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ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
4e73cc83d6
Before this change, building DNNL EP from onnxruntime 1.10.0 with clang fails with:
In file included from /build/python-onnxruntime/src/onnxruntime/onnxruntime/core/providers/dnnl/subgraph/dnnl_squeeze.cc:4:
In file included from /build/python-onnxruntime/src/onnxruntime/onnxruntime/core/providers/dnnl/subgraph/dnnl_squeeze.h:5:
In file included from /build/python-onnxruntime/src/onnxruntime/onnxruntime/core/providers/dnnl/subgraph/dnnl_subgraph.h:10:
In file included from /build/python-onnxruntime/src/onnxruntime/onnxruntime/core/providers/shared_library/provider_api.h:19:
In file included from /build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/common/common.h:36:
/build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/common/make_string.h:33:6: error: call to function 'operator<<' that is neither visible in the template definition nor found by argument-dependent lookup
ss << t;
^
/build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/common/make_string.h:39:3: note: in instantiation of function template specialization 'onnxruntime::detail::MakeStringImpl<std::vector<long>>' requested here
MakeStringImpl(ss, args...);
^
/build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/common/make_string.h:39:3: note: in instantiation of function template specialization 'onnxruntime::detail::MakeStringImpl<const char *, std::vector<long>>' requested here
/build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/common/make_string.h:39:3: note: in instantiation of function template specialization 'onnxruntime::detail::MakeStringImpl<long, const char *, std::vector<long>>' requested here
/build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/common/make_string.h:39:3: note: in instantiation of function template specialization 'onnxruntime::detail::MakeStringImpl<const char *, long, const char *, std::vector<long>>' requested here
/build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/common/make_string.h:39:3: note: in instantiation of function template specialization 'onnxruntime::detail::MakeStringImpl<unsigned long, const char *, long, const char *, std::vector<long>>' requested here
/build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/common/make_string.h:46:3: note: in instantiation of function template specialization 'onnxruntime::detail::MakeStringImpl<const char *, unsigned long, const char *, long, const char *, std::vector<long>>' requested here
MakeStringImpl(ss, args...);
^
/build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/common/make_string.h:93:18: note: in instantiation of function template specialization 'onnxruntime::detail::MakeStringImpl<const char *, unsigned long, const char *, long, const char *, std::vector<long>>' requested here
return detail::MakeStringImpl(detail::if_char_array_make_ptr_t<Args const&>(args)...);
^
/build/python-onnxruntime/src/onnxruntime/onnxruntime/core/providers/dnnl/subgraph/dnnl_squeeze.cc:46:7: note: in instantiation of function template specialization 'onnxruntime::MakeString<char [20], unsigned long, char [23], long, char [9], std::vector<long>>' requested here
ORT_ENFORCE(data_dims[i] == 1, "Dimension of input ", i, " must be 1 instead of ", data_dims[i],
^
/build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/common/common.h:184:64: note: expanded from macro 'ORT_ENFORCE'
::onnxruntime::MakeString(__VA_ARGS__)); \
^
/build/python-onnxruntime/src/onnxruntime/include/onnxruntime/core/framework/tensor_shape.h:147:15: note: 'operator<<' should be declared prior to the call site
std::ostream& operator<<(std::ostream& out, const TensorShape& shape);
^
1 error generated.
make[2]: *** [CMakeFiles/onnxruntime_providers_dnnl.dir/build.make:384: CMakeFiles/onnxruntime_providers_dnnl.dir/build/python-onnxruntime/src/onnxruntime/onnxruntime/core/providers/dnnl/subgraph/dnnl_squeeze.cc.o] Error 1
Two-phase lookups fail as:
1. visible in the template definition - fails as `std::ostream& operator<<(std::ostream& out, const TensorShape& shape)` (from include/onnxruntime/core/framework/tensor_shape.h) is defined after `template <typename... Args> std::string MakeString(const Args&... args)` (from include/onnxruntime/core/common/make_string.h) as per `clang++ -E`
2. argument-dependent lookup - fails as the argument data_dims has type `std::vector<long>` (via typedef in dnnl.hpp), while `std::ostream& operator<<(std::ostream& out, const TensorShape& shape)` is in namespace onnxruntime instead of std
There are several possible fixes:
* Make operator<< appear before MakeString by adjust the order of header files - I consider it fragile
* Also define operator<< in namespace std - may results in namespace pollution
* Use an argument of a class in onnxruntime namespace - this commit
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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
General Information: onnxruntime.ai
Usage documention and tutorials: onnxruntime.ai/docs
Companion sample repositories:
- ONNX Runtime Inferencing: microsoft/onnxruntime-inference-examples
- ONNX Runtime Training: microsoft/onnxruntime-training-examples
Build Pipeline Status
| System | CPU | GPU | EPs |
|---|---|---|---|
| Windows | |||
| Linux | |||
| Mac | |||
| Android | |||
| iOS | |||
| WebAssembly |
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.