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Remove OSes/architectures that we don't build on and have no CI for. (#904)

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* support non-tensor types

* support non-tensor types.

* support non-tensor types.

* fix compilation issues

* fix compilation issues

* Build without mkldnn for release packages. We'll default to MLAS.

* Remove OSes/architectures that we don't build on and have no CI for.
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Pranav Sharma 2019-04-25 11:48:48 -07:00 committed by GitHub
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BUILD.md
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@ -2,7 +2,7 @@
## Supported architectures
| | x86_32 | x86_64 | ARM32 | ARM64 |
| | x86_32 | x86_64 | ARM32v7 | ARM64 |
|-----------|:------------:|:------------:|:------------:|:------------:|
|Windows | YES | YES | YES | YES |
|Linux | YES | YES | YES | YES |
@ -15,26 +15,19 @@
|Windows 10 | YES | YES |Must use VS 2017 or the latest VS2015|
|Windows 10 <br/> Subsystem for Linux | YES | NO | |
|Ubuntu 16.x | YES | YES | Also supported on ARM32v7 (experimental) |
|Ubuntu 17.x | YES | YES | |
|Ubuntu 18.x | YES | YES | |
|Fedora 23 | YES | YES | |
|Fedora 24 | YES | YES | |
|Fedora 25 | YES | YES | |
|Fedora 26 | YES | YES | |
|Fedora 27 | YES | YES | |
|Fedora 28 | YES | NO |Cannot build GPU kernels but can run them |
* Red Hat Enterprise Linux and CentOS are not supported.
* GCC 4.x and below are not supported. If you are using GCC 7.0+, you'll need to upgrade eigen to a newer version before compiling ONNX Runtime.
* Other version of Ubuntu might work but we don't support them officially.
* GCC 4.x and below are not supported.
OS/Compiler Matrix:
| OS/Compiler | Supports VC | Supports GCC | Supports Clang |
|-------------|:------------:|:----------------:|:---------------:|
|Windows 10 | YES | Not tested | planning |
|Linux | NO | YES(gcc>=5.0) | YES |
| OS/Compiler | Supports VC | Supports GCC |
|-------------|:------------:|:----------------:|
|Windows 10 | YES | Not tested |
|Linux | NO | YES(gcc>=5.0) |
ONNX Runtime python binding only supports Python 3.x. Please use python 3.5+.
ONNX Runtime python binding only supports Python 3.5, 3.6 and 3.7.
## Build
1. Checkout the source tree:
@ -56,7 +49,7 @@ The build script runs all unit tests by default (for native builds and skips tes
The complete list of build options can be found by running `./build.sh (or ./build.bat) --help`
## Build x86
## Build x86
1. For Windows, just add --x86 argument when launching build.bat
2. For Linux, it must be built out of a x86 os, --x86 argument also needs be specified to build.sh
@ -78,7 +71,7 @@ The complete list of build flavors can be seen by running `./build.sh --help` or
ONNX Runtime supports CUDA builds. You will need to download and install [CUDA](https://developer.nvidia.com/cuda-toolkit) and [CUDNN](https://developer.nvidia.com/cudnn).
ONNX Runtime is built and tested with CUDA 9.1 and CUDNN 7.1 using the Visual Studio 2017 14.11 toolset (i.e. Visual Studio 2017 v15.3).
CUDA versions from 9.1 up to 10.0, and CUDNN versions from 7.1 up to 7.4 should also work with Visual Studio 2017.
CUDA versions from 9.1 up to 10.0, and CUDNN versions from 7.1 up to 7.4 should also work with Visual Studio 2017.
- The path to the CUDA installation must be provided via the CUDA_PATH environment variable, or the `--cuda_home parameter`.
- The path to the CUDNN installation (include the `cuda` folder in the path) must be provided via the CUDNN_PATH environment variable, or `--cudnn_home parameter`. The CUDNN path should contain `bin`, `include` and `lib` directories.
@ -91,8 +84,8 @@ You can build with:
./build.bat --use_cuda --cudnn_home <cudnn home path> --cuda_home <cuda home path> (Windows)
```
Depending on compatibility between the CUDA, CUDNN, and Visual Studio 2017 versions you are using, you may need to explicitly install an earlier version of the MSVC toolset.
- CUDA 10.0 is known to work with toolsets from 14.11 up to 14.16 (Visual Studio 2017 15.9), and should continue to work with future Visual Studio versions
Depending on compatibility between the CUDA, CUDNN, and Visual Studio 2017 versions you are using, you may need to explicitly install an earlier version of the MSVC toolset.
- CUDA 10.0 is known to work with toolsets from 14.11 up to 14.16 (Visual Studio 2017 15.9), and should continue to work with future Visual Studio versions
- https://devblogs.microsoft.com/cppblog/cuda-10-is-now-available-with-support-for-the-latest-visual-studio-2017-versions/
- CUDA 9.2 is known to work with the 14.11 MSVC toolset (Visual Studio 15.3 and 15.4)
@ -109,8 +102,8 @@ To use the 14.11 toolset with a later version of Visual Studio 2017 you have two
2. Alternatively if you have CMake 3.12 or later you can specify the toolset version via the `--msvc_toolset` build script parameter.
- e.g. `.\build.bat --msvc_toolset 14.11`
_Side note: If you have multiple versions of CUDA installed on a Windows machine and are building with Visual Studio, CMake will use the build files for the highest version of CUDA it finds in the BuildCustomization folder.
e.g. C:\Program Files (x86)\Microsoft Visual Studio\2017\Enterprise\Common7\IDE\VC\VCTargets\BuildCustomizations\.
_Side note: If you have multiple versions of CUDA installed on a Windows machine and are building with Visual Studio, CMake will use the build files for the highest version of CUDA it finds in the BuildCustomization folder.
e.g. C:\Program Files (x86)\Microsoft Visual Studio\2017\Enterprise\Common7\IDE\VC\VCTargets\BuildCustomizations\.
If you want to build with an earlier version, you must temporarily remove the 'CUDA x.y.*' files for later versions from this directory._
### MKL-DNN/MKLML
@ -120,11 +113,11 @@ To build ONNX Runtime using MKL-DNN built with dependency on MKL small libraries
### TensorRT
ONNX Runtime supports the TensorRT execution provider (released as preview). You will need to download and install [CUDA](https://developer.nvidia.com/cuda-toolkit), [CUDNN](https://developer.nvidia.com/cudnn) and [TensorRT](https://developer.nvidia.com/nvidia-tensorrt-download).
The TensorRT execution provider for ONNX Runtime is built and tested with CUDA 9.0/CUDA 10.0, CUDNN 7.1 and TensorRT 5.0.2.6.
The TensorRT execution provider for ONNX Runtime is built and tested with CUDA 9.0/CUDA 10.0, CUDNN 7.1 and TensorRT 5.0.2.6.
- The path to the CUDA installation must be provided via the CUDA_PATH environment variable, or the `--cuda_home parameter`. The CUDA path should contain `bin`, `include` and `lib` directories.
- The path to the CUDA `bin` directory must be added to the PATH environment variable so that `nvcc` is found.
- The path to the CUDNN installation (path to folder that contains libcudnn.so) must be provided via the CUDNN_PATH environment variable, or `--cudnn_home parameter`.
- The path to the CUDNN installation (path to folder that contains libcudnn.so) must be provided via the CUDNN_PATH environment variable, or `--cudnn_home parameter`.
- The path to TensorRT installation must be provided via the `--tensorrt_home parameter`.
You can build from source on Linux by using the following `cmd` from the onnxruntime directory:
@ -316,10 +309,10 @@ ls -l /code/onnxruntime/build/Linux/MinSizeRel/dist/*.whl
### Cross compiling on Windows
#### Using Visual C++ compilers
1. Download and install Visual C++ compilers and libraries for ARM(64).
1. Download and install Visual C++ compilers and libraries for ARM(64).
If you have Visual Studio installed, please use the Visual Studio Installer (look under the section `Individual components` after choosing to `modify` Visual Studio) to download and install the corresponding ARM(64) compilers and libraries.
2. Use `build.bat` and specify `--arm` or `--arm64` as the build option to start building. Preferably use `Developer Command Prompt for VS` or make sure all the installed cross-compilers are findable from the command prompt being used to build using the PATH environmant variable.
2. Use `build.bat` and specify `--arm` or `--arm64` as the build option to start building. Preferably use `Developer Command Prompt for VS` or make sure all the installed cross-compilers are findable from the command prompt being used to build using the PATH environmant variable.
### Using other compilers
(TODO)