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eralyeraly
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updated scripts, changed blob url
Signed-off-by: eraly <[email protected]>
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‎LICENSE.txt

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Copyright (c) 2020 Konduit K.K
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Copyright 2015-2019 Skymind Inc.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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##########################
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-- Misc files --
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*README.md
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*readme.md
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.github/CONTRIBUTING.md
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.github/ISSUE_TEMPLATE.md
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.github/PULL_REQUEST_TEMPLATE.md
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org/deeplearning4j/examples/misc/customlayers/CustomLayerExampleReadme.md
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org/deeplearning4j/examples/tictactoe/ReadMe.txt
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lstm-hdfs/src/resources/test/f1
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lstm-hdfs/src/resources/test/f2
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lstm-hdfs/src/resources/train/f1
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lstm-hdfs/src/resources/train/f2
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lstm-hdfs/src/resources/train/f3
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nd4j-examples/src/main/resources/numpy_cheatsheet/file.csv
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nd4j-examples/src/main/resources/numpy_cheatsheet/file.txt
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nd4j-examples/src/main/resources/numpy_cheatsheet/saveFile.csv
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nd4j-examples/src/main/resources/numpy_cheatsheet/saveFile.txt
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pydatavec-examples/basic_example.csv
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pydatavec-examples/reduction_example.csv
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rl4j-examples/cartpole.gif
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rl4j-examples/cliffwalk.gif
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rl4j-examples/cliffwalk_block.gif
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rl4j-examples/doom.gif
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rl4j-examples/scoregraph.png
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tutorials/00. Quickstart for Deeplearning4j.json
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tutorials/00. Quickstart for Deeplearning4j.zepp.ipynb
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tutorials/01. MultiLayerNetwork and ComputationGraph.json
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tutorials/01. MultiLayerNetwork and ComputationGraph.zepp.ipynb
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tutorials/02. Built-in Data Iterators.json
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tutorials/02. Built-in Data Iterators.zepp.ipynb
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tutorials/03. Logistic Regression.json
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tutorials/03. Logistic Regression.zepp.ipynb
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tutorials/04. Feed-forward.json
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tutorials/04. Feed-forward.zepp.ipynb
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tutorials/05. Basic Autoencoder- Anomaly Detection Using Reconstruction Error.json
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tutorials/05. Basic Autoencoder- Anomaly Detection Using Reconstruction Error.zepp.ipynb
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tutorials/06. Advanced Autoencoder- Trajectory Clustering using AIS.json
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tutorials/06. Advanced Autoencoder- Trajectory Clustering using AIS.zepp.ipynb
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tutorials/07. Convolutions- Train FaceNet Using Center Loss.json
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tutorials/07. Convolutions- Train FaceNet Using Center Loss.zepp.ipynb
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tutorials/08. RNNs- Sequence Classification of Synthetic Control Data.json
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tutorials/08. RNNs- Sequence Classification of Synthetic Control Data.zepp.ipynb
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tutorials/09. Early Stopping.ipynb
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tutorials/09. Early Stopping.zepp.json
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tutorials/10. Layers and Preprocessors.ipynb
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tutorials/10. Layers and Preprocessors.zepp.json
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tutorials/11. Hyperparameter Optimization.json
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tutorials/11. Hyperparameter Optimization.zepp.ipynb
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tutorials/12. Clinical Time Series LSTM Example.json
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tutorials/12. Clinical Time Series LSTM Example.zepp.ipynb
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tutorials/13. Clinical LSTM Time Series Example Using SKIL.json
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tutorials/13. Clinical LSTM Time Series Example Using SKIL.zepp.ipynb
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tutorials/14. Parallel Training.json
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tutorials/14. Parallel Training.zepp.ipynb
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tutorials/15. Sea Temperature Convolutional LSTM Example.json
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tutorials/15. Sea Temperature Convolutional LSTM Example.zepp.ipynb
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tutorials/16. Sea Temperature Convolutional LSTM Example 2.json
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tutorials/16. Sea Temperature Convolutional LSTM Example 2.zepp.ipynb
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tutorials/17. Instacart Multitask Example.json
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tutorials/17. Instacart Multitask Example.zepp.ipynb
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tutorials/18. Instacart Single Task Example.json
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tutorials/18. Instacart Single Task Example.zepp.ipynb
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tutorials/19. Cloud Detection Example.json
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tutorials/19. Cloud Detection Example.zepp.ipynb
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Copyright (c) 2020 Konduit K.K
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Copyright (c) 2015-2019 Skymind, Inc.
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Apache 2.0 License
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##########################

‎dl4j-distributed-training-examples/scripts/patentExamplePreproc.sh

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#Other variables. Don't modify these
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SCRIPTDIR=$(dirname "$0")
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JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-beta6-bin.jar
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JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-beta7-bin.jar
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AZURE_ACCT=fs.azure.account.key.${AZURE_STORAGE_ACCT}.blob.core.windows.net
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‎dl4j-distributed-training-examples/scripts/patentExampleTrain.sh

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#Other variables. Don't modify these
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SCRIPTDIR=$(dirname "$0")
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JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-beta6-bin.jar
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JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-beta7-bin.jar
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AZURE_ACCT=fs.azure.account.key.${AZURE_STORAGE_ACCT}.blob.core.windows.net
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‎dl4j-distributed-training-examples/scripts/tinyImagenetTrain.sh

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MASTER_PORT=7077 # Port for the spark master. Default is 7077
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MINIBATCH=32 # Minibatch size for preprocessed datasets
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SCRIPTDIR=$(dirname "$0")
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JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-beta6-bin.jar
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JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-beta7-bin.jar
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#Memory
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OFFHEAP_MEM_JAVACPP=20G # Maximum amount of off-heap memory

‎dl4j-distributed-training-examples/src/main/java/org/deeplearning4j/distributedtrainingexamples/patent/DownloadPreprocessPatents.java

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private int maxSequenceLength = 1000;
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@Parameter(names = {"--wordVectorsPath"})
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private String wordVectorsPath = "wasbs://resources@deeplearning4jblob.blob.core.windows.net/wordvectors/GoogleNews-vectors-negative300.bin.gz";
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private String wordVectorsPath = "wasbs://resources@dl4jdata.blob.core.windows.net/wordvectors/GoogleNews-vectors-negative300.bin.gz";
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public static void main(String[] args) throws Exception {

‎dl4j-distributed-training-examples/src/main/java/org/deeplearning4j/distributedtrainingexamples/patent/TrainPatentClassifier.java

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private int totalExamplesTest = 10000;
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@Parameter(names = {"--wordVectorsPath"}, description = "Word vectors path")
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private String wordVectorsPath = "wasbs://resources@deeplearning4jblob.blob.core.windows.net/wordvectors/GoogleNews-vectors-negative300.bin.gz";
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private String wordVectorsPath = "wasbs://resources@dl4jdata.blob.core.windows.net/wordvectors/GoogleNews-vectors-negative300.bin.gz";
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@Parameter(names = {"--saveFrequencySec"}, description = "How often (in seconds) to save a copy of the parameters for later evaluation")
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private int saveFreqSec = 180;

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