fbc334)
onednn_verbose,primitive,error,gpu,jit::gemm,Insufficient registers in requested bundle
onednn_verbose,primitive,error,gpu,jit::gemm,Insufficient registers in requested bundle
onednn_verbose,info,gpu,runtime:OpenCL
onednn_verbose,primitive,error,gpu,jit::gemm,Insufficient registers in requested bundle
onednn_verbose,primitive,error,gpu,jit::gemm,Insufficient registers in requested bundle
onednn_verbose,primitive,error,gpu,jit::gemm,Insufficient registers in requested bundle
onednn_verbose,info,gpu,engine,0,name:Intel(R) Arc(TM) 140V GPU (16GB),driver_version:32.0.101,binary_kernels:enabled
onednn_verbose,primitive,info,template:operation,engine,primitive,implementation,prop_kind,memory_descriptors,attributes,auxiliary,problem_desc,exec_time
onednn_verbose,primitive,error,gpu,jit::gemm,Insufficient registers in requested bundle
onednn_verbose,primitive,error,gpu,jit::gemm,Insufficient registers in requested bundle
onednn_verbose,primitive,error,gpu,jit::gemm,Insufficient registers in requested bundle
Traceback (most recent call last):
File "C:\Users\devcloud\image_generation\generate_image.py", line 18, in <module>
text2image_pipe.compile()
File "C:\Users\devcloud\image_generation\sd_env\lib\site-packages\optimum\intel\openvino\modeling_diffusion.py", line 687, in compile
component._compile()
File "C:\Users\devcloud\image_generation\sd_env\lib\site-packages\optimum\intel\openvino\modeling_diffusion.py", line 779, in _compile
self.request = core.compile_model(self.model, self._device, self.ov_config)
File "C:\Users\devcloud\image_generation\sd_env\lib\site-packages\openvino\runtime\ie_api.py", line 543, in compile_model
super().compile_model(model, device_name, {} if config is None else config),
RuntimeError: Exception from src/inference/src/cpp/core.cpp:107:
Exception from src/inference/src/dev/plugin.cpp:53:
Check 'false' failed at src/plugins/intel_gpu/src/plugin/program_builder.cpp:185:
[GPU] ProgramBuilder build failed!
Exception from src/plugins/intel_gpu/src/graph/include\primitive_type_base.h:59:
[GPU] Can't choose implementation for fullyconnectedcompressed:__module.model.down_blocks.1.resnets.0.time_emb_proj/aten::linear/MatMul node (type=fully_connected)
[GPU] Original name: __module.model.down_blocks.1.resnets.0.time_emb_proj/aten::linear/MatMul
[GPU] Original type: FullyConnectedCompressed
[GPU] Reason: could not create a primitive
Step-by-step reproduction
importtorchfromtimeimporttimefrompathlibimportPathfromoptimum.intelimportOVStableDiffusionXLPipelinestart=time()
model_dir=Path("model_int8")
device='CPU'text2image_pipe=OVStableDiffusionXLPipeline.from_pretrained(model_dir, device=device)
# Define the shapes related to the inputs and desired outputsbatch_size, num_images, height, width=1, 1, 512, 512# Statically reshape the modeltext2image_pipe.reshape(batch_size, height, width, num_images)
# Compile the model before inferencetext2image_pipe.compile()
prompt="cute cat 4k, high-res, masterpiece, best quality, full hd, extremely detailed, soft lighting, dynamic angle, 35mm"image=text2image_pipe(
prompt,
num_inference_steps=25,
height=height,
width=width,
num_images_per_prompt=num_images,
generator=torch.Generator(device="cpu").manual_seed(903512),
).images[0]
image.save("cat.png")
end=time()
time_taken=end-startprint(f"Time taken for image generation: {time_taken:.2f} seconds")
Relevant log output
No response
Issue submission checklist
I'm reporting an issue. It's not a question.
I checked the problem with the documentation, FAQ, open issues, Stack Overflow, etc., and have not found a solution.
There is reproducer code and related data files such as images, videos, models, etc.
The text was updated successfully, but these errors were encountered:
You mentioned other models, is it the same model with different precision or they are completely different model?
Did you use this command optimum-cli export openvino -m stabilityai/stable-diffusion-xl-base-1.0 --weight-format int8 {model_dir} as implemented in the openvino-notebook, to get the INT8 format?
Did you convert and run the model using OV 2024? (this is to confirm whether you use converted model files from older version into newer)
You mentioned other models, is it the same model with different precision or they are completely different model?
Did you use this command optimum-cli export openvino -m stabilityai/stable-diffusion-xl-base-1.0 --weight-format int8 {model_dir} as implemented in the openvino-notebook, to get the INT8 format?
Did you convert and run the model using OV 2024? (this is to confirm whether you use converted model files from older version into newer)
Quantized the model with Optimum CLI and used OV 2024.4 version which is the latest. Will test it once more after getting access to the system.
OpenVINO Version
2024.4
Operating System
Windows System
Device used for inference
GPU
Framework
None
Model used
stabilityai/stable-diffusion-xl-base-1.0
Issue description
Trying to follow the below notebook on a LNL Windows machine targeting iGPU.
https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/stable-diffusion-xl/stable-diffusion-xl.ipynb
Getting the following error. Other models works on the GPU and hence the issue is not with GPU or the drivers. This is a INT8 quantized model.
Step-by-step reproduction
Relevant log output
No response
Issue submission checklist
The text was updated successfully, but these errors were encountered: