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Posted to commits@singa.apache.org by wa...@apache.org on 2019/04/24 14:57:38 UTC
svn commit: r1858059 [1/38] - in /incubator/singa/site/trunk: ./ en/
en/_sources/ en/_sources/community/ en/_sources/develop/ en/_sources/docs/
en/_sources/docs/model_zoo/ en/_sources/docs/model_zoo/caffe/
en/_sources/docs/model_zoo/char-rnn/ en/_sourc...
Author: wangwei
Date: Wed Apr 24 14:57:35 2019
New Revision: 1858059
URL: http://svn.apache.org/viewvc?rev=1858059&view=rev
Log:
update the docs by jenkins for commit 6eb7942
Added:
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Modified:
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incubator/singa/site/trunk/index.html
incubator/singa/site/trunk/zh/.buildinfo
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--- incubator/singa/site/trunk/en/.buildinfo (added)
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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 1499d409d023c2775f8afadba5faaacb
+tags: 645f666f9bcd5a90fca523b33c5a78b7
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+++ incubator/singa/site/trunk/en/_sources/community/issue-tracking.md.txt Wed Apr 24 14:57:35 2019
@@ -0,0 +1,27 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+## Issue Tracking
+
+___
+
+SINGA uses [JIRA](https://www.atlassian.com/software/jira) a J2EE-based, issue tracking and project management application.
+
+Issues, bugs, and feature requests should be submitted to the following issue tracking system for this project.
+
+* https://issues.apache.org/jira/browse/singa
Added: incubator/singa/site/trunk/en/_sources/community/mail-lists.rst.txt
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+++ incubator/singa/site/trunk/en/_sources/community/mail-lists.rst.txt Wed Apr 24 14:57:35 2019
@@ -0,0 +1,28 @@
+.. Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+
+
+Project Mailing Lists
+=====================
+
+These are the mailing lists that have been established for this project. For each list, there is a subscribe, unsubscribe, and an archive link.
+
+.. csv-table:: Mailing Lists
+ :header: "Name", "Post", "Subscribe", "Unsubscribe", "Archive"
+
+ "Development", "dev@singa.incubator.apache.org", "`Subscribe <ma...@singa.incubator.apache.org>`_", "`Unsubscribe <ma...@singa.incubator.apache.org.>`_", "`mail-archives.apache.org <http://mail-archives.apache.org/mod_mbox/singa-dev/>`_"
+ "Commits", "commits@singa.incubator.apache.org", "`Subscribe <ma...@singa.incubator.apache.org>`_", "`Unsubscribe <ma...@singa.incubator.apache.org>`_", "`mail-archives.apache.org <http://mail-archives.apache.org/mod_mbox/singa-commits/>`_"
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--- incubator/singa/site/trunk/en/_sources/community/source-repository.rst.txt (added)
+++ incubator/singa/site/trunk/en/_sources/community/source-repository.rst.txt Wed Apr 24 14:57:35 2019
@@ -0,0 +1,64 @@
+.. Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+
+Source Repository
+=================
+
+This project uses `Git <http://git-scm.com/>`_ to manage its source code. Instructions on Git use can be found at http://git-scm.com/documentation .
+
+Web Access
+----------
+
+The following is a link to the online source repository.
+
+* https://gitbox.apache.org/repos/asf?p=incubator-singa.git
+
+Contributors
+------------
+
+Contributors are encouraged to rebase their commits onto the latest master before sending the pull requests to make the git history clean. The following git instructors should be executed after committing the current work:
+
+.. code-block:: bash
+
+ git checkout master
+ git pull <apache/incubator-singa upstream> master:master
+ git checkout <new feature branch>
+ git rebase master
+
+Committers
+----------
+
+* To connect your Apache account with your Github account, Please follow the instructions on: https://gitbox.apache.org/setup/. After that you can directly merge PRs using GitHubâs UI.
+
+To merge pull request https://github.com/apache/incubator-singa/pull/xxx, the following instructions should be executed,
+
+.. code-block:: bash
+
+ git clone https://github.com/apache/incubator-singa.git
+ git remote add asf https://gitbox.apache.org/repos/asf/incubator-singa.git
+ # optional
+ git pull asf master:master
+ git fetch origin pull/xxx/head:prxxx
+ git merge prxxx
+ git push asf master:master
+
+* To migrate from git-wip-us.apache.org to Gitbox: If you already cloned the SINGA repository from the old repo https://git-wip-us.apache.org/repos/asf/incubator-singa.git, you can update the master by:
+
+.. code-block:: bash
+
+ git remote set-url origin git@github.com/apache/singa.git
+
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@@ -0,0 +1,84 @@
+.. Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+
+
+The SINGA Team
+==============
+
+A successful project requires many people to play many roles. Some members write code or documentation, while others are valuable as testers, submitting patches and suggestions.
+
+Mentors
+-------
+
+================== ============
+Name Email
+================== ============
+Daniel Dai daijy@apache.org
+Ted Dunning tdunning@apache.org
+Alan Gates gates@apache.org
+Thejas Nair thejas@apache.org
+================== ============
+
+
+Developers
+----------
+
+The SINGA community has developers mainly from National University of Singapore, Zhejiang University, NetEase, Osaka University, yzBigData, etc.
+
++--------------------+--------------------------------+-----------------------------------------------+
+| Name | Email | Organization |
++====================+================================+===============================================+
+| Gang Chen | cg@zju.edu.cn | Zhejiang University |
++--------------------+--------------------------------+-----------------------------------------------+
+| Haibo Chen | hzchenhaibo@corp.netease.com | NetEase |
++--------------------+--------------------------------+-----------------------------------------------+
+| Anh Dinh | dinhtta@apache.org | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Jinyang Gao | jinyang@apache.org | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Xin Ji | jixin@comp.nus.edu.sg | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Chonho Lee | chonho@gmail.com | Osaka University |
++--------------------+--------------------------------+-----------------------------------------------+
+| Zhaojing Luo | zhaojing@apache.org | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Beng Chin Ooi | ooibc@comp.nus.edu.sg | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Kian-Lee Tan | tankl@apache.org | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Anthony K. H. Tung | atung@comp.nus.edu.sg | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Ji Wang | wangji@comp.nus.edu.sg | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Sheng Wang | wangsh@apache.org | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Wei Wang | wangwei@apache.org | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Yuan Wang | wangyuan@corp.netease.com | NetEase |
++--------------------+--------------------------------+-----------------------------------------------+
+| Wenfeng Wu | wuwf@comp.nus.edu.sg | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Zhongle Xie | zhongle@apache.org | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Meihui Zhang | meihui_zhang@sutd.edu.sg | Singapore University of Technology and Design |
++--------------------+--------------------------------+-----------------------------------------------+
+| Kaiping Zheng | kaiping@apache.org | National University of Singapore |
++--------------------+--------------------------------+-----------------------------------------------+
+| Moaz Reyad | moaz@apache.org | University of Genoa |
++--------------------+--------------------------------+-----------------------------------------------+
+| Chang Yao | yaochang2009@gmail.com | yzBigdata |
++--------------------+--------------------------------+-----------------------------------------------+
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@@ -0,0 +1,77 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+## How to Contribute Code
+
+
+### Coding Style
+
+The SINGA codebase follows the [Google C++ Style Guide](http://google-styleguide.googlecode.com/svn/trunk/cppguide.xml).
+
+To check if your code follows the style, you can use the provided cpplint tool:
+
+ $ ./tool/cpplint.py YOUR_FILE
+
+
+### JIRA format
+
+Like other Apache projects, SINGA uses JIRA to track bugs, improvements and
+other high-level discussions (e.g., system design and features). Github pull requests are
+used for implementation discussions, e.g., code review and code merge.
+
+* Provide a descriptive Title.
+* Write a detailed Description. For bug reports, this should ideally include a
+ short reproduction of the problem. For new features, it may include a design
+ document.
+* Set [required fields](https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark#ContributingtoSpark-JIRA)
+
+### Pull Request
+
+The work flow is
+
+* Fork the [SINGA Github repository](https://github.com/apache/incubator-singa) to
+your own Github account.
+
+* Clone your fork, create a new branch (e.g., feature-foo or fixbug-foo),
+ work on it. After finishing your job,
+ [rebase](https://git-scm.com/book/en/v2/Git-Branching-Rebasing) it to the
+ current latest master and push commits to your own Github account (the new
+ branch).
+
+* Open a pull request against the master branch of apache/incubator-singa.
+The PR title should be of the form SINGA-xxxx Title, where
+SINGA-xxxx is the relevant JIRA number, and Title may be the JIRA's title or a
+more specific title describing the PR itself, for example, "SINGA-6 Implement thread-safe singleton". Detailed description can be copied from the JIRA.
+Consider identifying committers or other contributors who have worked on the
+code being changed. Find the file(s) in Github and click "Blame" to see a
+line-by-line annotation of who changed the code last. You can add @username in
+the PR description to ping them immediately.
+Please state that the contribution is your original work and that you license
+the work to the project under the project's open source license. Further commits (e.g., bug fix)
+to your new branch will be added to this pull request automatically by Github.
+
+* Wait for one committer to review the patch. If no conflicts, the committers will merge it with
+the master branch. The merge should a) not use rebase b) disable fast forward merge c) check the
+commit message format and test the code/feature.
+
+* If there are too many small commit messages, you will be told to squash your commits into fewer meaningful
+commits. If your commit message does not follow the format (i.e., SINGA-xxxx), you will be told to
+reword your commit message. Both changes can be done using interactive git rebase. Once you
+get the commits corrected, push them to you own github again. Your pull request
+will be automatically updated. For details, please refer to
+[Rebase Pull Requests](https://github.com/edx/edx-platform/wiki/How-to-Rebase-a-Pull-Request).
Added: incubator/singa/site/trunk/en/_sources/develop/contribute-docs.md.txt
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@@ -0,0 +1,54 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+# How to Contribute to Documentation
+
+
+## Website
+This document gives step-by-step instructions for deploying [SINGA website](http://singa.incubator.apache.org).
+
+SINGA website is built by [Sphinx](http://www.sphinx-doc.org) >=1.4.4 from a source tree stored in git: https://github.com/apache/incubator-singa/tree/master/doc.
+
+To install Sphinx:
+
+ $ pip install -U Sphinx
+
+To install the markdown support for Sphinx:
+
+ $ pip install recommonmark
+
+To install the rtd theme:
+
+ $ pip install sphinx_rtd_theme
+
+You can build the website by executing the following command from the doc folder:
+
+ $ ./build.sh html
+
+Committers can update the [SINGA website](http://singa.apache.org/en/index.html) by following these steps:
+
+ $ cd _build
+ $ svn co https://svn.apache.org/repos/asf/incubator/singa/site/trunk
+ $ cp -r html/* trunk
+ # svn add <newly added html files>
+ $ svn commit -m "commit messages" --username <committer ID> --password <password>
+
+
+## CPP API
+
+To generate docs, run "doxygen" from the doc folder (Doxygen >= 1.8 recommended)
Added: incubator/singa/site/trunk/en/_sources/develop/how-contribute.md.txt
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@@ -0,0 +1,36 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+# How to Contribute to SINGA
+
+As with any open source project, there are several ways you can help:
+
+* Join the [mailing list](http://singa.apache.org/en/community/mail-lists.html) and answer other user's questions.
+* [Build SINGA](http://singa.apache.org/en/docs/installation.html) by yourself.
+* Report bugs, feature requests and other issues in the [issue tracking](http://singa.apache.org/en/community/issue-tracking.html) application.
+* Check SINGA's [development schedule](http://singa.apache.org/en/develop/schedule.html) and [contribute code](http://singa.apache.org/en/develop/contribute-code.html) by providing patches.
+* [Help with the documentation](http://singa.apache.org/en/develop/contribute-docs.html) by updating webpages that are lacking or unclear.
+
+
+# How to become a SINGA committer
+
+SINGA committers are members that have write access to SINGA code and documentation repositories. They can contribute by themselves and accept other contributions.
+
+Becoming a SINGA committer requires understanding the Apache Way and being an active member in the SINGA project. An active member participates on mailing lists, answers questions, contributes code, tests and documentation, presents SINGA in talks and seminars, verifies releases and report issues or feature requests.
+
+New committers can be suggested by current committers or PPMC members, and voted upon by the PPMC according to Apache guidelines. You can start by talking to other committers and ask for their advice and guidance.
Added: incubator/singa/site/trunk/en/_sources/develop/how-to-release.rst.txt
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@@ -0,0 +1,228 @@
+.. Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+
+How to prepare a release
+========================
+
+This is a guide for the release preparing process in SINGA.
+
+Select a release manager
+------------------------
+
+The release manager (RM) is the coordinator for the release process. It is the RM's signature (.asc) that is uploaded together with the release. The RM generates KEY (RSA 4096-bit) and uploads it to a public key server. The RM needs to get his key endorsed (signed) by other Apache user, to be connected to the web of trust. He should first ask the mentor to help signing his key. http://www.apache.org/dev/release-signing.html
+
+Check:
+ + The codebase does not include third-party code which is not compatible to APL
+ + The dependencies are compatible with APL. GNU-like licenses are NOT compatible
+ + All source files written by us MUST include the Apache license header: http://www.apache.org/legal/src-headers.html. There's a script in there which helps propagating the header to all files.
+ + The build process is error-free.
+ + Unit tests are included (as much as possible)
+ + The Jupyter notebooks are working with the new release
+ + The online documentation on the Apache website is up to date.
+
+Prepare LICENSE file
+--------------------
+
+copy and paste this http://apache.org/licenses/LICENSE-2.0.txt
+
+Prepare NOTICE file
+-------------------
+
+ + Use this template: http://apache.org/legal/src-headers.html#notice
+ + If we include any third party code in the release package which is not APL, must state it at the end of the NOTICE file.
+ + Example: http://apache.org/licenses/example-NOTICE.txt
+
+Prepare RELEASE_NOTES file
+--------------------------
+
+ + Introduction, Features, Bugs (link to JIRA), Changes (N/A for first erlease), Dependency list, Incompatibility issues.
+ + Follow this example: http://commons.apache.org/proper/commons-digester/commons-digester-3.0/RELEASE-NOTES.txt
+
+Prepare README file
+-------------------
+ + How to build, run test, run examples
+ + List of dependencies.
+ + Mail list, website, etc. Any information useful for user to start.
+
+Prepare DISCLAIMER file
+-----------------------
+ + modify from http://incubator.apache.org/guides/branding.html#disclaimers
+
+Package the release
+-------------------
+
+The release should be packaged into : apache-singa-incubating-xx.xx.xx.tar.gz
+ + src/
+ + README
+ + LICENSE
+ + NOTICE
+ + RELEASE_NOTES
+ + DISCLAIMER
+ + ...
+
+Upload the release
+-------------------
+
+The release is uploaded to the RMâs Apache page: people.apache.org/~ID/...
+ + apache-singa-incubating-xx.xx.xx.tar.gz
+ + KEY
+ + XX.acs
+ + XX.md5
+
+Roll out artifacts to mirrors
+-----------------------------
+
+svn add to âdist/release/incubator/singaâ
+
+Delete old artifacts (automatically archived)
+
+Update the Download page
+------------------------
+
+The tar.gz file MUST be downloaded from mirror, using closer.cgi script
+other artifacts MUST be downloaded from main Apache site
+Good idea to update EC2 image and make it available for download as well
+
+Make the internal announcements
+-------------------------------
+
+Template for singa-dev@ voting:
+
+To: dev@singa.incubator.apache.org
+Subject: [VOTE] Release apache-singa-X.Y.Z-incubating (release candidate N)
+
+Hi all,
+
+I have created a build for Apache SINGA X.Y.Z-incubating, release candidate N.
+
+The artifacts to be voted on are located here:
+https://dist.apache.org/repos/dist/dev/incubator/singa/apache-singa-X.Y.Z-incubating-rcN/
+
+The hashes of the artifacts are as follows:
+apache-singa-X.Y.Z-incubating.tar.gz.md5 XXXX
+apache-singa-X.Y.Z-incubating.tar.gz.sha256 XXXX
+
+Release artifacts are signed with the following key:
+https://people.apache.org/keys/committer/{Apache ID of the Release Manager}.asc
+
+and the signature file is:
+apache-singa-X.Y.Z-incubating.tar.gz.asc
+
+Please vote on releasing this package. The vote is open for at least 72 hours and passes if a majority of at least three +1 votes are cast.
+
+[ ] +1 Release this package as Apache SINGA X.Y.Z-incubating
+[ ] 0 I don't feel strongly about it, but I'm okay with the release
+[ ] -1 Do not release this package because...
+
+Here is my vote:
+
++1
+
+{SINGA Team Member Name}
+
+Wait at least 48 hours for test responses
+
+Any PPMC, committer or contributor can test features for releasing, and feedback. Based on that, PPMC will decide whether start a vote.
+
+Call a vote in dev
+------------------
+
+Call a vote in dev@singa.apache.org
+
+
+
+Vote Check
+----------
+
+All PPMC members and committers should check these before vote +1 :
+
+
+Call for a vote in Apache IPMC
+------------------------------
+
+Call a vote in general@incubator.apache.org
+
+Vote result mail
+----------------
+
+Template for singa-dev@ voting (results):
+
+
+Subject: [RESULT] [VOTE] Release apache-singa-X.Y.Z-incubating (release candidate N)
+To: dev@singa.incubator.apache.org
+
+Thanks to everyone who has voted and given their comments. The tally is as follows.
+
+N binding +1s:
+<names>
+
+N non-binding +1s:
+<names>
+
+No 0s or -1s.
+
+I am delighted to announce that the proposal to release
+Apache SINGA X.Y.Z-incubating has passed.
+
+I'll now start a vote on the general list. Those of you in the IPMC, please recast your vote on the new thread.
+
+{SINGA Team Member Name}
+
+Template for general@ voting - results
+
+
+To: general@incubator.apache.org
+Subject: [RESULT] [VOTE] Release Apache SINGA X.Y.Z (incubating)
+
+Thanks everyone for their votes and comments.
+
+I'm delighted to announce that this vote passes with the following results:
+
+N binding +1s:
+<names>
+
+N non-binding +1s:
+<names>
+
+No 0s or -1s.
+
+Weâll now roll the release out to the mirrors.
+
+{SINGA Team Member Name}
+
+
+Publish release
+---------------
+
+Template for ANNOUNCING the release
+
+To: announce@apache.org, dev@singa.apache.org
+Subject: [ANNOUNCE] Apache SINGA (incubating) X.Y.Z released
+
+We are pleased to announce that SINGA (incubating) X.Y.Z is released.
+
+SINGA is a general distributed deep learning platform for training big deep learning models over large datasets. It is designed with an intuitive programming model based on the layer abstraction. SINGA supports a wide variety of popular deep learning models.
+
+The release is available at:
+http://singa.incubator.apache.org/downloads.html
+
+The main features of this release include XXX
+
+We look forward to hearing your feedbacks, suggestions, and contributions to the project.
+
+On behalf of the SINGA team,
+{SINGA Team Member Name}
\ No newline at end of file
Added: incubator/singa/site/trunk/en/_sources/develop/schedule.rst.txt
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==============================================================================
--- incubator/singa/site/trunk/en/_sources/develop/schedule.rst.txt (added)
+++ incubator/singa/site/trunk/en/_sources/develop/schedule.rst.txt Wed Apr 24 14:57:35 2019
@@ -0,0 +1,65 @@
+.. Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+
+
+Development Schedule
+====================
+
+.. csv-table::
+ :header: "Release","Module","Feature"
+
+ "v0.1 Sep 2015 ","Neural Network ","Feed forward neural network, including CNN, MLP "
+ " "," ","RBM-like model, including RBM "
+ " "," ","Recurrent neural network, including standard RNN "
+ " ","Architecture ","One worker group on single node (with data partition) "
+ " "," ","Multi worker groups on single node using `Hogwild <http://www.eecs.berkeley.edu/~brecht/papers/hogwildTR.pdf>`_ "
+ " "," ","Distributed Hogwild"
+ " "," ","Multi groups across nodes, like `Downpour <http://papers.nips.cc/paper/4687-large-scale-distributed-deep-networks>`_"
+ " "," ","All-Reduce training architecture like `DeepImage <http://arxiv.org/abs/1501.02876>`_ "
+ " "," ","Load-balance among servers "
+ " ","Failure recovery ","Checkpoint and restore "
+ " ","Tools ","Installation with GNU auto Tools "
+ "v0.2 Jan 2016 ","Neural Network ","Feed forward neural network, including AlexNet, cuDNN layers,Tools "
+ " "," ","Recurrent neural network, including GRULayer and BPTT "
+ " "," ","Model partition and hybrid partition "
+ " ","Tools ","Integration with Mesos for resource management "
+ " "," ","Prepare Docker images for deployment"
+ " "," ","Visualization of neural net and debug information "
+ " ","Binding ","Python binding for major components "
+ " ","GPU ","Single node with multiple GPUs "
+ "v0.3 April 2016 ","GPU ","Multiple nodes, each with multiple GPUs"
+ " "," ","Heterogeneous training using both GPU and CPU `CcT <http://arxiv.org/abs/1504.04343>`_"
+ " "," ","Support cuDNN v4 "
+ " ","Installation ","Remove dependency on ZeroMQ, CZMQ, Zookeeper for single node training"
+ " ","Updater ","Add new SGD updaters including Adam, AdamMax and AdaDelta"
+ " ","Binding ","Enhance Python binding for training"
+ "v1.0 Sep 2016 ","Programming abstraction ","Tensor with linear algebra, neural net and random operations "
+ " "," ","Updater for distributed parameter updating "
+ " ","Hardware ","Use Cuda and Cudnn for Nvidia GPU"
+ " "," ","Use OpenCL for AMD GPU or other devices"
+ " ","Cross-platform ","To extend from Linux to MacOS"
+ " "," ","Large image models, e.g., `VGG <https://arxiv.org/pdf/1409.1556.pdf>`_ and `Residual Net <http://arxiv.org/abs/1512.03385>`_"
+ "v1.1 Jan 2017 ","Model Zoo ","GoogleNet; Health-care models"
+ " ","Caffe converter ","Use SINGA to train models configured in caffe proto files"
+ " ","Model components ","Add concat and slice layers; accept multiple inputs to the net"
+ " ","Compilation and installation ","Windows suppport"
+ " "," ","Simplify the installation by compiling protobuf and openblas together with SINGA"
+ " "," ","Build python wheel automatically using Jenkins"
+ " "," ","Install SINGA from Debian packages"
+ "v1.2 June 2018 ","AutoGrad ","AutoGrad for BP"
+ " ","Python 3 ","Support Python 3 for PySinga"
+ " ","Models ","Add popular models, including VGG, ResNet, DenseNet, InceptionNet"
Added: incubator/singa/site/trunk/en/_sources/docs.rst.txt
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/en/_sources/docs.rst.txt?rev=1858059&view=auto
==============================================================================
--- incubator/singa/site/trunk/en/_sources/docs.rst.txt (added)
+++ incubator/singa/site/trunk/en/_sources/docs.rst.txt Wed Apr 24 14:57:35 2019
@@ -0,0 +1,23 @@
+.. Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+
+
+Documentation
+=============
+
+.. toctree::
+ docs/index
Added: incubator/singa/site/trunk/en/_sources/docs/autograd.md.txt
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==============================================================================
--- incubator/singa/site/trunk/en/_sources/docs/autograd.md.txt (added)
+++ incubator/singa/site/trunk/en/_sources/docs/autograd.md.txt Wed Apr 24 14:57:35 2019
@@ -0,0 +1,166 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+
+
+# Autograd in Singa
+
+There are two typical ways to implement autograd, via symbolic differentiation like [Theano](http://deeplearning.net/software/theano/index.html) or reverse differentiation like [Pytorch](https://pytorch.org/docs/stable/notes/autograd.html). Singa follows Pytorch way, which records the computation graph and apply the backward propagation automatically after forward propagation. The autograd algorithm is explained in details [here](https://pytorch.org/docs/stable/notes/autograd.html). We explain the relevant modules in Singa and give an example to illustrate the usage.
+
+## Relevant Modules
+
+There are three classes involved in autograd, namely `singa.tensor.Tensor` , `singa.autograd.Operation`, and `singa.autograd.Layer`. In the rest of this article, we use tensor, operation and layer to refer to an instance of the respective class.
+
+### Tensor
+
+Three attributes of Tensor are used by autograd,
+- `.creator` is an `Operation` instance. It records the operation that generates the Tensor instance.
+- `.requires_grad` is a boolean variable. It is used to indicate that the autograd algorithm needs to compute the gradient of the tensor (i.e., the owner). For example, during backpropagation, the gradients of the tensors for the weight matrix of a linear layer and the feature maps of a convolution layer (not the bottom layer) should be computed.
+- `.stores_grad` is a boolean variable. It is used to indicate that the gradient of the owner tensor should be stored and output by the backward function. For example, the gradient of the feature maps is computed during backpropagation, but is not included in the output of the backward function.
+
+Programmers can change `requires_grad` and `stores_grad` of a Tensor instance. For example, if later is set to True, the corresponding gradient is included in the output of the backward function. It should be noted that if `stores_grad` is True, then `requires_grad` must be true, not vice versa.
+
+
+### Operation
+
+It takes one or more `Tensor` instances as input, and then outputs one or more `Tensor` instances. For example, ReLU can be implemented as a specific Operation subclass. When an `Operation` instance is called (after instantiation), the following two steps are executed:
+
+1. record the source operations, i.e., the `creator`s of the input tensors. 2. do calculation by calling member function `.forward()`
+
+There are two member functions for forwarding and backwarding, i.e., `.forward()` and `.backward()`. They take `Tensor.data` as inputs (the type is `CTensor`), and output `Ctensor`s. To add a specific operation, subclass `operation` should implement their own `.forward()` and `.backward()`. The `backward()` function is called by the `backward()` function of autograd automatically during backward propogation to compute the gradients of inputs (according to the `require_grad` field).
+
+### Layer
+
+For those operations that require parameters, we package them into a new class, `Layer`. For example, convolution operation is wrapped into a convolution layer. `Layer` manages (stores) the parameters and calls the corresponding `Operation`s to implement the transformation.
+
+
+
+## Examples
+
+Multiple examples are provided in the [example folder](https://github.com/apache/incubator-singa/tree/master/examples/autograd). We explain two representative examples here.
+
+### Operation only
+
+The following codes implement a MLP model using only Operation instances (no Layer instances).
+
+#### Import packages
+
+```
+from singa.tensor import Tensor
+from singa import autograd
+from singa import opt
+```
+
+#### Create weight matrix and bias vector
+
+The parameter tensors are created with both `requires_grad` and `stores_grad` set to True.
+
+```
+w0 = Tensor(shape=(2, 3), requires_grad=True, stores_grad=True)
+w0.gaussian(0.0, 0.1)
+b0 = Tensor(shape=(1, 3), requires_grad=True, stores_grad=True)
+b0.set_value(0.0)
+
+w1 = Tensor(shape=(3, 2), requires_grad=True, stores_grad=True)
+w1.gaussian(0.0, 0.1)
+b1 = Tensor(shape=(1, 2), requires_grad=True, stores_grad=True)
+b1.set_value(0.0)
+```
+
+#### Training
+```
+inputs = Tensor(data=data) # data matrix
+target = Tensor(data=label) # label vector
+autograd.training = True # for training
+sgd = opt.SGD(0.05) # optimizer
+
+for i in range(10):
+ x = autograd.matmul(inputs, w0) # matrix multiplication
+ x = autograd.add_bias(x, b0) # add the bias vector
+ x = autograd.relu(x) # ReLU activation operation
+
+ x = autograd.matmul(x, w1)
+ x = autograd.add_bias(x, b1)
+
+ loss = autograd.softmax_cross_entropy(x, target)
+
+ for p, g in autograd.backward(loss):
+ sgd.update(p, g)
+```
+
+
+### Operation + Layer
+
+The following [example](https://github.com/apache/incubator-singa/blob/master/examples/autograd/mnist_cnn.py) implements a CNN model using layers provided by the autograd module.
+
+#### Create the layers
+
+```
+conv1 = autograd.Conv2d(1, 32, 3, padding=1, bias=False)
+bn1 = autograd.BatchNorm2d(32)
+pooling1 = autograd.MaxPool2d(3, 1, padding=1)
+conv21 = autograd.Conv2d(32, 16, 3, padding=1)
+conv22 = autograd.Conv2d(32, 16, 3, padding=1)
+bn2 = autograd.BatchNorm2d(32)
+linear = autograd.Linear(32 * 28 * 28, 10)
+pooling2 = autograd.AvgPool2d(3, 1, padding=1)
+```
+
+#### Define the forward function
+
+The operations in the forward pass will be recorded automatically for backward propagation.
+
+```
+def forward(x, t):
+ # x is the input data (a batch of images)
+ # t the the label vector (a batch of integers)
+ y = conv1(x) # Conv layer
+ y = autograd.relu(y) # ReLU operation
+ y = bn1(y) # BN layer
+ y = pooling1(y) # Pooling Layer
+
+ # two parallel convolution layers
+ y1 = conv21(y)
+ y2 = conv22(y)
+ y = autograd.cat((y1, y2), 1) # cat operation
+ y = autograd.relu(y) # ReLU operation
+ y = bn2(y)
+ y = pooling2(y)
+
+ y = autograd.flatten(y) # flatten operation
+ y = linear(y) # Linear layer
+ loss = autograd.softmax_cross_entropy(y, t) # operation
+ return loss, y
+```
+
+#### Training
+
+```
+autograd.training = True
+for epoch in range(epochs):
+ for i in range(batch_number):
+ inputs = tensor.Tensor(device=dev, data=x_train[
+ i * batch_sz:(1 + i) * batch_sz], stores_grad=False)
+ targets = tensor.Tensor(device=dev, data=y_train[
+ i * batch_sz:(1 + i) * batch_sz], requires_grad=False, stores_grad=False)
+
+ loss, y = forward(inputs, targets) # forward the net
+
+ for p, gp in autograd.backward(loss): # auto backward
+ sgd.update(p, gp)
+```
Added: incubator/singa/site/trunk/en/_sources/docs/cnn.md.txt
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--- incubator/singa/site/trunk/en/_sources/docs/cnn.md.txt (added)
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@@ -0,0 +1,159 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+# Quickstart - Cifar10 example
+Convolution neural network (CNN) is a type of feed-forward artificial neural network widely used for image classification. In this example, we will use a deep CNN model to do image classification for the [CIFAR10 dataset](http://www.cs.toronto.edu/~kriz/cifar.html).
+
+## Running instructions for CPP version
+Please refer to [Installation](installation.html) page for how to install SINGA. Currently, we CNN requires CUDNN, hence both CUDA and CUDNN should be installed and SINGA should be compiled with CUDA and CUDNN.
+
+The Cifar10 dataset could be downloaded by running
+
+ # switch to cifar10 directory
+ $ cd ../examples/cifar10
+ # download data for CPP version
+ $ python download_data.py bin
+
+'bin' is for downloading binary version of Cifar10 data.
+
+During downloading, you should see the detailed output like
+
+ Downloading CIFAR10 from http://www.cs.toronto.edu/~kriz/cifar-10-binary.tar.gz
+ The tar file does exist. Extracting it now..
+ Finished!
+
+Now you have prepared the data for this Cifar10 example, the final step is to execute the `run.sh` script,
+
+ # in SINGA_ROOT/examples/cifar10/
+ $ ./run.sh
+
+You should see the detailed output as follows: first read the data files in order, show the statistics of training and testing data, then show the details of neural net structure with some parameter information, finally illustrate the performance details during training and validation process. The number of epochs can be specified in `run.sh` file.
+
+ Start training
+ Reading file cifar-10-batches-bin/data_batch_1.bin
+ Reading file cifar-10-batches-bin/data_batch_2.bin
+ Reading file cifar-10-batches-bin/data_batch_3.bin
+ Reading file cifar-10-batches-bin/data_batch_4.bin
+ Reading file cifar-10-batches-bin/data_batch_5.bin
+ Reading file cifar-10-batches-bin/test_batch.bin
+ Training samples = 50000, Test samples = 10000
+ conv1(32, 32, 32, )
+ pool1(32, 16, 16, )
+ relu1(32, 16, 16, )
+ lrn1(32, 16, 16, )
+ conv2(32, 16, 16, )
+ relu2(32, 16, 16, )
+ pool2(32, 8, 8, )
+ lrn2(32, 8, 8, )
+ conv3(64, 8, 8, )
+ relu3(64, 8, 8, )
+ pool3(64, 4, 4, )
+ flat(1024, )
+ ip(10, )
+ conv1_weight : 8.09309e-05
+ conv1_bias : 0
+ conv2_weight : 0.00797731
+ conv2_bias : 0
+ conv3_weight : 0.00795888
+ conv3_bias : 0
+ ip_weight : 0.00798683
+ ip_bias : 0
+ Messages will be appended to an existed file: train_perf
+ Messages will be appended to an existed file: val_perf
+ Epoch 0, training loss = 1.828369, accuracy = 0.329420, lr = 0.001000
+ Epoch 0, val loss = 1.561823, metric = 0.420600
+ Epoch 1, training loss = 1.465898, accuracy = 0.469940, lr = 0.001000
+ Epoch 1, val loss = 1.361778, metric = 0.513300
+ Epoch 2, training loss = 1.320708, accuracy = 0.529000, lr = 0.001000
+ Epoch 2, val loss = 1.242080, metric = 0.549100
+ Epoch 3, training loss = 1.213776, accuracy = 0.571620, lr = 0.001000
+ Epoch 3, val loss = 1.175346, metric = 0.582000
+
+The training details are stored in `train_perf` file in the same directory and the validation details in `val_perf` file.
+
+
+## Running instructions for Python version
+To run CNN example in Python version, we need to compile SINGA with Python binding,
+
+ $ mkdir build && cd build
+ $ cmake -DUSE_PYTHON=ON ..
+ $ make
+
+Now download the Cifar10 dataset,
+
+ # switch to cifar10 directory
+ $ cd ../examples/cifar10
+ # download data for Python version
+ $ python download_data.py py
+
+During downloading, you should see the detailed output like
+
+ Downloading CIFAR10 from http://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz
+ The tar file does exist. Extracting it now..
+ Finished!
+
+Then execute the `train.py` script to build the model
+
+ $ python train.py
+
+You should see the output as follows including the details of neural net structure with some parameter information, reading data files, and the performance details during training and testing process.
+
+ (32L, 32L, 32L)
+ (32L, 16L, 16L)
+ (32L, 16L, 16L)
+ (32L, 16L, 16L)
+ (32L, 16L, 16L)
+ (32L, 16L, 16L)
+ (32L, 8L, 8L)
+ (32L, 8L, 8L)
+ (64L, 8L, 8L)
+ (64L, 8L, 8L)
+ (64L, 4L, 4L)
+ (1024L,)
+ Start intialization............
+ conv1_weight gaussian 7.938460476e-05
+ conv1_bias constant 0.0
+ conv2_weight gaussian 0.00793507322669
+ conv2_bias constant 0.0
+ conv3_weight gaussian 0.00799657031894
+ conv3_bias constant 0.0
+ dense_weight gaussian 0.00804364029318
+ dense_bias constant 0.0
+ Loading data ..................
+ Loading data file cifar-10-batches-py/data_batch_1
+ Loading data file cifar-10-batches-py/data_batch_2
+ Loading data file cifar-10-batches-py/data_batch_3
+ Loading data file cifar-10-batches-py/data_batch_4
+ Loading data file cifar-10-batches-py/data_batch_5
+ Loading data file cifar-10-batches-py/test_batch
+ Epoch 0
+ training loss = 1.881866, training accuracy = 0.306360 accuracy = 0.420000
+ test loss = 1.602577, test accuracy = 0.412200
+ Epoch 1
+ training loss = 1.536011, training accuracy = 0.441940 accuracy = 0.500000
+ test loss = 1.378170, test accuracy = 0.507600
+ Epoch 2
+ training loss = 1.333137, training accuracy = 0.519960 accuracy = 0.520000
+ test loss = 1.272205, test accuracy = 0.540600
+ Epoch 3
+ training loss = 1.185212, training accuracy = 0.574120 accuracy = 0.540000
+ test loss = 1.211573, test accuracy = 0.567600
+
+This script will call `alexnet.py` file to build the alexnet model. After the training is finished, SINGA will save the model parameters into a checkpoint file `model.bin` in the same directory. Then we can use this `model.bin` file for prediction.
+
+ $ python predict.py
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+.. Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+
+
+Caffe Converter
+================
+
+.. automodule:: singa.converter
+ :members:
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+.. Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+
+
+Data
+========
+
+
+
+.. automodule:: singa.data
+ :members:
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+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+# Dependent library installation
+
+## Windows
+
+This section is used to compile and install the dependent libraries under
+windows system from source codes. The following instructions ONLY work for Visual Studio 2015 as
+previous VS does not support [C++11 features](https://msdn.microsoft.com/en-us/library/hh567368.aspx) well (including generic lambdas, auto, non-static
+data member initializers). If you intend to generate a 32-bit/64-bit singa solution, please configure all the
+VS projects for the dependent libraries as 32-bit/64-bit. This can be done by
+"Configuration Manager" in VS 2015 or use corresponding generator in cmake. When compiling the following libraries, you
+may get system-specific warnings/errors. Please fix them according to the
+prompts by VS.
+
+### Google Logging
+The glog library is an optional library for singa project. But it is currently necessary for Window compilation.
+Since the latest release version of glog will encounter error C2084 on sprintf function
+under VS2015, we test the compilation and installation using the master branch from [github](https://github.com/google/glog).
+
+Step 1: Download and decompress the source code. Or use `git clone
+https://github.com/google/glog` to get the code.
+
+Step 2: Open "glog.sln" file under project folder. You will get a conversion
+dialog and please finish it by the prompts. Compile all the projects in the solution after
+proper configuration, especially "libglog" and "libglog_static" projects.
+
+Step 3: Copy all the header files and the entire directory named "glog" under
+"src\windows\" folder into the installation include folder (or system folder).
+Copy all the generated library files into the installation library folder (or
+system folder).
+
+Step 4: Done.
+
+
+### Google protobuf
+
+Tested on version 2.6.1:
+
+Step 1: Download and decompress the source code.
+
+Step 2: Open "protobuf.sln" file under "vsprojects" folder. You will get a conversion
+dialog and please finish it by the prompts. Compile all the projects in the solution after proper
+configuration. Especially "libprotobuf", "libprotobuf-lite", "libprotoc" and
+"protoc" projects.
+
+Step 3: Run "extract_includes.bat" script under "vsprojects" folder, you will
+get a new "include" folder with all the headers.
+
+Step 4: Copy the library files, such as "libprotobuf.lib",
+"libprotobuf-lite.lib", "libprotoc.lib", etc., into your installation library folder (or
+system folder). Copy the binary file "protoc" into your installation binary
+folder (or system folder). Copy all the headers and folders in "include" folder into your
+installation include folder (or system folder).
+
+Step 5: Done.
+
+### CBLAS
+
+There are ready-to-use binary packages online
+([link](https://sourceforge.net/projects/openblas/files/)). However, we still install
+OpenBLAS with version 0.2.18 as test:
+
+Step 1: Download and decompress the source code.
+
+Step 2: Start a cmd window under the OpenBLAS folder then run the following
+commands to generate the solution:
+
+ $ md build $$ cd build
+ $ cmake -G "Visual Studio 14" ..
+
+Or run `cmake -G "Visual Studio 14 Win64"` as you wish.
+
+Step 3: Install Perl into your system and put perl.exe on your path. Open "OpenBlas.sln" and build the solution, especially "libopenblas"
+project.
+
+Step 4: Copy the library files under "build\lib" folder and all header files
+under OpenBLAS folder into installation library and include folders (or system
+folders).
+
+Step 5: Done.
+
+
+## FAQ
+
+1. Error C2375 'snprintf': redefinition; different linkage
+
+ Add âHAVE_SNPRINTFâ to âC/C++ - Preprocessor - Preprocessor definitionsâ
+
+2. Error due to hash map
+
+ Add "_SILENCE_STDEXT_HASH_DEPRECATION_WARNINGS" to Preprocessor Definitions.
+
+
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+.. Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+
+
+Device
+=======
+
+
+The Device abstract represents any hardware device with memory and compuation units.
+All [Tensor operations](tensor.html) are scheduled by the resident device for execution.
+Tensor memory is also managed by the device's memory manager. Therefore, optimization
+of memory and execution are implemented in the Device class.
+
+Specific devices
+----------------
+Currently, SINGA has three Device implmentations,
+
+1. CudaGPU for an Nvidia GPU card which runs Cuda code
+2. CppCPU for a CPU which runs Cpp code
+3. OpenclGPU for a GPU card which runs OpenCL code
+
+
+Python API
+----------
+
+.. automodule:: singa.device
+ :members: create_cuda_gpus, create_cuda_gpus_on, get_default_device
+
+
+The following code provides examples of creating devices::
+
+ from singa import device
+ cuda = device.create_cuda_gpu_on(0) # use GPU card of ID 0
+ host = device.get_default_device() # get the default host device (a CppCPU)
+ ary1 = device.create_cuda_gpus(2) # create 2 devices, starting from ID 0
+ ary2 = device.create_cuda_gpus([0,2]) # create 2 devices on ID 0 and 2
+
+
+CPP API
+---------
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+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements. See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership. The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied. See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+# Docker Images
+
+
+## Available tags
+
+* `devel`, with SINGA and the development packages installed on Ubuntu16.04 (no GPU)
+* `devel-cuda`, with SINGA, CUDA8.0, CUDNN5, and other development packages installed on Ubuntu16.04
+
+## Use the existing Docker images
+
+Users can pull the Docker images from Dockerhub via
+
+ docker pull apache/singa:devel
+ # or
+ docker pull apache/singa:devel-cuda
+
+Run the docker container using
+
+ docker run -it apache/singa:devel /bin/bash
+ # or
+ docker run -it apache/singa:devel-cuda /bin/bash
+
+The latest SINGA code is under the `incubator-singa` folder.
+
+## Create new Docker images from Dockerfile
+
+New Docker images could be created by executing the following command within the
+Dockerfile folder, e.g., tool/docker/devel/
+
+ docker build -t singa:<TAG> -f Dockerfile
+
+The `<TAG>` is named as
+
+ devel|runtime[-CUDA|CPU][-CUDNN]
+
+* devel: development images with all dependent libs' header files installed and SINGA's source code; runtime: the minimal images which can run SINGA programs.
+* CUDA: cuda10.0, cuda9.0
+* CUDNN: cudnn7
+
+Here are some example tags:
+
+`devel-cuda9-cudnn7`, `devel-cuda9-cudnn7`, `devel-cuda10-cudnn7`, `devel-cpu`, `runtime-gpu` and `runtime-cpu`
+
+
+Please follow the existing Dockefiles under tool/docker/ to create other Dockefiles.
+The folder structure is like
+
+ level1: devel|runtime
+ level2: Dockerfile, OS
+ level3: Dockerfile, CUDA|MKLDNN
+
+
+For example, the path of the Dockerfile for `devel-cuda9-cudnn7` is `tool/docker/devel/ubuntu/cuda9/Dockerfile`.