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Coding_Conventions_and_Standards.md

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ONNX Runtime coding conventions and standards

C++ Code Style

Google style from https://google.github.io/styleguide/cppguide.html with a few minor alterations:

Other

  • Qualify usages of auto with const, *, & and && where applicable to more clearly express the intent
  • When adding a new class, disable copy/assignment/move until you have a proven need for these capabilities. If a need arises, enable copy/assignment/move selectively, and when doing so validate that the implementation of the class supports what is being enabled.
  • Prefer passing gsl::span<const T> by value (or std::span when supported) as input arguments when passing const references to containers with contiguous storage (like std::vector). This allows to make the function container independent, represent arbitrary memory spans or pass sub-spans as an argument.
  • Use AsSpan({1, 2, 3}) to convert std::initializer_list<T> to a span. You can also use std::array.
  • Prefer passing std::string_view by value instead of const std::string&.
  • Prefer returning gsl::span<const T> or gsl::span<T> by value instead of a const reference or reference to a contiguous member container.
  • The use of the following container typedefs to reduce memory allocations is preferred:
    • Use TensorShapeVector typedef to build or modify shapes from core/framework/tensor_shape.h. It is based on a vector implementation that features small buffer optimization. Its small buffer size is the same to that of in TensorShape. Use InlinedShapeVector<T> for shape related operations, but of different type.
    • Use InlinedVector<T> typedef instead of std::vector. By default, it provides 64 bytes of inlined storage. You can customize inlined size with the second template non-type parameter N.
    • Use InlinedHashSet<T> and InlinedHashMap<T> typedefs from core/framework/inlined_containers.h. These are drop-in replacements for std::unordered_set/map that store their keys and values in one continuous buffer and reduce the number of allocations. They also do not allocate an end node. Note, that these Hash containers do not provide pointer stability.
    • Consider using std::string_view to use in maps and sets to reduce the number of allocations and avoid string duplication. Keep in mind that the strings referred to must be alive.
    • We have selected to use Abseil library for the above typedefs. Abseil container documentation is here.
  • Prefer using reserve() and not resize() on vectors. resize() default constructs all the elements for the size which can be expensive/noticeable even if the type is trivial. Default values are rarely used in practice and it becomes a waste. Construction like std::vector<int>(10, 0) is the same as resize() and is potentially wasteful.
  • Use reserve() on hash containers or pass the number of items in the constructor.
  • Don't use else after return. see: https://llvm.org/docs/CodingStandards.html#don-t-use-else-after-a-return
  • Don't overuse std::shared_ptr. Use std::shared_ptr only if it's not clear when and where the object will be de-allocated. See also: https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines#Rf-shared_ptr
  • Avoid using the long type, which could be either 32 bits or 64 bits.
  • If there is a legitimate need to allocate objects on the heap, prefer using std::make_unique(). References for the reasoning:
  • Use SafeInt when calculating the size of memory to allocate to protect against overflow errors
    • #include "core/common/safeint.h"
    • search for SafeInt<size_t> in the code for examples

Clang-format

Clang-format will handle automatically formatting code to these rules. There’s a Visual Studio plugin that can format on save at https://marketplace.visualstudio.com/items?itemName=LLVMExtensions.ClangFormat, or alternatively the latest versions of Visual Studio 2017 include clang-format support.

There is a .clang-format file in the root directory that has the max line length override and defaults to the google rules. This should be automatically discovered by the clang-format tools.

Code analysis

Visual Studio Code Analysis with C++ Core guidelines rules enabled is configured to run on build for the onnxruntime_common, onnxruntime_graph and onnxruntime_util libraries. Updating the onnxruntime_framework and onnxruntime_provider libraries to enable Code Analysis and build warning free is pending.

Code changes should build with no Code Analysis warnings, however this is somewhat difficult to achieve consistently as the Code Analysis implementation is in fairly constant flux. Different minor releases may have less false positives (a build with the latest version may be warning free, and a build with an earlier version may not), or detect additional problems (an earlier version builds warning free and a later version doesn't).

Unit Testing and Code Coverage

There should be unit tests that cover the core functionality of the product, expected edge cases, and expected errors. Code coverage from these tests should aim at maintaining over 80% coverage.

All changes should be covered by new or existing unit tests.

In order to check that all the code you expect to be covered by testing is covered, run code coverage in Visual Studio using 'Analyze Code Coverage' under the Test menu.

There is a configuration file in onnxruntime/VSCodeCoverage.runsettings that can be used to configure code coverage so that it reports numbers for just the onnxruntime code. Select that file in Visual Studio via the Test menu: Test -> Test Settings -> Select Test Settings File.

Using Show Code Coverage Coloring will allow you to visually inspect which lines were hit by the tests. See https://docs.microsoft.com/en-us/visualstudio/test/using-code-coverage-to-determine-how-much-code-is-being-tested?view=vs-2017.

Python Code Style

Follow the Black formatter's coding style when possible. A maximum line length of 120 characters is allowed for consistency with the C++ code.

Please adhere to the PEP8 Style Guide. We use Google's python style guide as the style guide which is an extension to PEP8.

Code can be validated with flake8 using the configuration file in the root directory called .flake8.

Use pyright, which is provided as a component of the pylance extension in VS Code for static type checking.

Auto-formatting is done with black and isort. The tools are configured in pyproject.toml. From anywhere in the repository, you can run

black .
isort .

to format Python files.

Use pydocstyle to lint documentation styles. pydocstyle is enabled in VS Code.

IDEs

VS Code

VS Code is automatically configured with workspace configurations.

For Python development is VS Code, read this tutorial for more information.

PyCharm

Follow black's documentation to set up the black formatter for PyCharm.

Testing

We use the Python built-in unittest framework for creating unit tests and pytest to run them. Use pytest to create tests only when unittest does not fit the need.

Style

Test the behavior, instead of the implementation. To make what a test is testing clear, the test methods should be named following the pattern test_<method or function name>_<expected behavior>_[when_<condition>].

e.g. test_method_x_raises_error_when_dims_is_not_a_sequence

Objective-C/C++ Code Style

Please follow the Google Objective-C/C++ Style Guide.

Clang-format can be used to format Objective-C/C++ code. The .clang-format file is in the repository root directory.