Yibing Liu
7 years ago
commit
f5681f1551
@ -1 +1,157 @@
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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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|
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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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|
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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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|
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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 +1,213 @@
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#!/usr/bin/env python
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from paddle.trainer_config_helpers import *
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height = 224
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width = 224
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num_class = 1000
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batch_size = get_config_arg('batch_size', int, 64)
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layer_num = get_config_arg("layer_num", int, 50)
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is_test = get_config_arg("is_test", bool, False)
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args = {'height': height, 'width': width, 'color': True, 'num_class': num_class}
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define_py_data_sources2(
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"train.list", None, module="provider", obj="process", args=args)
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settings(
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batch_size=batch_size,
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learning_rate=0.01 / batch_size,
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learning_method=MomentumOptimizer(0.9),
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regularization=L2Regularization(0.0005 * batch_size))
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#######################Network Configuration #############
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def conv_bn_layer(name,
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input,
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filter_size,
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num_filters,
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stride,
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padding,
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channels=None,
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active_type=ReluActivation()):
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"""
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A wrapper for conv layer with batch normalization layers.
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Note:
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conv layer has no activation.
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"""
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tmp = img_conv_layer(
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name=name + "_conv",
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input=input,
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filter_size=filter_size,
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num_channels=channels,
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num_filters=num_filters,
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stride=stride,
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padding=padding,
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act=LinearActivation(),
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bias_attr=False)
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return batch_norm_layer(
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name=name + "_bn", input=tmp, act=active_type, use_global_stats=is_test)
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def bottleneck_block(name, input, num_filters1, num_filters2):
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"""
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A wrapper for bottlenect building block in ResNet.
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Last conv_bn_layer has no activation.
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Addto layer has activation of relu.
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"""
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last_name = conv_bn_layer(
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name=name + '_branch2a',
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input=input,
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filter_size=1,
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num_filters=num_filters1,
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stride=1,
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padding=0)
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last_name = conv_bn_layer(
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name=name + '_branch2b',
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input=last_name,
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filter_size=3,
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num_filters=num_filters1,
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stride=1,
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padding=1)
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last_name = conv_bn_layer(
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name=name + '_branch2c',
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input=last_name,
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filter_size=1,
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num_filters=num_filters2,
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stride=1,
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padding=0,
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active_type=LinearActivation())
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return addto_layer(
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name=name + "_addto", input=[input, last_name], act=ReluActivation())
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def mid_projection(name, input, num_filters1, num_filters2, stride=2):
|
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"""
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A wrapper for middile projection in ResNet.
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projection shortcuts are used for increasing dimensions,
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and other shortcuts are identity
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branch1: projection shortcuts are used for increasing
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dimensions, has no activation.
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branch2x: bottleneck building block, shortcuts are identity.
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"""
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# stride = 2
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branch1 = conv_bn_layer(
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name=name + '_branch1',
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input=input,
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filter_size=1,
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num_filters=num_filters2,
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stride=stride,
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padding=0,
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active_type=LinearActivation())
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last_name = conv_bn_layer(
|
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name=name + '_branch2a',
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input=input,
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filter_size=1,
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num_filters=num_filters1,
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stride=stride,
|
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padding=0)
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last_name = conv_bn_layer(
|
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name=name + '_branch2b',
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input=last_name,
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filter_size=3,
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num_filters=num_filters1,
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stride=1,
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padding=1)
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last_name = conv_bn_layer(
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name=name + '_branch2c',
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input=last_name,
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filter_size=1,
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num_filters=num_filters2,
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stride=1,
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padding=0,
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active_type=LinearActivation())
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return addto_layer(
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name=name + "_addto", input=[branch1, last_name], act=ReluActivation())
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img = data_layer(name='image', size=height * width * 3)
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def deep_res_net(res2_num=3, res3_num=4, res4_num=6, res5_num=3):
|
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"""
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A wrapper for 50,101,152 layers of ResNet.
|
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res2_num: number of blocks stacked in conv2_x
|
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res3_num: number of blocks stacked in conv3_x
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res4_num: number of blocks stacked in conv4_x
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res5_num: number of blocks stacked in conv5_x
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"""
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# For ImageNet
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# conv1: 112x112
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tmp = conv_bn_layer(
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"conv1",
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input=img,
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filter_size=7,
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channels=3,
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num_filters=64,
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stride=2,
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padding=3)
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tmp = img_pool_layer(name="pool1", input=tmp, pool_size=3, stride=2)
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# conv2_x: 56x56
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tmp = mid_projection(
|
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name="res2_1", input=tmp, num_filters1=64, num_filters2=256, stride=1)
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for i in xrange(2, res2_num + 1, 1):
|
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tmp = bottleneck_block(
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name="res2_" + str(i), input=tmp, num_filters1=64, num_filters2=256)
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# conv3_x: 28x28
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tmp = mid_projection(
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name="res3_1", input=tmp, num_filters1=128, num_filters2=512)
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for i in xrange(2, res3_num + 1, 1):
|
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tmp = bottleneck_block(
|
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name="res3_" + str(i),
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input=tmp,
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num_filters1=128,
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num_filters2=512)
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# conv4_x: 14x14
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tmp = mid_projection(
|
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name="res4_1", input=tmp, num_filters1=256, num_filters2=1024)
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for i in xrange(2, res4_num + 1, 1):
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tmp = bottleneck_block(
|
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name="res4_" + str(i),
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input=tmp,
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num_filters1=256,
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num_filters2=1024)
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# conv5_x: 7x7
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tmp = mid_projection(
|
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name="res5_1", input=tmp, num_filters1=512, num_filters2=2048)
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for i in xrange(2, res5_num + 1, 1):
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tmp = bottleneck_block(
|
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name="res5_" + str(i),
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input=tmp,
|
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num_filters1=512,
|
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num_filters2=2048)
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tmp = img_pool_layer(
|
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name='avgpool',
|
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input=tmp,
|
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pool_size=7,
|
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stride=1,
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pool_type=AvgPooling())
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return fc_layer(input=tmp, size=num_class, act=SoftmaxActivation())
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|
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|
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if layer_num == 50:
|
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resnet = deep_res_net(3, 4, 6, 3)
|
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elif layer_num == 101:
|
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resnet = deep_res_net(3, 4, 23, 3)
|
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elif layer_num == 152:
|
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resnet = deep_res_net(3, 8, 36, 3)
|
||||
else:
|
||||
print("Wrong layer number.")
|
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|
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lbl = data_layer(name="label", size=num_class)
|
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loss = cross_entropy(name='loss', input=resnet, label=lbl)
|
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inputs(img, lbl)
|
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outputs(loss)
|
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@ -0,0 +1,188 @@
|
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if(NOT WITH_GPU)
|
||||
return()
|
||||
endif()
|
||||
|
||||
set(paddle_known_gpu_archs "30 35 50 52 60 61 70")
|
||||
set(paddle_known_gpu_archs7 "30 35 50 52")
|
||||
set(paddle_known_gpu_archs8 "30 35 50 52 60 61")
|
||||
|
||||
######################################################################################
|
||||
# A function for automatic detection of GPUs installed (if autodetection is enabled)
|
||||
# Usage:
|
||||
# detect_installed_gpus(out_variable)
|
||||
function(detect_installed_gpus out_variable)
|
||||
if(NOT CUDA_gpu_detect_output)
|
||||
set(cufile ${PROJECT_BINARY_DIR}/detect_cuda_archs.cu)
|
||||
|
||||
file(WRITE ${cufile} ""
|
||||
"#include <cstdio>\n"
|
||||
"int main() {\n"
|
||||
" int count = 0;\n"
|
||||
" if (cudaSuccess != cudaGetDeviceCount(&count)) return -1;\n"
|
||||
" if (count == 0) return -1;\n"
|
||||
" for (int device = 0; device < count; ++device) {\n"
|
||||
" cudaDeviceProp prop;\n"
|
||||
" if (cudaSuccess == cudaGetDeviceProperties(&prop, device))\n"
|
||||
" std::printf(\"%d.%d \", prop.major, prop.minor);\n"
|
||||
" }\n"
|
||||
" return 0;\n"
|
||||
"}\n")
|
||||
|
||||
execute_process(COMMAND "${CUDA_NVCC_EXECUTABLE}" "-ccbin=${CUDA_HOST_COMPILER}"
|
||||
"--run" "${cufile}"
|
||||
WORKING_DIRECTORY "${PROJECT_BINARY_DIR}/CMakeFiles/"
|
||||
RESULT_VARIABLE nvcc_res OUTPUT_VARIABLE nvcc_out
|
||||
ERROR_QUIET OUTPUT_STRIP_TRAILING_WHITESPACE)
|
||||
|
||||
if(nvcc_res EQUAL 0)
|
||||
# only keep the last line of nvcc_out
|
||||
STRING(REGEX REPLACE ";" "\\\\;" nvcc_out "${nvcc_out}")
|
||||
STRING(REGEX REPLACE "\n" ";" nvcc_out "${nvcc_out}")
|
||||
list(GET nvcc_out -1 nvcc_out)
|
||||
string(REPLACE "2.1" "2.1(2.0)" nvcc_out "${nvcc_out}")
|
||||
set(CUDA_gpu_detect_output ${nvcc_out} CACHE INTERNAL "Returned GPU architetures from detect_installed_gpus tool" FORCE)
|
||||
endif()
|
||||
endif()
|
||||
|
||||
if(NOT CUDA_gpu_detect_output)
|
||||
message(STATUS "Automatic GPU detection failed. Building for all known architectures.")
|
||||
set(${out_variable} ${paddle_known_gpu_archs} PARENT_SCOPE)
|
||||
else()
|
||||
set(${out_variable} ${CUDA_gpu_detect_output} PARENT_SCOPE)
|
||||
endif()
|
||||
endfunction()
|
||||
|
||||
|
||||
########################################################################
|
||||
# Function for selecting GPU arch flags for nvcc based on CUDA_ARCH_NAME
|
||||
# Usage:
|
||||
# select_nvcc_arch_flags(out_variable)
|
||||
function(select_nvcc_arch_flags out_variable)
|
||||
# List of arch names
|
||||
set(archs_names "Kepler" "Maxwell" "Pascal" "All" "Manual")
|
||||
set(archs_name_default "All")
|
||||
if(NOT CMAKE_CROSSCOMPILING)
|
||||
list(APPEND archs_names "Auto")
|
||||
endif()
|
||||
|
||||
# set CUDA_ARCH_NAME strings (so it will be seen as dropbox in CMake-Gui)
|
||||
set(CUDA_ARCH_NAME ${archs_name_default} CACHE STRING "Select target NVIDIA GPU achitecture.")
|
||||
set_property( CACHE CUDA_ARCH_NAME PROPERTY STRINGS "" ${archs_names} )
|
||||
mark_as_advanced(CUDA_ARCH_NAME)
|
||||
|
||||
# verify CUDA_ARCH_NAME value
|
||||
if(NOT ";${archs_names};" MATCHES ";${CUDA_ARCH_NAME};")
|
||||
string(REPLACE ";" ", " archs_names "${archs_names}")
|
||||
message(FATAL_ERROR "Only ${archs_names} architeture names are supported.")
|
||||
endif()
|
||||
|
||||
if(${CUDA_ARCH_NAME} STREQUAL "Manual")
|
||||
set(CUDA_ARCH_BIN ${paddle_known_gpu_archs} CACHE STRING "Specify 'real' GPU architectures to build binaries for, BIN(PTX) format is supported")
|
||||
set(CUDA_ARCH_PTX "50" CACHE STRING "Specify 'virtual' PTX architectures to build PTX intermediate code for")
|
||||
mark_as_advanced(CUDA_ARCH_BIN CUDA_ARCH_PTX)
|
||||
else()
|
||||
unset(CUDA_ARCH_BIN CACHE)
|
||||
unset(CUDA_ARCH_PTX CACHE)
|
||||
endif()
|
||||
|
||||
if(${CUDA_ARCH_NAME} STREQUAL "Kepler")
|
||||
set(cuda_arch_bin "30 35")
|
||||
elseif(${CUDA_ARCH_NAME} STREQUAL "Maxwell")
|
||||
set(cuda_arch_bin "50")
|
||||
elseif(${CUDA_ARCH_NAME} STREQUAL "Pascal")
|
||||
set(cuda_arch_bin "60 61")
|
||||
elseif(${CUDA_ARCH_NAME} STREQUAL "Volta")
|
||||
set(cuda_arch_bin "70")
|
||||
elseif(${CUDA_ARCH_NAME} STREQUAL "All")
|
||||
set(cuda_arch_bin ${paddle_known_gpu_archs})
|
||||
elseif(${CUDA_ARCH_NAME} STREQUAL "Auto")
|
||||
detect_installed_gpus(cuda_arch_bin)
|
||||
else() # (${CUDA_ARCH_NAME} STREQUAL "Manual")
|
||||
set(cuda_arch_bin ${CUDA_ARCH_BIN})
|
||||
endif()
|
||||
|
||||
# remove dots and convert to lists
|
||||
string(REGEX REPLACE "\\." "" cuda_arch_bin "${cuda_arch_bin}")
|
||||
string(REGEX REPLACE "\\." "" cuda_arch_ptx "${CUDA_ARCH_PTX}")
|
||||
string(REGEX MATCHALL "[0-9()]+" cuda_arch_bin "${cuda_arch_bin}")
|
||||
string(REGEX MATCHALL "[0-9]+" cuda_arch_ptx "${cuda_arch_ptx}")
|
||||
list(REMOVE_DUPLICATES cuda_arch_bin)
|
||||
list(REMOVE_DUPLICATES cuda_arch_ptx)
|
||||
|
||||
set(nvcc_flags "")
|
||||
set(nvcc_archs_readable "")
|
||||
|
||||
# Tell NVCC to add binaries for the specified GPUs
|
||||
foreach(arch ${cuda_arch_bin})
|
||||
if(arch MATCHES "([0-9]+)\\(([0-9]+)\\)")
|
||||
# User explicitly specified PTX for the concrete BIN
|
||||
list(APPEND nvcc_flags -gencode arch=compute_${CMAKE_MATCH_2},code=sm_${CMAKE_MATCH_1})
|
||||
list(APPEND nvcc_archs_readable sm_${CMAKE_MATCH_1})
|
||||
else()
|
||||
# User didn't explicitly specify PTX for the concrete BIN, we assume PTX=BIN
|
||||
list(APPEND nvcc_flags -gencode arch=compute_${arch},code=sm_${arch})
|
||||
list(APPEND nvcc_archs_readable sm_${arch})
|
||||
endif()
|
||||
endforeach()
|
||||
|
||||
# Tell NVCC to add PTX intermediate code for the specified architectures
|
||||
foreach(arch ${cuda_arch_ptx})
|
||||
list(APPEND nvcc_flags -gencode arch=compute_${arch},code=compute_${arch})
|
||||
list(APPEND nvcc_archs_readable compute_${arch})
|
||||
endforeach()
|
||||
|
||||
string(REPLACE ";" " " nvcc_archs_readable "${nvcc_archs_readable}")
|
||||
set(${out_variable} ${nvcc_flags} PARENT_SCOPE)
|
||||
set(${out_variable}_readable ${nvcc_archs_readable} PARENT_SCOPE)
|
||||
endfunction()
|
||||
|
||||
message(STATUS "CUDA detected: " ${CUDA_VERSION})
|
||||
if (${CUDA_VERSION} LESS 7.0)
|
||||
set(paddle_known_gpu_archs ${paddle_known_gpu_archs})
|
||||
elseif (${CUDA_VERSION} LESS 8.0) # CUDA 7.x
|
||||
set(paddle_known_gpu_archs ${paddle_known_gpu_archs7})
|
||||
list(APPEND CUDA_NVCC_FLAGS "-D_MWAITXINTRIN_H_INCLUDED")
|
||||
list(APPEND CUDA_NVCC_FLAGS "-D__STRICT_ANSI__")
|
||||
elseif (${CUDA_VERSION} LESS 9.0) # CUDA 8.x
|
||||
set(paddle_known_gpu_archs ${paddle_known_gpu_archs8})
|
||||
list(APPEND CUDA_NVCC_FLAGS "-D_MWAITXINTRIN_H_INCLUDED")
|
||||
list(APPEND CUDA_NVCC_FLAGS "-D__STRICT_ANSI__")
|
||||
# CUDA 8 may complain that sm_20 is no longer supported. Suppress the
|
||||
# warning for now.
|
||||
list(APPEND CUDA_NVCC_FLAGS "-Wno-deprecated-gpu-targets")
|
||||
endif()
|
||||
|
||||
include_directories(${CUDA_INCLUDE_DIRS})
|
||||
list(APPEND EXTERNAL_LIBS ${CUDA_LIBRARIES} ${CUDA_rt_LIBRARY})
|
||||
if(NOT WITH_DSO)
|
||||
list(APPEND EXTERNAL_LIBS ${CUDNN_LIBRARY} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_curand_LIBRARY} ${NCCL_LIBRARY})
|
||||
endif(NOT WITH_DSO)
|
||||
|
||||
# setting nvcc arch flags
|
||||
select_nvcc_arch_flags(NVCC_FLAGS_EXTRA)
|
||||
list(APPEND CUDA_NVCC_FLAGS ${NVCC_FLAGS_EXTRA})
|
||||
message(STATUS "Added CUDA NVCC flags for: ${NVCC_FLAGS_EXTRA_readable}")
|
||||
|
||||
# Set C++11 support
|
||||
set(CUDA_PROPAGATE_HOST_FLAGS OFF)
|
||||
|
||||
# Release/Debug flags set by cmake. Such as -O3 -g -DNDEBUG etc.
|
||||
# So, don't set these flags here.
|
||||
list(APPEND CUDA_NVCC_FLAGS "-std=c++11")
|
||||
list(APPEND CUDA_NVCC_FLAGS "--use_fast_math")
|
||||
list(APPEND CUDA_NVCC_FLAGS "-Xcompiler -fPIC")
|
||||
# Set :expt-relaxed-constexpr to suppress Eigen warnings
|
||||
list(APPEND CUDA_NVCC_FLAGS "--expt-relaxed-constexpr")
|
||||
|
||||
if(CMAKE_BUILD_TYPE STREQUAL "Debug")
|
||||
list(APPEND CUDA_NVCC_FLAGS ${CMAKE_CXX_FLAGS_DEBUG})
|
||||
elseif(CMAKE_BUILD_TYPE STREQUAL "Release")
|
||||
list(APPEND CUDA_NVCC_FLAGS ${CMAKE_CXX_FLAGS_RELEASE})
|
||||
elseif(CMAKE_BUILD_TYPE STREQUAL "RelWithDebInfo")
|
||||
list(APPEND CUDA_NVCC_FLAGS ${CMAKE_CXX_FLAGS_RELWITHDEBINFO})
|
||||
elseif(CMAKE_BUILD_TYPE STREQUAL "MinSizeRel")
|
||||
list(APPEND CUDA_NVCC_FLAGS ${CMAKE_CXX_FLAGS_MINSIZEREL})
|
||||
endif()
|
||||
|
||||
mark_as_advanced(CUDA_BUILD_CUBIN CUDA_BUILD_EMULATION CUDA_VERBOSE_BUILD)
|
||||
mark_as_advanced(CUDA_SDK_ROOT_DIR CUDA_SEPARABLE_COMPILATION)
|
||||
Some files were not shown because too many files have changed in this diff Show More
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Reference in new issue