commit | 1f2a21820dfa2c97de8cc9e09cd03cf1c1684e31 | [log] [tgz] |
---|---|---|
author | Jorge Gorbe Moya <jgorbe@google.com> | Wed Sep 14 17:20:33 2022 -0700 |
committer | Jorge Gorbe Moya <jgorbe@google.com> | Tue Sep 27 14:28:41 2022 -0700 |
tree | bbd81bca17463a1e5ede201714b4feac35de729c | |
parent | c78e947d2636eae54ac0d56159e0e4d8018f6cd4 [diff] |
[NFCI] Refactor FormatterContainerPair into TieredFormatterContainer. `FormatterContainerPair` is (as its name indicates) a very thin wrapper over two formatter containers, one for exact matches and another one for regex matches. The logic to decide which subcontainer to access is replicated everywhere `FormatterContainerPair`s are used. So, for example, when we look for a formatter there's some adhoc code that does a lookup in the exact match formatter container, and if it fails it does a lookup in the regex match formatter container. The same logic is then copied and pasted for summaries, filters, and synthetic child providers. This change introduces a new `TieredFormatterContainer` that has two main characteristics: - It generalizes `FormatterContainerPair` from 2 to any number of subcontainers, that are looked up in priority order. - It centralizes all the logic to choose which subcontainer to use for lookups, add/delete, and indexing. This allows us to have a single copy of the same logic, templatized for each kind of formatter. It also simplifies the upcoming addition of a new tier of callback-based matches. See https://discourse.llvm.org/t/rfc-python-callback-for-data-formatters-type-matching/64204 for more details about this. The rest of the change is mostly replacing copy-pasted code with calls to methods of the relevant `TieredFormatterContainer`, and adding some methods to the `TypeCategoryImpl` class so we can remove some of this copy-pasted code from `SBTypeCategory`. Differential Revision: https://reviews.llvm.org/D133910
This directory and its sub-directories contain the source code for LLVM, a toolkit for the construction of highly optimized compilers, optimizers, and run-time environments.
The README briefly describes how to get started with building LLVM. For more information on how to contribute to the LLVM project, please take a look at the Contributing to LLVM guide.
Taken from here.
Welcome to the LLVM project!
The LLVM project has multiple components. The core of the project is itself called “LLVM”. This contains all of the tools, libraries, and header files needed to process intermediate representations and convert them into object files. Tools include an assembler, disassembler, bitcode analyzer, and bitcode optimizer. It also contains basic regression tests.
C-like languages use the Clang frontend. This component compiles C, C++, Objective-C, and Objective-C++ code into LLVM bitcode -- and from there into object files, using LLVM.
Other components include: the libc++ C++ standard library, the LLD linker, and more.
The LLVM Getting Started documentation may be out of date. The Clang Getting Started page might have more accurate information.
This is an example work-flow and configuration to get and build the LLVM source:
Checkout LLVM (including related sub-projects like Clang):
git clone https://github.com/llvm/llvm-project.git
Or, on windows, git clone --config core.autocrlf=false https://github.com/llvm/llvm-project.git
Configure and build LLVM and Clang:
cd llvm-project
cmake -S llvm -B build -G <generator> [options]
Some common build system generators are:
Ninja
--- for generating Ninja build files. Most llvm developers use Ninja.Unix Makefiles
--- for generating make-compatible parallel makefiles.Visual Studio
--- for generating Visual Studio projects and solutions.Xcode
--- for generating Xcode projects.Some common options:
-DLLVM_ENABLE_PROJECTS='...'
and -DLLVM_ENABLE_RUNTIMES='...'
--- semicolon-separated list of the LLVM sub-projects and runtimes you'd like to additionally build. LLVM_ENABLE_PROJECTS
can include any of: clang, clang-tools-extra, cross-project-tests, flang, libc, libclc, lld, lldb, mlir, openmp, polly, or pstl. LLVM_ENABLE_RUNTIMES
can include any of libcxx, libcxxabi, libunwind, compiler-rt, libc or openmp. Some runtime projects can be specified either in LLVM_ENABLE_PROJECTS
or in LLVM_ENABLE_RUNTIMES
.
For example, to build LLVM, Clang, libcxx, and libcxxabi, use -DLLVM_ENABLE_PROJECTS="clang" -DLLVM_ENABLE_RUNTIMES="libcxx;libcxxabi"
.
-DCMAKE_INSTALL_PREFIX=directory
--- Specify for directory the full path name of where you want the LLVM tools and libraries to be installed (default /usr/local
). Be careful if you install runtime libraries: if your system uses those provided by LLVM (like libc++ or libc++abi), you must not overwrite your system's copy of those libraries, since that could render your system unusable. In general, using something like /usr
is not advised, but /usr/local
is fine.
-DCMAKE_BUILD_TYPE=type
--- Valid options for type are Debug, Release, RelWithDebInfo, and MinSizeRel. Default is Debug.
-DLLVM_ENABLE_ASSERTIONS=On
--- Compile with assertion checks enabled (default is Yes for Debug builds, No for all other build types).
cmake --build build [-- [options] <target>]
or your build system specified above directly.
The default target (i.e. ninja
or make
) will build all of LLVM.
The check-all
target (i.e. ninja check-all
) will run the regression tests to ensure everything is in working order.
CMake will generate targets for each tool and library, and most LLVM sub-projects generate their own check-<project>
target.
Running a serial build will be slow. To improve speed, try running a parallel build. That's done by default in Ninja; for make
, use the option -j NNN
, where NNN
is the number of parallel jobs to run. In most cases, you get the best performance if you specify the number of CPU threads you have. On some Unix systems, you can specify this with -j$(nproc)
.
For more information see CMake.
Consult the Getting Started with LLVM page for detailed information on configuring and compiling LLVM. You can visit Directory Layout to learn about the layout of the source code tree.
Join LLVM Discourse forums, discord chat or #llvm IRC channel on OFTC.
The LLVM project has adopted a code of conduct for participants to all modes of communication within the project.