18a7f34ba0
Currently, the nhwc_transformer_test.cc compilation unit defines
explicit FP16 versions of `ModelTestBuilder::MakeInput<MLFloat16>` and
`ModelTestBuilder::MakeInitializer<MLFloat16>` outside of the
ModelTestBuilder class's header file.
These explicit template instantiations cause linker errors when other
compilation units also instantiate these functions due to duplicate
definitions. Additionally, the versions defined in
nhwc_transformer_test.cc do not really conform to the expected behavior
in the original ModelTestBuilder class, which is to make random
input/initializer values. Instead, the versions in
nhwc_transformer_test.cc create a range of values.
The solution is to edit nhwc_transformer_test.cc to use stand-alone
static functions that do not change the ModelTestBuilder class.
**Note**: This linker error cannot currently be replicated in our CIs
because it requires a QNN-HTP-enabled Windows ARM64 environment with
`MLAS_F16VEC_INTRINSICS_SUPPORTED` defined. I can replicate on a local
build. The linker error/conflict happens with with this new FP16 QNN
test:
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ONNX Runtime is a cross-platform inference and training machine-learning accelerator.
ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. Learn more →
ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Learn more →
Get Started & Resources
-
General Information: onnxruntime.ai
-
Usage documentation and tutorials: onnxruntime.ai/docs
-
YouTube video tutorials: youtube.com/@ONNXRuntime
-
Companion sample repositories:
- ONNX Runtime Inferencing: microsoft/onnxruntime-inference-examples
- ONNX Runtime Training: microsoft/onnxruntime-training-examples
Builtin Pipeline Status
| System | Inference | Training |
|---|---|---|
| Windows | ||
| Linux | ||
| Mac | ||
| Android | ||
| iOS | ||
| Web | ||
| Other |
Third-party Pipeline Status
| System | Inference | Training |
|---|---|---|
| Linux |  |
Data/Telemetry
Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the privacy statement for more details.
Contributions and Feedback
We welcome contributions! Please see the contribution guidelines.
For feature requests or bug reports, please file a GitHub Issue.
For general discussion or questions, please use GitHub Discussions.
Code of Conduct
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
License
This project is licensed under the MIT License.