chengduoZH
7 years ago
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10bd9f6831
@ -1 +1,157 @@
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./doc/howto/dev/contribute_to_paddle_en.md
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# Contribute Code
|
||||
|
||||
We sincerely appreciate your contribution. This document explains our workflow and work style.
|
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|
||||
## Workflow
|
||||
|
||||
PaddlePaddle uses this [Git branching model](http://nvie.com/posts/a-successful-git-branching-model/). The following steps guide usual contributions.
|
||||
|
||||
1. Fork
|
||||
|
||||
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/).
|
||||
|
||||
1. Clone
|
||||
|
||||
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
|
||||
```
|
||||
|
||||
1. Create the local feature branch
|
||||
|
||||
For daily works like adding a new feature or fixing a bug, please open your feature branch before coding:
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|
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```bash
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git checkout -b my-cool-stuff
|
||||
```
|
||||
|
||||
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:
|
||||
|
||||
```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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|
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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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```
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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
|
||||
Check for merge conflicts................................................Passed
|
||||
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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```
|
||||
|
||||
1. Build and test
|
||||
|
||||
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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||||
|
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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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|
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1. Push and file a pull request
|
||||
|
||||
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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|
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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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|
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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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|
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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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|
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|
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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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|
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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.
|
||||
|
||||
- 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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|
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|
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## Coding Standard
|
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|
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### Code Style
|
||||
|
||||
Our C/C++ code follows the [Google style guide](http://google.github.io/styleguide/cppguide.html).
|
||||
|
||||
Our Python code follows the [PEP8 style guide](https://www.python.org/dev/peps/pep-0008/).
|
||||
|
||||
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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|
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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
|
||||
|
||||
Please remember to add related unit tests.
|
||||
|
||||
- For C/C++ code, please follow [`google-test` Primer](https://github.com/google/googletest/blob/master/googletest/docs/Primer.md).
|
||||
|
||||
- For Python code, please use [Python's standard `unittest` package](http://pythontesting.net/framework/unittest/unittest-introduction/).
|
||||
|
||||
|
||||
### Writing Logs
|
||||
|
||||
We use [glog](https://github.com/google/glog) for logging in our C/C++ code.
|
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|
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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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|
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`VLOG` requires a *verbose level* parameter. For example:
|
||||
|
||||
```c++
|
||||
VLOG(3) << "Operator FC is taking " << num_inputs << "inputs."
|
||||
```
|
||||
|
||||
When we run a PaddlePaddle application or test, we can specify a verbose threshold. For example:
|
||||
|
||||
```bash
|
||||
GLOG_vmodule=buddy_allocator=2 \
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||||
GLOG_v=10 \
|
||||
python \
|
||||
../python/paddle/v2/framework/tests/test_recurrent_op.py
|
||||
```
|
||||
|
||||
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:
|
||||
|
||||
- verbose level 1: [framework](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/framework)
|
||||
- verbose level 3: [operators](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/operators)
|
||||
- verbose level 5: [memory](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/memory), [platform](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/platform)
|
||||
- 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
|
||||
|
||||
Machine:
|
||||
|
||||
- Server
|
||||
- Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz, 2 Sockets, 20 Cores per socket
|
||||
- Laptop
|
||||
- DELL XPS15-9560-R1745: i7-7700HQ 8G 256GSSD
|
||||
- i5 MacBook Pro (Retina, 13-inch, Early 2015)
|
||||
- Desktop
|
||||
- i7-6700k
|
||||
|
||||
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)
|
||||
|
||||
- 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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|
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## Benchmark Model
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||||
|
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### Server
|
||||
Test on batch size 64, 128, 256 on Intel(R) Xeon(R) Gold 6148 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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||||
|
||||
|
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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
|
||||
TBD
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||||
|
After Width: | Height: | Size: 620 B |
|
After Width: | Height: | Size: 156 B |
@ -0,0 +1,72 @@
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||||
# Averaging Parameter in PaddlePaddle
|
||||
|
||||
## Why Averaging
|
||||
In a large scale machine learning setup where the size of the training data is huge, it could take us a large number of iterations over the training data before we can achieve the optimal values of parameters of our model. Looking at the problem setup, it is desirable if we can obtain the optimal values of parameters by going through the data in as few passes as we can.
|
||||
|
||||
Polyak and Juditsky (1992) showed that the test performance of simple average of parameters obtained by Stochastic Gradient Descent (SGD) is as good as that of parameter values that are obtained by training the model over and over again, over the training dataset.
|
||||
|
||||
Hence, to accelerate the speed of Stochastic Gradient Descent, Averaged Stochastic Gradient Descent (ASGD) was proposed in Polyak and Juditsky (1992). For ASGD, the running average of parameters obtained by SGD, is used as the estimator for <img src="./images/theta_star.gif"/><br/> . The averaging is done as follows:
|
||||
|
||||
<img src="./images/asgd.gif" align="center"/><br/>
|
||||
|
||||
We propose averaging for any optimizer similar to how ASGD performs it, as mentioned above.
|
||||
|
||||
### How to perform Parameter Averaging in PaddlePaddle
|
||||
|
||||
Parameter Averaging in PaddlePaddle works in the following way during training :
|
||||
1. It will take in an instance of a normal optimizer as an input, e.g. RMSPropOptimizer
|
||||
2. The optimizer itself is responsible for updating the parameters.
|
||||
3. The ParameterAverageOptimizer maintains a separate copy of the parameters for itself:
|
||||
1. In concept, the values of this copy are the average of the values of the parameters in the most recent N batches.
|
||||
2. However, saving all the N instances of the parameters in memory is not feasible.
|
||||
3. Therefore, an approximation algorithm is used.
|
||||
|
||||
Hence, overall we have have two copies of the parameters: one for the optimizer itself, and one for the ParameterAverageOptimizer. The former should be used in back propagation, while the latter should be used during testing and should be saved.
|
||||
|
||||
During the testing/ saving the model phase, we perform the following steps:
|
||||
1. Perform the delayed operations.
|
||||
2. Save current values of the parameters to a temporary variable.
|
||||
3. Replace the values of the parameters with the averaged values.
|
||||
4. Perform testing and/or save the parameters.
|
||||
5. Restore the values of the parameters once done.
|
||||
|
||||
### How to implement Averaging of Parameter in PaddlePaddle
|
||||
|
||||
We can add the ParameterAverageOptimizer op to the graph through Python API. Using this approach, we manually add this op to the graph and direct the output of the optimizer op to this op during training.
|
||||
|
||||
**Advantages**:
|
||||
- Allows for greater flexibility to the users of PaddlePaddle. Using this approach, the users can plug different optimizers into ParameterAverageOptimizer by passing in the optimizer to the op.
|
||||
- Makes it easy for the users to customize and extend the framework.
|
||||
|
||||
**Disadvantages**:
|
||||
- Implementation requires re-writing the averaging methodology in Python.
|
||||
|
||||
### Low-Level implementation
|
||||
|
||||
In the new design, we propose to create a new operation for averaging parameter updates (ParameterAverageOptimizer). For now, we can add an op that takes in the following as input:
|
||||
- the optimizer
|
||||
- the window_size to keep the updates
|
||||
|
||||
The ParameterAverageOptimizer op can be like any other operator with its own CPU/GPU implementation either using Eigen or separate CPU and GPU kernels. As the initial implementation, we can implement the kernel using Eigen following the abstraction pattern implemented for [Operators](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/rmsprop_op.h). We also want to support the case when the Trainer/Optimizer runs on the GPU while ParameterAverageOptimizer runs on a CPU.
|
||||
|
||||
The idea of building an op for averaging is in sync with the refactored PaddlePaddle philosophy of using operators to represent any computation unit. The way the op will be added to the computation graph will be decided by the [layer functions](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/python_api.md#layer-function) in Python API.
|
||||
|
||||
### Python API implementation for ParameterAverageOptimizer
|
||||
|
||||
Based on Polyak and Juditsky (1992), we can generalize the averaging of updates to any optimizer. The input to the op would be the following:
|
||||
- Any optimizer (RMSProp , AdaGrad etc.)
|
||||
- A window size. The op keeps accumulating updated parameter values over a window of N batches and takes an average. Move the averaged value to a buffer when window is full to avoid loss of precision.
|
||||
|
||||
Using the ParameterAverageOptimizer op, any user can add the operation to their computation graphs. However, this will require a lot of lines of code and we should design Python APIs that support averaging. As per the PaddlePaddle [Python API design](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/python_api.md), the layer functions are responsible for creating operators, operator parameters and variables. Since ParameterAverageOptimizer will be an operator, it makes sense to create it in the layer functions.
|
||||
We will have a wrapper written in Python that will support the functionality and implement the actual core computation in C++ core as we have done for other [Optimizers](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/operators/rmsprop_op.cc)
|
||||
|
||||
#### Creation of the ParameterAverageOptimizer operator
|
||||
There are two ways for creating the ParameterAverageOptimizer op:
|
||||
1. We create the op immediately while building the computation graph.
|
||||
2. We add the op in a lazy manner, just before the backward pass, similar to the way the optimization ops are added.
|
||||
|
||||
The proposal is to add the op immediately while building the computation graph.
|
||||
|
||||
#### High-level API
|
||||
|
||||
In PaddlePaddle Python API, users will primarily rely on [layer functions](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/python_api.md#layer-function) to create neural network layers. Hence, we also need to provide parameter average functionality in layer functions.
|
||||
@ -0,0 +1,62 @@
|
||||
# Build PaddlePaddle for Raspberry Pi
|
||||
|
||||
You may use any of the following two approaches to build the inference library of PaddlePaddle for Raspberry Pi:
|
||||
|
||||
1. Build using SSH: Log in to a Raspberry Pi using SSH and build the library. The required development tools and third-party dependencies are listed in here: [`/Dockerfile`](https://github.com/PaddlePaddle/Paddle/blob/develop/Dockerfile).
|
||||
|
||||
1. Cross-compile: We talk about how to cross-compile PaddlePaddle for Raspberry Pi on a Linux/x64 machine, in more detail in this article.
|
||||
|
||||
## The Cross-Compiling Toolchain
|
||||
|
||||
Step 1. Clone the Github repo by running the following command.
|
||||
|
||||
```bash
|
||||
git clone https://github.com/raspberrypi/tools.git
|
||||
```
|
||||
|
||||
Step 2. Use the pre-built cross-compiler found in `./tools/tree/master/arm-bcm2708/gcc-linaro-arm-linux-gnueabihf-raspbian-x64`. To run it on a Linux computer, glibc version >= 2.14 is needed.
|
||||
|
||||
## CMake Arguments
|
||||
|
||||
CMake supports [cross-compiling](https://cmake.org/cmake/help/v3.0/manual/cmake-toolchains.7.html#cross-compiling). All CMake configuration arguments required for the cross-compilation for Raspberry Pi can be found in [`cmake/cross_compiling/raspberry_pi.cmake`](https://github.com/PaddlePaddle/Paddle/blob/develop/cmake/cross_compiling/raspberry_pi.cmake).
|
||||
|
||||
Some important arguments that need to be set:
|
||||
|
||||
- `CMAKE_SYSTEM_NAME`: The target platform. Must be `RPi`.
|
||||
|
||||
- `RPI_TOOLCHAIN`: The absolute path of the cross-compiling toolchain.
|
||||
|
||||
- `RPI_ARM_NEON`: Use ARM NEON Intrinsics. This is a required argument and set default to `ON`.
|
||||
|
||||
- `HOST_C/CXX_COMPILER`: The C/C++ compiler for the host. It is used to build building tools running on the host, for example, protoc.
|
||||
|
||||
A commonly-used CMake configuration is as follows:
|
||||
|
||||
```
|
||||
cmake -DCMAKE_SYSTEM_NAME=RPi \
|
||||
-DRPI_TOOLCHAIN=your/path/to/arm-bcm2708/gcc-linaro-arm-linux-gnueabihf-raspbian-x64 \
|
||||
-DRPI_ARM_NEON=ON \
|
||||
-DCMAKE_INSTALL_PREFIX=your/path/to/install \
|
||||
-DWITH_GPU=OFF \
|
||||
-DWITH_C_API=ON \
|
||||
-DWITH_PYTHON=OFF \
|
||||
-DWITH_SWIG_PY=OFF \
|
||||
..
|
||||
```
|
||||
|
||||
To build the inference library, please set the argument WITH\_C\_API to ON: `WITH_C_API=ON`.
|
||||
|
||||
You can add more arguments. For example, to minimize the size of the generated inference library, you may use `CMAKE_BUILD_TYPE=MinSizeRel`. For performance optimization, you may use `CMAKE_BUILD_TYPE=Release`.
|
||||
|
||||
## Build and Install
|
||||
|
||||
The following commands build the inference library of PaddlePaddle for Raspberry Pi and third-party dependencies.
|
||||
|
||||
```bash
|
||||
make
|
||||
make install
|
||||
```
|
||||
|
||||
The intermediate files will be stored in `build`. Third-party libraries will be located in `build/third_party`. If you have already built it for other platforms like Android or iOS, you may want to clear these directories by running the command: `rm -rf build`.
|
||||
|
||||
The infernece library will be in `your/path/to/install/lib`, with related header files in `your/path/to/install/include`.
|
||||
@ -1,219 +0,0 @@
|
||||
# Contribute Code
|
||||
|
||||
We sincerely appreciate your contributions. You can use fork and pull request
|
||||
workflow to merge your code.
|
||||
|
||||
## Code Requirements
|
||||
- Your code comments must be fully documented by
|
||||
[Doxygen](http://www.stack.nl/~dimitri/doxygen/) style.
|
||||
- Make sure the compiler option `WITH_STYLE_CHECK` is on and the compiler
|
||||
passes the code style check.
|
||||
- All code must have unit test.
|
||||
- Pass all unit tests.
|
||||
|
||||
The following tutorial guides you into submitting your contibution.
|
||||
|
||||
## [Creating a Fork](https://help.github.com/articles/fork-a-repo/)
|
||||
|
||||
Just head over to the GitHub page and click the "Fork" button.
|
||||
It's just that simple.
|
||||
|
||||
## Clone
|
||||
|
||||
Clone remote repository.
|
||||
|
||||
```bash
|
||||
➜ git clone https://github.com/USERNAME/Paddle
|
||||
➜ cd Paddle
|
||||
```
|
||||
|
||||
## Create a local branch
|
||||
|
||||
Paddle is currently using [Git-flow branching model](http://nvie.com/posts/a-successful-git-branching-model/).
|
||||
|
||||
All feature and bug fix development work should be done on a new branch, generally create new branch from `develop` branch .
|
||||
|
||||
```bash
|
||||
➜ git checkout -b my-cool-stuff
|
||||
```
|
||||
|
||||
Before the checkout, you need to keep the current branch directory clean, otherwise the untracked file will be brought to the new branch, which can be inspected by `git status`.
|
||||
|
||||
## Using `pre-commit` hook
|
||||
|
||||
Paddle developers use [pre-commit](http://pre-commit.com/) tool to manage git
|
||||
pre-commit hooks. It can help us format source codes (cpp, python), check some
|
||||
basic thing before commit (only one EOL for each file, do not add a huge file
|
||||
in git). `pre-commit` tests is a part of unit tests in Travis-CI now, every
|
||||
PR doesn't fit hook can not be merged into Paddle.
|
||||
|
||||
To use [pre-commit](http://pre-commit.com/), you should install it by
|
||||
`pip install pre-commit`, and currently, Paddle uses `clang-format` to format
|
||||
c/cpp sources. Please make sure clang-format 3.8+ installed.
|
||||
|
||||
Install and run it as follow:
|
||||
|
||||
```bash
|
||||
➜ pip install pre-commit
|
||||
➜ pre-commit install
|
||||
```
|
||||
|
||||
When you commit your code, the pre-commit hook will check the local code if there is
|
||||
anything not suitable to commit, and so on.
|
||||
|
||||
## Start to develop
|
||||
|
||||
In this tutorial, I delete a line in README.md and created a new file.
|
||||
|
||||
We can use `git status` to inspect the changes of current directory, `git diff` to see difference.
|
||||
|
||||
```bash
|
||||
➜ git status
|
||||
On branch test
|
||||
Changes not staged for commit:
|
||||
(use "git add <file>..." to update what will be committed)
|
||||
(use "git checkout -- <file>..." to discard changes in working directory)
|
||||
|
||||
modified: README.md
|
||||
|
||||
Untracked files:
|
||||
(use "git add <file>..." to include in what will be committed)
|
||||
|
||||
test
|
||||
|
||||
no changes added to commit (use "git add" and/or "git commit -a")
|
||||
```
|
||||
## Build and Test
|
||||
|
||||
We package PaddlePaddle's compile environment into a Docker image, called the develop image named `paddle:dev`, it contains all compiling tools that PaddlePaddle needs.
|
||||
|
||||
If you want to build the develop image, just run:
|
||||
|
||||
```bash
|
||||
➜ docker build -t paddle:dev .
|
||||
```
|
||||
|
||||
Then we can use the develop image to build PaddlePaddle source. For example:
|
||||
|
||||
```bash
|
||||
➜ docker run -v $(pwd):/paddle -e "WITH_GPU=OFF" -e "WITH_AVX=ON" -e "WITH_TEST=ON" paddle:dev
|
||||
```
|
||||
|
||||
The above command will compile PaddlePaddle and create a Dockerfile for building production image. All the generated files are in the build directory. "WITH_GPU" controls if the generated production image supports GPU. "WITH_AVX" controls if the generated production image supports AVX. "WITH_TEST" controls if the unit test will be generated.
|
||||
|
||||
Then we can generate the production image by copying the compiled PaddlePaddle program into the image by
|
||||
|
||||
```bash
|
||||
➜ docker build -t paddle:prod -f build/Dockerfile .
|
||||
```
|
||||
|
||||
Run unit test finally:
|
||||
|
||||
```bash
|
||||
➜ docker run -it -v $(pwd):/paddle paddle:dev bash -c "cd /paddle/build && ctest"
|
||||
```
|
||||
|
||||
For more details, you can read [this doc](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/getstarted/build_and_install/docker_install_en.rst).
|
||||
|
||||
## Commit
|
||||
|
||||
Next we cancel the changes to the README.md file and then commit our changes by following command lines:
|
||||
|
||||
```bash
|
||||
➜ git checkout -- README.md
|
||||
➜ git status
|
||||
On branch test
|
||||
Untracked files:
|
||||
(use "git add <file>..." to include in what will be committed)
|
||||
|
||||
test
|
||||
|
||||
nothing added to commit but untracked files present (use "git add" to track)
|
||||
➜ git add test
|
||||
```
|
||||
|
||||
We should write a description of each commit by `git commit` to allow others to know
|
||||
the changes in these files.
|
||||
|
||||
```bash
|
||||
➜ git commit
|
||||
CRLF end-lines remover...............................(no files to check)Skipped
|
||||
yapf.................................................(no files to check)Skipped
|
||||
Check for added large files..............................................Passed
|
||||
Check for merge conflicts................................................Passed
|
||||
Check for broken symlinks................................................Passed
|
||||
Detect Private Key...................................(no files to check)Skipped
|
||||
Fix End of Files.....................................(no files to check)Skipped
|
||||
clang-formater.......................................(no files to check)Skipped
|
||||
[my-cool-stuff c703c041] add test file
|
||||
1 file changed, 0 insertions(+), 0 deletions(-)
|
||||
create mode 100644 233
|
||||
```
|
||||
|
||||
## Keeping Fork Up to Date
|
||||
|
||||
Before pull your request, you should sync your code from the latest PaddlePaddle.
|
||||
To do this, you'll need to add a remote at first:
|
||||
|
||||
```bash
|
||||
➜ git remote add upstream https://github.com/PaddlePaddle/Paddle
|
||||
➜ git remote
|
||||
origin
|
||||
upstream
|
||||
```
|
||||
|
||||
Update your fork with the latest upstream changes:
|
||||
|
||||
```bash
|
||||
➜ git fetch upstream
|
||||
➜ git pull upstream develop
|
||||
```
|
||||
|
||||
Now, your local master branch is up-to-date with everything modified upstream.
|
||||
|
||||
## Push to GitHub
|
||||
|
||||
```bash
|
||||
# push to your repository in Github
|
||||
➜ git push origin my-cool-stuff
|
||||
```
|
||||
|
||||
## Create an issue and a Pull Request
|
||||
|
||||
Create an Issue to describe the problem and record its number.
|
||||
|
||||
Go to the page for your fork on GitHub, select your development branch,
|
||||
and click the `New pull request`.
|
||||
|
||||
<img width="295" alt="screen shot 2017-04-26 at 9 09 28 pm" src="https://cloud.githubusercontent.com/assets/11692045/25436054/a6d98c66-2ac4-11e7-9cb1-18dd13150230.png">
|
||||
|
||||
Then select the target branch:
|
||||
|
||||
<img width="750" alt="screen shot 2017-04-26 at 9 11 52 pm" src="https://cloud.githubusercontent.com/assets/11692045/25436139/f83b1e6c-2ac4-11e7-8c0e-add499023c46.png">
|
||||
|
||||
We can add `resolve #Issue number` in PR description to close the issue automatically after the PR is merge. More details in <https://help.github.com/articles/closing-issues-via-commit-messages/>.
|
||||
|
||||
Then wait for review, if there need to modify, refer to the above steps to update the corresponding origin branch.
|
||||
|
||||
## Delete origin branch
|
||||
|
||||
After the PR is merge into the main repository, we can delete the remote branch on the PR page.
|
||||
|
||||
<img width="775" alt="screen shot 2017-04-26 at 9 18 24 pm" src="https://cloud.githubusercontent.com/assets/11692045/25436457/e4cdd472-2ac5-11e7-9272-badc76c4a23e.png">
|
||||
|
||||
Or just run:
|
||||
|
||||
```bash
|
||||
➜ git push origin :my-cool-stuff
|
||||
```
|
||||
|
||||
## Delete local branch
|
||||
|
||||
Finally, we delete local branch:
|
||||
|
||||
```bash
|
||||
➜ git checkout develop
|
||||
|
||||
# delete my-cool-stuff branch
|
||||
➜ git branch -D my-cool-stuff
|
||||
```
|
||||
@ -0,0 +1 @@
|
||||
../../../CONTRIBUTING.md
|
||||
@ -1,2 +1,3 @@
|
||||
vendor/
|
||||
.glide/
|
||||
proto/*.go
|
||||
|
||||
@ -0,0 +1,4 @@
|
||||
# Ignore everything in this directory
|
||||
*
|
||||
# Except this file
|
||||
!.gitignore
|
||||
Some files were not shown because too many files have changed in this diff Show More
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Reference in new issue