85 строки
3.5 KiB
Markdown
85 строки
3.5 KiB
Markdown
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Data Pipelines
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==============
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*Data Pipelines* are used to convert from arbitrary data into a matrix/tensor that can be consumed by machine learning algorithms.
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Contributing
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============
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This project welcomes contributions and suggestions. Most contributions require you to agree to a
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Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us
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the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
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When you submit a pull request, a CLA bot will automatically determine whether you need to provide
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a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions
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provided by the bot. You will only need to do this once across all repos using our CLA.
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This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
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For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or
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contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.
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Developer Quick Start
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=====================
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Note that these commands should be invoked within the root of the repository.
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**Linux**
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1) Run `sudo ./bootstrap.sh ..`
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This will need to happen once per machine or after a repository has moved to a different directory. Note that `sudo` is not necessary when running within a Docker container.
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2) Run `source ./Activate.sh x64`
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This will need to happen each time a new terminal window is opened.
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**Windows**
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1) Run `bootstrap.cmd ..`
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This will need to happen once per machine or after a repository has moved to a different directory.
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2) Run `Activate.cmd x64`
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This will need to happen each time a new terminal window is opened.
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Useful Development Commands
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---------------------------
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The following commands are available within an activated terminal window.
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Name | Command | Description
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----------------|---------------------------|------------------------------------------------------------
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DevEnvScripts | `DevEnvScripts.sh|.cmd` | Lists all scripts available in the activated environment.
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Builder | `Builder.sh|.cmd` | Builds C++, Python, C#, etc. files; invoked by the CI machine.
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Tester | `Tester.sh|.cmd` | Tests C++, Python, C#, etc. files; invoked by the CI machine.
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Formatter | `Formatter.sh|.cmd` | Formats C++ and Python source files. (Coming Soon)
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Invoking CMake
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--------------
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Native code is built via [CMake](https://cmake.org/). The following commands can be used to build any folder that contains a `CMakeLists.txt` file.
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In each example, create a `build` directory that will contain the generated CMake content and eventual binaries.
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Assumed directory structure:
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| - <Workspace dir>
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| - CMakeLists.txt
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| - ...
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| - build
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| - <Initially empty>
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Within `<Workspace Dir>/build` run...
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- [Debug] `cmake -G Ninja ..`
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- [Debug with Code Coverage] `cmake -G Ninja -D CppCommon_CODE_COVERAGE=ON ..`
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- [Release] `cmake -G Ninja -D CMAKE_BUILD_TYPE=Release ..`
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Once CMake has generated the build files, within `<WorkSpace Dir>/build` run...
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- [Build] `cmake --build .` or `ninja -v` (if the build generator was Ninja)
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- [Test] `ctest --parallel`
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## Featurizers
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Information for setup/configuration of the Featurizers library can be found [here](src/FeaturizerPrep/Readme.md)
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