microsoft / Windows-Machine-Learning

Samples and Tools for Windows ML.
https://docs.microsoft.com/en-us/windows/ai/
MIT License
1.02k stars 445 forks source link

Errors evaluating 3D CNN model (Keras) #215

Closed Voxelworld closed 3 years ago

Voxelworld commented 5 years ago

Hello,

I'm submitting a bug report (I searched for similar issues and did not find one).

Current behavior

I build a Keras CNN which is based on 3D operations (Conv3D, MaxPooling3D, Upsampling3D, ..) and converted it with keras2onnx. When I run the ONNX models with the WinMLRunner an exception is raised:

onecoreuap\windows\windowsai\winml\dll\learningmodel.cpp(378)\Windows.AI.MachineLearning.dll!00007FFE4EF7956B: (caller: 00007FFE4EFFB6D9) Exception(2) tid(3364) 80070057 Falscher Parameter. 000001B1CEF4217C

Is Windows ML not capable of running such models?

I tried different model modifications, which all failed:

The attached model version (channels_first [1, 1, 64, 64, 64], keras2onnx 1.3.2, onnx 1.3.0, opset_version 7) runs without errors using the onnxruntime 0.3.0 python package. unet3d.channels_first.keras2onnx.onnx in models.zip

Minimal reproduction of the problem with instructions

Run attached ONNX model in WinMLRunner, or convert attached Keras model (.h5) to an .onnx model first.

Environment

Windows Build Number: Windows 10 Version 1809 (Build 17763.437)

App min and target version: WinMLRunner.exe Version: 1.0.1.0.190321.abf02d3

WinMLTools specific:

Best regards, Volker

zhangxiang1993 commented 5 years ago

Hi,

Thank you for reporting this bug.

  1. After Investigation, we found that WinML only has implementation for Upsample2D, we have already filed a bug for this.
  2. In order to work around it, you could write a custom operator for Upsample3D since the model runs well in OnnxRuntime.

By the way. Could you tell us more about the 3D scenario? e.g. What is the input of your model and what is used for?

Voxelworld commented 5 years ago

Hi Xiang, many thanks for investigating the issue and thanks for the tip!

Best regards Volker

zhangxiang1993 commented 5 years ago

Hi Volker,

  1. For creating custom operators: you could refer the APIs as listed here and we also have a sample project for custom RELU operator .

  2. ConvTranspose is another operator that we don't support 3D. And we have several other operators don't support 3D case either.

  3. In Windows 10 Version 1809, we support operators of ONNX 1.2(opset 7), in Windows 10 Version 1903, we support operators of ONNX 1.3(opset8).

Cheers Xiang

Voxelworld commented 5 years ago

Hi Xiang, thanks for the explanation.

It's a little bit confusing since the ONNX standard describes some of the operations for the generic N-dimensional case, e.g. ConvTranspose. So the operation is documented as part of opset version 1 (ConvTranspose-1). The generic Upsample operation seems to be part of opset 7. As far as the implementation is concerned, it's not as easy, I guess. :-)

  1. Can you make release notes available, to clarify which 3D ops are implemented in the respective Windows ML release?

  2. You said:

    1. After Investigation, we found that WinML only has implementation for Upsample2D, we have already filed a bug for this.

    Will Upsample3D (or perhaps ConvTranspose3D) be available in the next release?

It would be great if 3D operations would be fully supported in the near future to support things like volume- and video-processing.

Cheers Volker

Voxelworld commented 5 years ago

Hi Xiang, any news about 3D WinML improvements in the upcoming Windows release?

Even if the example of the custom ReLu-operator looks simple, a CPU implementation of 3D ConvTranspose or Upsample would be a little painful, and I assume that it would slow down the inference very much since the 3D data (5D tensors) have to pass the CPU-GPU boundary for every node.

Cheers Volker

zhangxiang1993 commented 4 years ago

Hi Volker,

Sorry for the super late reply, the upcoming WinML release will support your model with 3D data on CPU, but not on GPU yet.

Thanks Xiang

Voxelworld commented 4 years ago

Hi Xiang,

that's great news. I'm looking forward to the upcoming release.

Best regards Volker

martinb35 commented 3 years ago

closing per @zhangxiang1993 last comment.