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Merge pull request #458 from yahoo/experimental
TensorFlow 2.0 compatibility
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.travis.yml

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include:
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- language: python
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python: 2.7
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dist: trusty
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dist: xenial
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before_install:
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- curl -LO http://www-us.apache.org/dist/spark/spark-2.4.4/spark-2.4.4-bin-hadoop2.7.tgz
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- export SPARK_HOME=./spark
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- mkdir $SPARK_HOME
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- tar -xf spark-2.4.4-bin-hadoop2.7.tgz -C $SPARK_HOME --strip-components=1
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- export PATH=$SPARK_HOME/bin:$PATH
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- export SPARK_LOCAL_IP=127.0.0.1
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- export SPARK_CLASSPATH=./lib/tensorflow-hadoop-1.0-SNAPSHOT.jar
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- export PYTHONPATH=$(pwd)
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- source scripts/travis_before_install.sh
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install:
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- pip install -r requirements.txt
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- pip install mock
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script:
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- test/run_tests.sh
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- language: python
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python: 3.6
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dist: trusty
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dist: xenial
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before_install:
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- curl -LO http://www-us.apache.org/dist/spark/spark-2.4.4/spark-2.4.4-bin-hadoop2.7.tgz
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- export SPARK_HOME=./spark
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- mkdir $SPARK_HOME
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- tar -xf spark-2.4.4-bin-hadoop2.7.tgz -C $SPARK_HOME --strip-components=1
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- export PATH=$SPARK_HOME/bin:$PATH
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- export SPARK_LOCAL_IP=127.0.0.1
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- export SPARK_CLASSPATH=./lib/tensorflow-hadoop-1.0-SNAPSHOT.jar
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- export PYTHONPATH=$(pwd)
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- source scripts/travis_before_install.sh
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install:
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- pip install -r requirements.txt
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- pip list
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script:
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- sphinx-build -b html docs/source docs/build/html
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- test/run_tests.sh
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- language: java
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dist: trusty
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jdk: oraclejdk8
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notifications:
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email: false
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deploy:
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python: 3.6
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tags: true
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condition: "$TRAVIS_TAG =~ ^v.*$"
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- provider: script
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script: mvn deploy -DskipTests --settings .travis.settings.xml
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skip_cleanup: true
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on:
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branch: master
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jdk: oraclejdk8
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tags: true
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condition: "$TRAVIS_TAG =~ ^scala_.*$"

README.md

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<!--
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Copyright 2017 Yahoo Inc.
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Copyright 2019 Yahoo Inc.
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Licensed under the terms of the Apache 2.0 license.
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Please see LICENSE file in the project root for terms.
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-->
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TensorFlowOnSpark provides some important benefits (see [our
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blog](http://yahoohadoop.tumblr.com/post/157196317141/open-sourcing-tensorflowonspark-distributed-deep))
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over alternative deep learning solutions.
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* Easily migrate existing TensorFlow programs with <10 lines of code change
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* Support all TensorFlow functionalities: synchronous/asynchronous training, model/data parallelism, inferencing and TensorBoard
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* Server-to-server direct communication achieves faster learning when available
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* Allow datasets on HDFS and other sources pushed by Spark or pulled by TensorFlow
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* Easily integrate with your existing Spark data processing pipelines
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* Easily migrate existing TensorFlow programs with <10 lines of code change.
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* Support all TensorFlow functionalities: synchronous/asynchronous training, model/data parallelism, inferencing and TensorBoard.
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* Server-to-server direct communication achieves faster learning when available.
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* Allow datasets on HDFS and other sources pushed by Spark or pulled by TensorFlow.
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* Easily integrate with your existing Spark data processing pipelines.
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* Easily deployed on cloud or on-premise and on CPUs or GPUs.
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## Install
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TensorFlowOnSpark is provided as a pip package, which can be installed on single machines via:
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```
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# for tensorflow>=2.0.0
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pip install tensorflowonspark
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# for tensorflow<2.0.0
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pip install tensorflowonspark==1.4.4
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```
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For distributed clusters, please see our [wiki site](../../wiki) for detailed documentation for specific environments, such as our getting started guides for [single-node Spark Standalone](https://github.com/yahoo/TensorFlowOnSpark/wiki/GetStarted_Standalone), [YARN clusters](../../wiki/GetStarted_YARN) and [AWS EC2](../../wiki/GetStarted_EC2). Note: the Windows operating system is not currently supported due to [this issue](https://github.com/yahoo/TensorFlowOnSpark/issues/36).
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To use TensorFlowOnSpark with an existing TensorFlow application, you can follow our [Conversion Guide](../../wiki/Conversion-Guide) to describe the required changes. Additionally, our [wiki site](../../wiki) has pointers to some presentations which provide an overview of the platform.
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**Note: since TensorFlow 2.x breaks API compatibility with TensorFlow 1.x, the examples have been updated accordingly. If you are using TensorFlow 1.x, you will need to checkout the `v1.4.4` tag for compatible examples and instructions.**
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## API
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[API Documentation](https://yahoo.github.io/TensorFlowOnSpark/) is automatically generated from the code.
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Contributions are always welcome. For more information, please see our [guide for getting involved](Contributing.md).
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## License
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The use and distribution terms for this software are covered by the Apache 2.0 license.

docs/source/conf.py

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author = 'Yahoo Inc'
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# The short X.Y version
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version = '1.4.4'
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version = '2.0.0'
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# The full version, including alpha/beta/rc tags
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release = '1.4.4'
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release = '2.0.0'
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# -- General configuration ---------------------------------------------------

examples/cifar10/BUILD

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examples/cifar10/README.md

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examples/cifar10/README_orig.md

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examples/cifar10/__init__.py

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