wangmeng28
8 years ago
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e65960ede8
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./doc/howto/dev/contribute_to_paddle_en.md
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# Contribute Code
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We sincerely appreciate your contribution. This document explains our workflow and work style.
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## Workflow
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PaddlePaddle uses this [Git branching model](http://nvie.com/posts/a-successful-git-branching-model/). The following steps guide usual contributions.
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1. Fork
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Our development community has been growing fastly; it doesn't make sense for everyone to write into the official repo. So, please file Pull Requests from your fork. To make a fork, just head over to the GitHub page and click the ["Fork" button](https://help.github.com/articles/fork-a-repo/).
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1. Clone
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To make a copy of your fork to your local computers, please run
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```bash
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git clone https://github.com/your-github-account/paddle
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cd paddle
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```
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1. Create the local feature branch
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For daily works like adding a new feature or fixing a bug, please open your feature branch before coding:
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```bash
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git checkout -b my-cool-stuff
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```
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1. Commit
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Before issuing your first `git commit` command, please install [`pre-commit`](http://pre-commit.com/) by running the following commands:
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```bash
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pip install pre-commit
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pre-commit install
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```
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Our pre-commit configuration requires clang-format 3.8 for auto-formating C/C++ code and yapf for Python.
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Once installed, `pre-commit` checks the style of code and documentation in every commit. We will see something like the following when you run `git commit`:
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```
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➜ git commit
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CRLF end-lines remover...............................(no files to check)Skipped
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yapf.................................................(no files to check)Skipped
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Check for added large files..............................................Passed
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Check for merge conflicts................................................Passed
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Check for broken symlinks................................................Passed
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Detect Private Key...................................(no files to check)Skipped
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Fix End of Files.....................................(no files to check)Skipped
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clang-formater.......................................(no files to check)Skipped
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[my-cool-stuff c703c041] add test file
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1 file changed, 0 insertions(+), 0 deletions(-)
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create mode 100644 233
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```
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1. Build and test
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Users can build PaddlePaddle natively on Linux and Mac OS X. But to unify the building environment and to make it easy for debugging, the recommended way is [using Docker](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/howto/dev/build_en.md).
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1. Keep pulling
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An experienced Git user pulls from the official repo often -- daily or even hourly, so they notice conflicts with others work early, and it's easier to resolve smaller conflicts.
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```bash
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git remote add upstream https://github.com/PaddlePaddle/Paddle
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git pull upstream develop
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```
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1. Push and file a pull request
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You can "push" your local work into your forked repo:
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```bash
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git push origin my-cool-stuff
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```
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The push allows you to create a pull request, requesting owners of this [official repo](https://github.com/PaddlePaddle/Paddle) to pull your change into the official one.
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To create a pull request, please follow [these steps](https://help.github.com/articles/creating-a-pull-request/).
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If your change is for fixing an issue, please write ["Fixes <issue-URL>"](https://help.github.com/articles/closing-issues-using-keywords/) in the description section of your pull request. Github would close the issue when the owners merge your pull request.
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Please remember to specify some reviewers for your pull request. If you don't know who are the right ones, please follow Github's recommendation.
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1. Delete local and remote branches
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To keep your local workspace and your fork clean, you might want to remove merged branches:
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```bash
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git push origin :my-cool-stuff
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git checkout develop
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git pull upstream develop
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git branch -d my-cool-stuff
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```
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### Code Review
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- Please feel free to ping your reviewers by sending them the URL of your pull request via IM or email. Please do this after your pull request passes the CI.
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- Please answer reviewers' every comment. If you are to follow the comment, please write "Done"; please give a reason otherwise.
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- If you don't want your reviewers to get overwhelmed by email notifications, you might reply their comments by [in a batch](https://help.github.com/articles/reviewing-proposed-changes-in-a-pull-request/).
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- Reduce the unnecessary commits. Some developers commit often. It is recommended to append a sequence of small changes into one commit by running `git commit --amend` instead of `git commit`.
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## Coding Standard
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### Code Style
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Our C/C++ code follows the [Google style guide](http://google.github.io/styleguide/cppguide.html).
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Our Python code follows the [PEP8 style guide](https://www.python.org/dev/peps/pep-0008/).
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Our build process helps to check the code style. In [`build.sh`](https://github.com/PaddlePaddle/Paddle/blob/b84e8226514b8bb4405c3c28e54aa5077193d179/paddle/scripts/docker/build.sh#L42), the entry point of our [builder Docker image](https://github.com/PaddlePaddle/Paddle/blob/b84e8226514b8bb4405c3c28e54aa5077193d179/Dockerfile#L88), the CMake argument `WITH_STYLE_CHECK` is set to `ON` by default. This flag is on
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Please install pre-commit, which automatically reformat the changes to C/C++ and Python code whenever we run `git commit`. To check the whole codebase, we can run the command `pre-commit run -a`, as in the [`check_style.sh` file](https://github.com/PaddlePaddle/Paddle/blob/b84e8226514b8bb4405c3c28e54aa5077193d179/paddle/scripts/travis/check_style.sh#L30), which is invoked by [our Travis CI configuration](https://github.com/PaddlePaddle/Paddle/blob/b84e8226514b8bb4405c3c28e54aa5077193d179/.travis.yml#L43).
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### Unit Tests
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Please remember to add related unit tests.
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- For C/C++ code, please follow [`google-test` Primer](https://github.com/google/googletest/blob/master/googletest/docs/Primer.md).
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- For Python code, please use [Python's standard `unittest` package](http://pythontesting.net/framework/unittest/unittest-introduction/).
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### Writing Logs
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We use [glog](https://github.com/google/glog) for logging in our C/C++ code.
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For general information, please use `LOG`. For debug information, please use [`VLOG`](http://htmlpreview.github.io/?https://github.com/google/glog/blob/master/doc/glog.html#verbose). The reason is at [here](https://groups.google.com/a/chromium.org/d/msg/chromium-dev/3NDNd1KzXeY/AZKMMx37fdQJ).
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`VLOG` requires a *verbose level* parameter. For example:
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```c++
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VLOG(3) << "Operator FC is taking " << num_inputs << "inputs."
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```
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When we run a PaddlePaddle application or test, we can specify a verbose threshold. For example:
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```bash
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GLOG_vmodule=buddy_allocator=2 \
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GLOG_v=10 \
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python \
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../python/paddle/v2/framework/tests/test_recurrent_op.py
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```
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This will enable VLOG messages generated by `buddy_allocator.{h,cc}` and in the verbose range of 0 to 3, so you will see above example VLOG message, which is in level 3. This suggests that we output overall messages in lower verbose levels, so they display with higher probability. When coding C++, please follow the verbose level convention as follows:
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- verbose level 1: [framework](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/framework)
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- verbose level 3: [operators](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/operators)
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- verbose level 5: [memory](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/memory), [platform](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/platform)
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- verbose level 7: [math](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/math)
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@ -0,0 +1,48 @@
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# Benchmark
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Machine:
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- Server
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- Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz, 2 Sockets, 20 Cores per socket
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- Laptop
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- DELL XPS15-9560-R1745: i7-7700HQ 8G 256GSSD
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- i5 MacBook Pro (Retina, 13-inch, Early 2015)
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- Desktop
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- i7-6700k
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System: CentOS release 6.3 (Final), Docker 1.12.1.
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PaddlePaddle: paddlepaddle/paddle:latest (TODO: will rerun after 0.11.0)
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- MKL-DNN tag v0.10
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- MKLML 2018.0.20170720
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- OpenBLAS v0.2.20
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On each machine, we will test and compare the performance of training on single node using MKL-DNN / MKLML / OpenBLAS respectively.
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## Benchmark Model
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### Server
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Test on batch size 64, 128, 256 on Intel(R) Xeon(R) Gold 6148M CPU @ 2.40GHz
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Input image size - 3 * 224 * 224, Time: images/second
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- VGG-19
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| BatchSize | 64 | 128 | 256 |
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|--------------|-------| -----| --------|
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| OpenBLAS | 7.82 | 8.62 | 10.34 |
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| MKLML | 11.02 | 12.86 | 15.33 |
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| MKL-DNN | 27.69 | 28.8 | 29.27 |
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chart on batch size 128
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TBD
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- ResNet
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- GoogLeNet
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### Laptop
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|
TBD
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### Desktop
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TBD
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@ -0,0 +1,49 @@
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include(ExternalProject)
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set(NCCL_SOURCE_DIR ${THIRD_PARTY_PATH}/nccl)
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include_directories(${NCCL_SOURCE_DIR}/src/extern_nccl/src)
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if(WITH_DSO)
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# If we use DSO, we do not build nccl, just download the dependencies
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set(NCCL_BUILD_COMMAND "")
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set(NCCL_INSTALL_COMMAND "")
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set(NCCL_INSTALL_DIR "")
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else()
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# otherwise, we build nccl and link it.
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set(NCCL_INSTALL_DIR ${THIRD_PARTY_PATH}/install/nccl)
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# Note: cuda 8.0 is needed to make nccl
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# When cuda is not installed on the system directory, need to set CUDA_HOME to your cuda root
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set(NCCL_BUILD_COMMAND "make -j 8")
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set(NCCL_INSTALL_COMMAND "make install PREFIX=${NCCL_INSTALL_DIR}")
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endif()
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ExternalProject_Add(
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extern_nccl
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${EXTERNAL_PROJECT_LOG_ARGS}
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GIT_REPOSITORY "https://github.com/NVIDIA/nccl.git"
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GIT_TAG "v1.3.4-1"
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PREFIX "${NCCL_SOURCE_DIR}"
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UPDATE_COMMAND ""
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CONFIGURE_COMMAND ""
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BUILD_COMMAND "${NCCL_BUILD_COMMAND}"
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INSTALL_COMMAND "${NCCL_INSTALL_COMMAND}"
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INSTALL_DIR "${NCCL_INSTALL_DIR}"
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TEST_COMMAND ""
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)
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if(WITH_DSO)
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if(${CMAKE_VERSION} VERSION_LESS "3.3.0")
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set(dummyfile ${CMAKE_CURRENT_BINARY_DIR}/lib_nccl_dummy.c)
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file(WRITE ${dummyfile} "const char * dummy_nccl = \"${dummyfile}\";")
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add_library(nccl STATIC ${dummyfile})
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else()
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add_library(nccl INTERFACE)
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endif()
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else()
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add_library(nccl STATIC IMPORTED GLOBAL)
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set_property(TARGET nccl PROPERTY IMPORTED_LOCATION
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${NCCL_INSTALL_DIR}/lib/libnccl_static.a)
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endif()
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add_dependencies(nccl extern_nccl)
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@ -0,0 +1,23 @@
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# Executor Design Doc
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## Motivation
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||||||
|
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||||||
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We use executor to do the runtime evaluation of a `ProgramDesc`.
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||||||
|
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||||||
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## Overview
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||||||
|
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||||||
|
An executor takes a `ProgramDesc`, a `block_id` and a `Scope`. The `ProgramDesc` is a list of blocks and each block contains the protobuf definition of all the parameters and operators. The `block_id` specifies the entrance block. And the `Scope` is the container of all the variable instance, which is persistent throughout different runs.
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||||||
|
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||||||
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### What does executor do?
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||||||
|
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||||||
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It evaluates all the operators in the `block_id`th block of a `ProgramDesc`.
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||||||
|
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||||||
|
### What does executor NOT do?
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||||||
|
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||||||
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It does not do runtime optimization, meaning intelligently parse the dependency of each op a choose which one to be run and in which order they should be run.
|
||||||
|
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||||||
|
It does not do graph partitioning, meaning dividing the `ProgramDesc` into several small pieces and executing them on different devices.
|
||||||
|
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||||||
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## Implementation
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||||||
|
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||||||
|
`Executor` evaluates a `ProgramDesc`. Essentially, it instantiates Variables and Operators, then run all the operators in sequence. [[code]](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/executor.cc)
|
||||||
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Reference in new issue