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Cleanup of multiple projects (#175) 

* Cleanup modules

* Moving subprojects to nd4j-api

* Project cleanup

* Dropped AWS sub-project

* dl4j-util moved to core

* dl4j-perf moved to core

* Tests coverage

* Revert "Moving subprojects to nd4j-api"

This reverts commit bc6eb573c6b60c407ade47172c5d204725077e6b.

* Moved nd4j-buffer and nd4j-context to nd4j-api

* Rolled back change

* Revert "Project cleanup"

This reverts commit 64ac7f369b2d968f7be437718034f093fc886ffc.

* Datavec cleaned up

* Revert "Moved nd4j-buffer and nd4j-context to nd4j-api"

This reverts commit 75f4e8da80d2551e44e1251dd6c5923289fff8e1.

# Conflicts:
#	nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/autodiff/opvalidation/ReductionBpOpValidation.java

* Resolve conflict

* Compilation fixed.

* nd4j-context and nd4j-buffer moved to nd4j-api

* Fixed TF mapping for mmul

* Fix for dl4j-cuda tests

Signed-off-by: Alex Black <blacka101@gmail.com>

* Move last few tests from deeplearning4j-nn to -core

Signed-off-by: Alex Black <blacka101@gmail.com>

* Remove incorrect TF import mapping for TensorMmul op

Signed-off-by: Alex Black <blacka101@gmail.com>

* Cleaned TF mapping

* Fix path for test results on windows

* Remove old dependency

Signed-off-by: Alex Black <blacka101@gmail.com>

* One more attempt to fix path for test results on windows

* fixup! One more attempt to fix path for test results on windows

* fixup! One more attempt to fix path for test results on windows

Co-authored-by: Alex Black <blacka101@gmail.com>
Co-authored-by: Serhii Shepel <9946053+sshepel@users.noreply.github.com>
Co-authored-by: raver119 <raver119@gmail.com>
master
Alexander Stoyakin 2020-01-24 21:35:00 +02:00 committed by raver119
parent 99a54829c2
commit 4db28a9300
156 changed files with 92 additions and 5299 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

116
datavec/datavec-camel/pom.xml
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@ -1,116 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<!--~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~ Copyright (c) 2015-2018 Skymind, Inc.
~
~ This program and the accompanying materials are made available under the
~ terms of the Apache License, Version 2.0 which is available at
~ https://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.
~
~ SPDX-License-Identifier: Apache-2.0
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
<parent>
<artifactId>datavec-parent</artifactId>
<groupId>org.datavec</groupId>
<version>1.0.0-SNAPSHOT</version>
</parent>
<modelVersion>4.0.0</modelVersion>
<artifactId>datavec-camel</artifactId>
<name>DataVec Camel Component</name>
<url>http://deeplearning4j.org</url>
<dependencies>
<dependency>
<groupId>org.apache.camel</groupId>
<artifactId>camel-csv</artifactId>
<version>${camel.version}</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.datavec</groupId>
<artifactId>datavec-api</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.camel</groupId>
<artifactId>camel-core</artifactId>
<version>${camel.version}</version>
</dependency>
<!-- support camel documentation -->
<!-- logging -->
<!-- testing -->
<dependency>
<groupId>org.apache.camel</groupId>
<artifactId>camel-test</artifactId>
<version>${camel.version}</version>
<scope>test</scope>
</dependency>
</dependencies>
<build>
<defaultGoal>install</defaultGoal>
<plugins>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<configuration>
<source>1.7</source>
<target>1.7</target>
</configuration>
</plugin>
<plugin>
<artifactId>maven-resources-plugin</artifactId>
<version>3.0.1</version>
<configuration>
<encoding>UTF-8</encoding>
</configuration>
</plugin>
<!-- generate components meta-data and validate component includes documentation etc -->
<plugin>
<groupId>org.apache.camel</groupId>
<artifactId>camel-package-maven-plugin</artifactId>
<version>${camel.version}</version>
<executions>
<execution>
<id>prepare</id>
<goals>
<goal>prepare-components</goal>
</goals>
<phase>generate-resources</phase>
</execution>
<!-- <execution>
<id>validate</id>
<goals>
<goal>validate-components</goal>
</goals>
<phase>prepare-package</phase>
</execution>-->
</executions>
</plugin>
</plugins>
</build>
<profiles>
<profile>
<id>test-nd4j-native</id>
</profile>
<profile>
<id>test-nd4j-cuda-10.2</id>
</profile>
</profiles>
</project>

45
datavec/datavec-camel/src/main/java/org/datavec/camel/component/DataVecComponent.java
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@ -1,45 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.camel.component;
import org.apache.camel.CamelContext;
import org.apache.camel.Endpoint;
import org.apache.camel.impl.UriEndpointComponent;
import java.util.Map;
/**
* Represents the component that manages {@link DataVecEndpoint}.
*/
public class DataVecComponent extends UriEndpointComponent {
public DataVecComponent() {
super(DataVecEndpoint.class);
}
public DataVecComponent(CamelContext context) {
super(context, DataVecEndpoint.class);
}
@Override
protected Endpoint createEndpoint(String uri, String remaining, Map<String, Object> parameters) throws Exception {
DataVecEndpoint endpoint = new DataVecEndpoint(uri, this);
setProperties(endpoint, parameters);
endpoint.setInputFormat(remaining);
return endpoint;
}
}

93
datavec/datavec-camel/src/main/java/org/datavec/camel/component/DataVecConsumer.java
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@ -1,93 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.camel.component;
import org.apache.camel.Exchange;
import org.apache.camel.Processor;
import org.apache.camel.impl.ScheduledPollConsumer;
import org.datavec.api.conf.Configuration;
import org.datavec.api.formats.input.InputFormat;
import org.datavec.api.records.reader.RecordReader;
import org.datavec.api.split.InputSplit;
/**
* The DataVec consumer.
* @author Adam Gibson
*/
public class DataVecConsumer extends ScheduledPollConsumer {
private final DataVecEndpoint endpoint;
private Class<? extends InputFormat> inputFormatClazz;
private Class<? extends DataVecMarshaller> marshallerClazz;
private InputFormat inputFormat;
private Configuration configuration;
private DataVecMarshaller marshaller;
public DataVecConsumer(DataVecEndpoint endpoint, Processor processor) {
super(endpoint, processor);
this.endpoint = endpoint;
try {
inputFormatClazz = (Class<? extends InputFormat>) Class.forName(endpoint.getInputFormat());
inputFormat = inputFormatClazz.newInstance();
marshallerClazz = (Class<? extends DataVecMarshaller>) Class.forName(endpoint.getInputMarshaller());
marshaller = marshallerClazz.newInstance();
configuration = new Configuration();
for (String prop : endpoint.getConsumerProperties().keySet())
configuration.set(prop, endpoint.getConsumerProperties().get(prop).toString());
} catch (Exception e) {
throw new RuntimeException(e);
}
}
//stub, still need to fill out more of the end point yet..endpoint will likely be initialized with a split
protected InputSplit inputFromExchange(Exchange exchange) {
return marshaller.getSplit(exchange);
}
@Override
protected int poll() throws Exception {
Exchange exchange = endpoint.createExchange();
InputSplit split = inputFromExchange(exchange);
RecordReader reader = inputFormat.createReader(split, configuration);
int numMessagesPolled = 0;
while (reader.hasNext()) {
// create a message body
while (reader.hasNext()) {
exchange.getIn().setBody(reader.next());
try {
// send message to next processor in the route
getProcessor().process(exchange);
numMessagesPolled++; // number of messages polled
} finally {
// log exception if an exception occurred and was not handled
if (exchange.getException() != null) {
getExceptionHandler().handleException("Error processing exchange", exchange,
exchange.getException());
}
}
}
}
return numMessagesPolled;
}
}

68
datavec/datavec-camel/src/main/java/org/datavec/camel/component/DataVecEndpoint.java
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@ -1,68 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.camel.component;
import lombok.Data;
import org.apache.camel.Consumer;
import org.apache.camel.Processor;
import org.apache.camel.Producer;
import org.apache.camel.impl.DefaultEndpoint;
import org.apache.camel.spi.Metadata;
import org.apache.camel.spi.UriEndpoint;
import org.apache.camel.spi.UriParam;
import org.apache.camel.spi.UriPath;
/**
* Represents a DataVec endpoint.
* @author Adam Gibson
*/
@UriEndpoint(scheme = "datavec", title = "datavec", syntax = "datavec:inputFormat/?outputFormat=?&inputMarshaller=?",
consumerClass = DataVecConsumer.class, label = "datavec")
@Data
public class DataVecEndpoint extends DefaultEndpoint {
@UriPath
@Metadata(required = "true")
private String inputFormat;
@UriParam(defaultValue = "")
private String outputFormat;
@UriParam
@Metadata(required = "true")
private String inputMarshaller;
@UriParam(defaultValue = "org.datavec.api.io.converters.SelfWritableConverter")
private String writableConverter;
public DataVecEndpoint(String uri, DataVecComponent component) {
super(uri, component);
}
public DataVecEndpoint(String endpointUri) {
super(endpointUri);
}
public Producer createProducer() throws Exception {
return new DataVecProducer(this);
}
public Consumer createConsumer(Processor processor) throws Exception {
return new DataVecConsumer(this, processor);
}
public boolean isSingleton() {
return true;
}
}

36
datavec/datavec-camel/src/main/java/org/datavec/camel/component/DataVecMarshaller.java
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@ -1,36 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.camel.component;
import org.apache.camel.Exchange;
import org.datavec.api.split.InputSplit;
/**
* Marshals na exchange in to an input split
* @author Adam Gibson
*/
public interface DataVecMarshaller {
/**
*
* @param exchange
* @return
*/
InputSplit getSplit(Exchange exchange);
}

109
datavec/datavec-camel/src/main/java/org/datavec/camel/component/DataVecProducer.java
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@ -1,109 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.camel.component;
import org.apache.camel.Exchange;
import org.apache.camel.impl.DefaultProducer;
import org.datavec.api.conf.Configuration;
import org.datavec.api.formats.input.InputFormat;
import org.datavec.api.io.WritableConverter;
import org.datavec.api.io.converters.SelfWritableConverter;
import org.datavec.api.records.reader.RecordReader;
import org.datavec.api.split.InputSplit;
import org.datavec.api.writable.Writable;
import java.util.ArrayList;
import java.util.Collection;
/**
* The DataVec producer.
* Converts input records in to their final form
* based on the input split generated from
* the given exchange.
*
* @author Adam Gibson
*/
public class DataVecProducer extends DefaultProducer {
private Class<? extends InputFormat> inputFormatClazz;
private Class<? extends DataVecMarshaller> marshallerClazz;
private InputFormat inputFormat;
private Configuration configuration;
private WritableConverter writableConverter;
private DataVecMarshaller marshaller;
public DataVecProducer(DataVecEndpoint endpoint) {
super(endpoint);
if (endpoint.getInputFormat() != null) {
try {
inputFormatClazz = (Class<? extends InputFormat>) Class.forName(endpoint.getInputFormat());
inputFormat = inputFormatClazz.newInstance();
marshallerClazz = (Class<? extends DataVecMarshaller>) Class.forName(endpoint.getInputMarshaller());
Class<? extends WritableConverter> converterClazz =
(Class<? extends WritableConverter>) Class.forName(endpoint.getWritableConverter());
writableConverter = converterClazz.newInstance();
marshaller = marshallerClazz.newInstance();
configuration = new Configuration();
for (String prop : endpoint.getConsumerProperties().keySet())
configuration.set(prop, endpoint.getConsumerProperties().get(prop).toString());
} catch (Exception e) {
throw new RuntimeException(e);
}
}
}
//stub, still need to fill out more of the end point yet..endpoint will likely be initialized with a split
protected InputSplit inputFromExchange(Exchange exchange) {
return marshaller.getSplit(exchange);
}
@Override
public void process(Exchange exchange) throws Exception {
InputSplit split = inputFromExchange(exchange);
RecordReader reader = inputFormat.createReader(split, configuration);
Collection<Collection<Writable>> newRecord = new ArrayList<>();
if (!(writableConverter instanceof SelfWritableConverter)) {
newRecord = new ArrayList<>();
while (reader.hasNext()) {
Collection<Writable> newRecordAdd = new ArrayList<>();
// create a message body
Collection<Writable> next = reader.next();
for (Writable writable : next) {
newRecordAdd.add(writableConverter.convert(writable));
}
newRecord.add(newRecordAdd);
}
} else {
while (reader.hasNext()) {
// create a message body
Collection<Writable> next = reader.next();
newRecord.add(next);
}
}
exchange.getIn().setBody(newRecord);
exchange.getOut().setBody(newRecord);
}
}

42
datavec/datavec-camel/src/main/java/org/datavec/camel/component/csv/marshaller/ListStringInputMarshaller.java
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@ -1,42 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.camel.component.csv.marshaller;
import org.apache.camel.Exchange;
import org.datavec.api.split.InputSplit;
import org.datavec.api.split.ListStringSplit;
import org.datavec.camel.component.DataVecMarshaller;
import java.util.List;
/**
* Marshals List<List<String>>
*
* @author Adam Gibson
*/
public class ListStringInputMarshaller implements DataVecMarshaller {
/**
* @param exchange
* @return
*/
@Override
public InputSplit getSplit(Exchange exchange) {
List<List<String>> data = (List<List<String>>) exchange.getIn().getBody();
InputSplit listSplit = new ListStringSplit(data);
return listSplit;
}
}

1
datavec/datavec-camel/src/main/resources/META-INF/services/org/apache/camel/component/datavec
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@ -1 +0,0 @@
class=org.datavec.camel.component.DataVecComponent

82
datavec/datavec-camel/src/test/java/org/datavec/camel/component/DataVecComponentTest.java
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@ -1,82 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.camel.component;
import org.apache.camel.builder.RouteBuilder;
import org.apache.camel.component.mock.MockEndpoint;
import org.apache.camel.test.junit4.CamelTestSupport;
import org.apache.commons.io.FileUtils;
import org.datavec.api.records.reader.RecordReader;
import org.datavec.api.records.reader.impl.csv.CSVRecordReader;
import org.datavec.api.split.FileSplit;
import org.datavec.api.writable.Writable;
import org.junit.BeforeClass;
import org.junit.ClassRule;
import org.junit.Test;
import org.junit.rules.TemporaryFolder;
import org.nd4j.linalg.io.ClassPathResource;
import java.io.File;
import java.util.ArrayList;
import java.util.Collection;
public class DataVecComponentTest extends CamelTestSupport {
@ClassRule
public static TemporaryFolder testDir = new TemporaryFolder();
private static File dir;
private static File irisFile;
@BeforeClass
public static void before() throws Exception {
dir = testDir.newFolder();
File iris = new ClassPathResource("iris.dat").getFile();
irisFile = new File(dir, "iris.dat");
FileUtils.copyFile(iris, irisFile );
}
@Test
public void testDataVec() throws Exception {
MockEndpoint mock = getMockEndpoint("mock:result");
//1
mock.expectedMessageCount(1);
RecordReader reader = new CSVRecordReader();
reader.initialize(new FileSplit(new ClassPathResource("iris.dat").getFile()));
Collection<Collection<Writable>> recordAssertion = new ArrayList<>();
while (reader.hasNext())
recordAssertion.add(reader.next());
mock.expectedBodiesReceived(recordAssertion);
assertMockEndpointsSatisfied();
}
@Override
protected RouteBuilder createRouteBuilder() throws Exception {
return new RouteBuilder() {
public void configure() {
from("file:" + dir.getAbsolutePath() + "?fileName=iris.dat&noop=true").unmarshal().csv()
.to("datavec://org.datavec.api.formats.input.impl.ListStringInputFormat?inputMarshaller=org.datavec.camel.component.ListStringInputMarshaller&writableConverter=org.datavec.api.io.converters.SelfWritableConverter")
.to("mock:result");
}
};
}
}

41
datavec/datavec-camel/src/test/java/org/datavec/camel/component/ListStringInputMarshaller.java
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@ -1,41 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.camel.component;
import org.apache.camel.Exchange;
import org.datavec.api.split.InputSplit;
import org.datavec.api.split.ListStringSplit;
import java.util.List;
/**
* Marshals List<List<String>>
*
* @author Adam Gibson
*/
public class ListStringInputMarshaller implements DataVecMarshaller {
/**
* @param exchange
* @return
*/
@Override
public InputSplit getSplit(Exchange exchange) {
List<List<String>> data = (List<List<String>>) exchange.getIn().getBody();
InputSplit listSplit = new ListStringSplit(data);
return listSplit;
}
}

30
datavec/datavec-camel/src/test/resources/log4j.properties
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@ -1,30 +0,0 @@
################################################################################
# Copyright (c) 2015-2018 Skymind, Inc.
#
# This program and the accompanying materials are made available under the
# terms of the Apache License, Version 2.0 which is available at
# https://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.
#
# SPDX-License-Identifier: Apache-2.0
################################################################################
#
# The logging properties used
#
log4j.rootLogger=INFO, out
# uncomment the following line to turn on Camel debugging
#log4j.logger.org.apache.camel=DEBUG
# CONSOLE appender not used by default
log4j.appender.out=org.apache.log4j.ConsoleAppender
log4j.appender.out.layout=org.apache.log4j.PatternLayout
log4j.appender.out.layout.ConversionPattern=[%30.30t] %-30.30c{1} %-5p %m%n
#log4j.appender.out.layout.ConversionPattern=%d [%-15.15t] %-5p %-30.30c{1} - %m%n

5
datavec/datavec-data/datavec-data-image/pom.xml
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@ -37,11 +37,6 @@
<version>${logback.version}</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>nd4j-buffer</artifactId>
<version>${nd4j.version}</version>
</dependency>
<dependency>
<groupId>com.github.jai-imageio</groupId>
<artifactId>jai-imageio-core</artifactId>

0
datavec/datavec-geo/pom.xml → datavec/datavec-data/datavec-geo/pom.xml
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0
datavec/datavec-geo/src/main/java/org/datavec/api/transform/geo/LocationType.java → datavec/datavec-data/datavec-geo/src/main/java/org/datavec/api/transform/geo/LocationType.java
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0
datavec/datavec-geo/src/main/java/org/datavec/api/transform/reduce/geo/CoordinatesReduction.java → datavec/datavec-data/datavec-geo/src/main/java/org/datavec/api/transform/reduce/geo/CoordinatesReduction.java
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0
datavec/datavec-geo/src/main/java/org/datavec/api/transform/transform/geo/CoordinatesDistanceTransform.java → datavec/datavec-data/datavec-geo/src/main/java/org/datavec/api/transform/transform/geo/CoordinatesDistanceTransform.java
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0
datavec/datavec-geo/src/main/java/org/datavec/api/transform/transform/geo/GeoIPFetcher.java → datavec/datavec-data/datavec-geo/src/main/java/org/datavec/api/transform/transform/geo/GeoIPFetcher.java
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0
datavec/datavec-geo/src/main/java/org/datavec/api/transform/transform/geo/IPAddressToCoordinatesTransform.java → datavec/datavec-data/datavec-geo/src/main/java/org/datavec/api/transform/transform/geo/IPAddressToCoordinatesTransform.java
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0
datavec/datavec-geo/src/main/java/org/datavec/api/transform/transform/geo/IPAddressToLocationTransform.java → datavec/datavec-data/datavec-geo/src/main/java/org/datavec/api/transform/transform/geo/IPAddressToLocationTransform.java
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0
datavec/datavec-geo/src/test/java/org/datavec/api/transform/reduce/TestGeoReduction.java → datavec/datavec-data/datavec-geo/src/test/java/org/datavec/api/transform/reduce/TestGeoReduction.java
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0
datavec/datavec-geo/src/test/java/org/datavec/api/transform/transform/TestGeoTransforms.java → datavec/datavec-data/datavec-geo/src/test/java/org/datavec/api/transform/transform/TestGeoTransforms.java
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0
datavec/datavec-hadoop/pom.xml → datavec/datavec-data/datavec-hadoop/pom.xml
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/conf/ConfigurationUtil.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/conf/ConfigurationUtil.java
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/IndexToKey.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/IndexToKey.java
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/MapFileReader.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/MapFileReader.java
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/MapFileRecordReader.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/MapFileRecordReader.java
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/MapFileSequenceRecordReader.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/MapFileSequenceRecordReader.java
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/index/LongIndexToKey.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/index/LongIndexToKey.java
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/record/RecordWritable.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/record/RecordWritable.java
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/record/SequenceRecordWritable.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/records/reader/mapfile/record/SequenceRecordWritable.java
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/records/writer/mapfile/AbstractMapFileWriter.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/records/writer/mapfile/AbstractMapFileWriter.java
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/records/writer/mapfile/MapFileRecordWriter.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/records/writer/mapfile/MapFileRecordWriter.java
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0
datavec/datavec-hadoop/src/main/java/org/datavec/hadoop/records/writer/mapfile/MapFileSequenceRecordWriter.java → datavec/datavec-data/datavec-hadoop/src/main/java/org/datavec/hadoop/records/writer/mapfile/MapFileSequenceRecordWriter.java
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0
datavec/datavec-hadoop/src/test/java/org/datavec/hadoop/conf/TestConfigurationUtil.java → datavec/datavec-data/datavec-hadoop/src/test/java/org/datavec/hadoop/conf/TestConfigurationUtil.java
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0
datavec/datavec-hadoop/src/test/java/org/datavec/hadoop/records/reader/TestMapFileRecordReader.java → datavec/datavec-data/datavec-hadoop/src/test/java/org/datavec/hadoop/records/reader/TestMapFileRecordReader.java
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0
datavec/datavec-hadoop/src/test/java/org/datavec/hadoop/records/reader/TestMapFileRecordReaderMultipleParts.java → datavec/datavec-data/datavec-hadoop/src/test/java/org/datavec/hadoop/records/reader/TestMapFileRecordReaderMultipleParts.java
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0
datavec/datavec-hadoop/src/test/java/org/datavec/hadoop/records/reader/TestMapFileRecordReaderMultiplePartsSomeEmpty.java → datavec/datavec-data/datavec-hadoop/src/test/java/org/datavec/hadoop/records/reader/TestMapFileRecordReaderMultiplePartsSomeEmpty.java
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0
datavec/datavec-hadoop/src/test/java/org/datavec/hadoop/records/writer/TestMapFileRecordWriter.java → datavec/datavec-data/datavec-hadoop/src/test/java/org/datavec/hadoop/records/writer/TestMapFileRecordWriter.java
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0
datavec/datavec-hadoop/src/test/resources/log4j.properties → datavec/datavec-data/datavec-hadoop/src/test/resources/log4j.properties
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0
datavec/datavec-hadoop/src/test/resources/logback.xml → datavec/datavec-data/datavec-hadoop/src/test/resources/logback.xml
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65
datavec/datavec-perf/pom.xml
View File

@ -1,65 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<!--~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~ Copyright (c) 2015-2018 Skymind, Inc.
~
~ This program and the accompanying materials are made available under the
~ terms of the Apache License, Version 2.0 which is available at
~ https://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.
~
~ SPDX-License-Identifier: Apache-2.0
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<parent>
<artifactId>datavec-parent</artifactId>
<groupId>org.datavec</groupId>
<version>1.0.0-SNAPSHOT</version>
</parent>
<modelVersion>4.0.0</modelVersion>
<artifactId>datavec-perf</artifactId>
<name>datavec-perf</name>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<maven.compiler.source>1.7</maven.compiler.source>
<maven.compiler.target>1.7</maven.compiler.target>
</properties>
<dependencies>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>${slf4j.version}</version>
</dependency>
<dependency>
<groupId>org.datavec</groupId>
<artifactId>datavec-data-image</artifactId>
<version>${project.version}</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.datavec</groupId>
<artifactId>datavec-api</artifactId>
<version>${project.version}</version>
</dependency>
</dependencies>
<profiles>
<profile>
<id>test-nd4j-native</id>
</profile>
<profile>
<id>test-nd4j-cuda-10.2</id>
</profile>
</profiles>
</project>

112
datavec/datavec-perf/src/main/java/org/datavec/perf/timing/IOTiming.java
View File

@ -1,112 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.perf.timing;
import lombok.val;
import org.datavec.api.records.reader.RecordReader;
import org.datavec.api.split.InputStreamInputSplit;
import org.datavec.api.writable.Writable;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.performance.PerformanceTracker;
import org.nd4j.linalg.memory.MemcpyDirection;
import java.io.BufferedInputStream;
import java.io.File;
import java.io.FileInputStream;
import java.io.InputStream;
import java.util.List;
import java.util.Map;
/**
* Timing components of a data vec pipeline
* consisting of:
* {@link RecordReader}, {@link InputStreamInputSplit}
* (note that this uses input stream input split,
* the record reader must support {@link InputStreamInputSplit} for this to work)
*
* @author Adam Gibson
*/
public class IOTiming {
/**
* Returns statistics for components of a datavec pipeline
* averaged over the specified number of times
* @param nTimes the number of times to run the pipeline for averaging
* @param recordReader the record reader
* @param file the file to read
* @param function the function
* @return the averaged {@link TimingStatistics} for input/output on a record
* reader and ndarray creation (based on the given function
* @throws Exception
*/
public static TimingStatistics averageFileRead(long nTimes, RecordReader recordReader, File file, INDArrayCreationFunction function) throws Exception {
TimingStatistics timingStatistics = null;
for(int i = 0; i < nTimes; i++) {
TimingStatistics timingStatistics1 = timeNDArrayCreation(recordReader,new BufferedInputStream(new FileInputStream(file)),function);
if(timingStatistics == null)
timingStatistics = timingStatistics1;
else {
timingStatistics = timingStatistics.add(timingStatistics1);
}
}
return timingStatistics.average(nTimes);
}
/**
*
* @param reader
* @param inputStream
* @param function
* @return
* @throws Exception
*/
public static TimingStatistics timeNDArrayCreation(RecordReader reader,
InputStream inputStream,
INDArrayCreationFunction function) throws Exception {
reader.initialize(new InputStreamInputSplit(inputStream));
long longNanos = System.nanoTime();
List<Writable> next = reader.next();
long endNanos = System.nanoTime();
long etlDiff = endNanos - longNanos;
long startArrCreation = System.nanoTime();
INDArray arr = function.createFromRecord(next);
long endArrCreation = System.nanoTime();
long endCreationDiff = endArrCreation - startArrCreation;
Map<Integer, Map<MemcpyDirection, Long>> currentBandwidth = PerformanceTracker.getInstance().getCurrentBandwidth();
val bw = currentBandwidth.get(0).get(MemcpyDirection.HOST_TO_DEVICE);
val deviceToHost = currentBandwidth.get(0).get(MemcpyDirection.HOST_TO_DEVICE);
return TimingStatistics.builder()
.diskReadingTimeNanos(etlDiff)
.bandwidthNanosHostToDevice(bw)
.bandwidthDeviceToHost(deviceToHost)
.ndarrayCreationTimeNanos(endCreationDiff)
.build();
}
public interface INDArrayCreationFunction {
INDArray createFromRecord(List<Writable> record);
}
}

74
datavec/datavec-perf/src/main/java/org/datavec/perf/timing/TimingStatistics.java
View File

@ -1,74 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.perf.timing;
import lombok.Builder;
import lombok.Data;
/**
* The timing statistics for a data pipeline including:
* ndarray creation time in nanoseconds
* disk reading time in nanoseconds
* bandwidth used in host to device in nano seconds
* bandwidth device to host in nanoseconds
*
* @author Adam Gibson
*/
@Builder
@Data
public class TimingStatistics {
private long ndarrayCreationTimeNanos;
private long diskReadingTimeNanos;
private long bandwidthNanosHostToDevice;
private long bandwidthDeviceToHost;
/**
* Accumulate the given statistics
* @param timingStatistics the statistics to add
* @return the added statistics
*/
public TimingStatistics add(TimingStatistics timingStatistics) {
return TimingStatistics.builder()
.ndarrayCreationTimeNanos(ndarrayCreationTimeNanos + timingStatistics.ndarrayCreationTimeNanos)
.bandwidthNanosHostToDevice(bandwidthNanosHostToDevice + timingStatistics.bandwidthNanosHostToDevice)
.diskReadingTimeNanos(diskReadingTimeNanos + timingStatistics.diskReadingTimeNanos)
.bandwidthDeviceToHost(bandwidthDeviceToHost + timingStatistics.bandwidthDeviceToHost)
.build();
}
/**
* Average the results relative to the number of n.
* This method is meant to be used alongside
* {@link #add(TimingStatistics)}
* accumulated a number of times
* @param n n the number of elements
* @return the averaged results
*/
public TimingStatistics average(long n) {
return TimingStatistics.builder()
.ndarrayCreationTimeNanos(ndarrayCreationTimeNanos / n)
.bandwidthDeviceToHost(bandwidthDeviceToHost / n)
.diskReadingTimeNanos(diskReadingTimeNanos / n)
.bandwidthNanosHostToDevice(bandwidthNanosHostToDevice / n)
.build();
}
}

60
datavec/datavec-perf/src/test/java/org/datavec/datavec/timing/IOTimingTest.java
View File

@ -1,60 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.datavec.datavec.timing;
import org.datavec.api.records.reader.RecordReader;
import org.datavec.api.writable.NDArrayWritable;
import org.datavec.api.writable.Writable;
import org.datavec.image.loader.NativeImageLoader;
import org.datavec.image.recordreader.ImageRecordReader;
import org.datavec.perf.timing.IOTiming;
import org.datavec.perf.timing.TimingStatistics;
import org.junit.Test;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.io.ClassPathResource;
import java.util.List;
public class IOTimingTest {
@Test
public void testTiming() throws Exception {
final RecordReader image = new ImageRecordReader(28,28);
final NativeImageLoader nativeImageLoader = new NativeImageLoader(28,28);
TimingStatistics timingStatistics = IOTiming.timeNDArrayCreation(image, new ClassPathResource("datavec-perf/largestblobtest.jpg").getInputStream(), new IOTiming.INDArrayCreationFunction() {
@Override
public INDArray createFromRecord(List<Writable> record) {
NDArrayWritable imageWritable = (NDArrayWritable) record.get(0);
return imageWritable.get();
}
});
System.out.println(timingStatistics);
TimingStatistics timingStatistics1 = IOTiming.averageFileRead(1000,image,new ClassPathResource("datavec-perf/largestblobtest.jpg").getFile(), new IOTiming.INDArrayCreationFunction() {
@Override
public INDArray createFromRecord(List<Writable> record) {
NDArrayWritable imageWritable = (NDArrayWritable) record.get(0);
return imageWritable.get();
}
});
System.out.println(timingStatistics1);
}
}

4
datavec/pom.xml
View File

@ -59,16 +59,12 @@
<modules>
<module>datavec-api</module>
<module>datavec-data</module>
<module>datavec-geo</module>
<module>datavec-hadoop</module>
<module>datavec-spark</module>
<module>datavec-camel</module>
<module>datavec-local</module>
<module>datavec-spark-inference-parent</module>
<module>datavec-jdbc</module>
<module>datavec-excel</module>
<module>datavec-arrow</module>
<module>datavec-perf</module>
<module>datavec-python</module>
</modules>

11
deeplearning4j/deeplearning4j-core/pom.xml
View File

@ -153,6 +153,17 @@
<version>${jaxb.version}</version>
<scope>provided</scope>
</dependency>
<!-- Dependencies for dl4j-perf subproject -->
<dependency>
<groupId>com.github.oshi</groupId>
<artifactId>oshi-json</artifactId>
<version>${oshi.version}</version>
</dependency>
<dependency>
<groupId>com.github.oshi</groupId>
<artifactId>oshi-core</artifactId>
<version>${oshi.version}</version>
</dependency>
</dependencies>
<profiles>

0
deeplearning4j/dl4j-perf/src/main/java/org/deeplearning4j/perf/listener/DeviceMetric.java → deeplearning4j/deeplearning4j-core/src/main/java/org/deeplearning4j/perf/listener/DeviceMetric.java
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0
deeplearning4j/dl4j-perf/src/main/java/org/deeplearning4j/perf/listener/DiskInfo.java → deeplearning4j/deeplearning4j-core/src/main/java/org/deeplearning4j/perf/listener/DiskInfo.java
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0
deeplearning4j/dl4j-perf/src/main/java/org/deeplearning4j/perf/listener/HardwareMetric.java → deeplearning4j/deeplearning4j-core/src/main/java/org/deeplearning4j/perf/listener/HardwareMetric.java
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0
deeplearning4j/dl4j-perf/src/main/java/org/deeplearning4j/perf/listener/SystemInfoFilePrintListener.java → deeplearning4j/deeplearning4j-core/src/main/java/org/deeplearning4j/perf/listener/SystemInfoFilePrintListener.java
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0
deeplearning4j/dl4j-perf/src/main/java/org/deeplearning4j/perf/listener/SystemInfoPrintListener.java → deeplearning4j/deeplearning4j-core/src/main/java/org/deeplearning4j/perf/listener/SystemInfoPrintListener.java
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0
deeplearning4j/dl4j-perf/src/main/java/org/deeplearning4j/perf/listener/SystemPolling.java → deeplearning4j/deeplearning4j-core/src/main/java/org/deeplearning4j/perf/listener/SystemPolling.java
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0
deeplearning4j/deeplearning4j-util/src/main/java/org/deeplearning4j/util/MovingWindowMatrix.java → deeplearning4j/deeplearning4j-core/src/main/java/org/deeplearning4j/util/MovingWindowMatrix.java Executable file → Normal file
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0
deeplearning4j/deeplearning4j-util/src/main/java/org/deeplearning4j/util/ThreadUtils.java → deeplearning4j/deeplearning4j-core/src/main/java/org/deeplearning4j/util/ThreadUtils.java
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0
deeplearning4j/deeplearning4j-util/src/main/java/org/deeplearning4j/util/UIDProvider.java → deeplearning4j/deeplearning4j-core/src/main/java/org/deeplearning4j/util/UIDProvider.java
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0
deeplearning4j/deeplearning4j-nn/src/test/java/org/deeplearning4j/nn/adapters/ArgmaxAdapterTest.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/nn/adapters/ArgmaxAdapterTest.java
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0
deeplearning4j/deeplearning4j-nn/src/test/java/org/deeplearning4j/nn/adapters/Regression2dAdapterTest.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/nn/adapters/Regression2dAdapterTest.java
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0
deeplearning4j/deeplearning4j-nn/src/test/java/org/deeplearning4j/nn/layers/recurrent/MaskZeroLayerTest.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/nn/layers/recurrent/MaskZeroLayerTest.java
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0
deeplearning4j/deeplearning4j-nn/src/test/java/org/deeplearning4j/nn/layers/samediff/SameDiffCustomLayerTests.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/nn/layers/samediff/SameDiffCustomLayerTests.java
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8
deeplearning4j/deeplearning4j-nn/src/test/java/org/deeplearning4j/optimize/solvers/accumulation/EncodedGradientsAccumulatorTest.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/optimize/solver/accumulation/EncodedGradientsAccumulatorTest.java
View File

@ -14,11 +14,13 @@
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.optimize.solvers.accumulation;
package org.deeplearning4j.optimize.solver.accumulation;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.deeplearning4j.BaseDL4JTest;
import org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator;
import org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler;
import org.deeplearning4j.optimize.solvers.accumulation.encoding.threshold.FixedThresholdAlgorithm;
import org.junit.Test;
import org.nd4j.linalg.api.ndarray.INDArray;
@ -68,8 +70,8 @@ public class EncodedGradientsAccumulatorTest extends BaseDL4JTest {
accumulator.receiveUpdate(encoded);
// just purge updates, like they were consumed
for (int i = 0; i < accumulator.messages.size(); i++) {
accumulator.messages.get(i).clear();
for (int i = 0; i < accumulator.getMessages().size(); i++) {
accumulator.getMessages().get(i).clear();
}
}
}

13
deeplearning4j/deeplearning4j-nn/src/test/java/org/deeplearning4j/optimize/solvers/accumulation/IndexedTailTest.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/optimize/solver/accumulation/IndexedTailTest.java
View File

@ -14,12 +14,13 @@
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.optimize.solvers.accumulation;
package org.deeplearning4j.optimize.solver.accumulation;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.apache.commons.lang3.RandomUtils;
import org.deeplearning4j.BaseDL4JTest;
import org.deeplearning4j.optimize.solvers.accumulation.IndexedTail;
import org.junit.Ignore;
import org.junit.Test;
import org.nd4j.linalg.factory.Nd4j;
@ -97,9 +98,9 @@ public class IndexedTailTest extends BaseDL4JTest {
assertEquals(-1, tail.maxAppliedIndexEverywhere());
// 2 consumers consumed 2 elements, and 1 consumer consumed 3 elements
tail.positions.get(11L).set(2);
tail.positions.get(22L).set(2);
tail.positions.get(33L).set(3);
tail.getPositions().get(11L).set(2);
tail.getPositions().get(22L).set(2);
tail.getPositions().get(33L).set(3);
// all elements including this index are safe to remove, because they were consumed everywhere
assertEquals(2, tail.maxAppliedIndexEverywhere());
@ -197,10 +198,10 @@ public class IndexedTailTest extends BaseDL4JTest {
Nd4j.getExecutioner().commit();
}
assertTrue(tail.collapsedMode.get());
assertTrue(tail.getCollapsedMode().get());
assertEquals(1, tail.updatesSize());
val array = tail.updates.get(32L);
val array = tail.getUpdates().get(32L);
assertNotNull(array);
assertEquals(sum, (int) array.getDouble(0));
}

3
deeplearning4j/deeplearning4j-nn/src/test/java/org/deeplearning4j/optimize/solvers/accumulation/SmartFancyBlockingQueueTest.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/optimize/solver/accumulation/SmartFancyBlockingQueueTest.java
View File

@ -14,12 +14,13 @@
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.optimize.solvers.accumulation;
package org.deeplearning4j.optimize.solver.accumulation;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.apache.commons.lang3.RandomUtils;
import org.deeplearning4j.BaseDL4JTest;
import org.deeplearning4j.optimize.solvers.accumulation.SmartFancyBlockingQueue;
import org.deeplearning4j.util.ThreadUtils;
import org.junit.Ignore;
import org.junit.Test;

2
deeplearning4j/deeplearning4j-nn/src/test/java/org/deeplearning4j/optimize/solvers/accumulation/ThresholdAlgorithmTests.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/optimize/solver/accumulation/ThresholdAlgorithmTests.java
View File

@ -14,7 +14,7 @@
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.optimize.solvers.accumulation;
package org.deeplearning4j.optimize.solver.accumulation;
import org.deeplearning4j.BaseDL4JTest;
import org.deeplearning4j.optimize.solvers.accumulation.encoding.ThresholdAlgorithm;

3
deeplearning4j/deeplearning4j-nn/src/test/java/org/deeplearning4j/optimize/listeners/ScoreStatTest.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/optimizer/listener/ScoreStatTest.java
View File

@ -1,5 +1,6 @@
package org.deeplearning4j.optimize.listeners;
package org.deeplearning4j.optimizer.listener;
import org.deeplearning4j.optimize.listeners.CollectScoresIterationListener;
import org.junit.Ignore;
import org.junit.Test;

0
deeplearning4j/dl4j-perf/src/test/java/org/deeplearning4j/perf/listener/SystemPollingTest.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/perf/listener/SystemPollingTest.java
View File

0
deeplearning4j/dl4j-perf/src/test/java/org/deeplearning4j/perf/listener/TestHardWareMetric.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/perf/listener/TestHardWareMetric.java
View File

0
deeplearning4j/dl4j-perf/src/test/java/org/deeplearning4j/perf/listener/TestSystemInfoPrintListener.java → deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/perf/listener/TestSystemInfoPrintListener.java
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15
deeplearning4j/deeplearning4j-cuda/src/test/java/org/deeplearning4j/gradientcheck/CuDNNGradientChecks.java
View File

@ -305,7 +305,7 @@ public class CuDNNGradientChecks extends BaseDL4JTest {
//However, numerical gradient will be 0 as forward pass doesn't depend on this "parameter"
Set<String> excludeParams = new HashSet<>(Arrays.asList("1_mean", "1_var", "1_log10stdev"));
boolean gradOK = GradientCheckUtil.checkGradients(mln, DEFAULT_EPS, DEFAULT_MAX_REL_ERROR,
DEFAULT_MIN_ABS_ERROR, PRINT_RESULTS, RETURN_ON_FIRST_FAILURE, input, labels, excludeParams);
DEFAULT_MIN_ABS_ERROR, PRINT_RESULTS, RETURN_ON_FIRST_FAILURE, input, labels, null, null, false, -1, excludeParams, null);
assertTrue(gradOK);
}
@ -417,7 +417,7 @@ public class CuDNNGradientChecks extends BaseDL4JTest {
}
boolean gradOK = GradientCheckUtil.checkGradients(mln, DEFAULT_EPS, DEFAULT_MAX_REL_ERROR,
DEFAULT_MIN_ABS_ERROR, PRINT_RESULTS, RETURN_ON_FIRST_FAILURE, input, labels, null, null, true, 32);
DEFAULT_MIN_ABS_ERROR, PRINT_RESULTS, RETURN_ON_FIRST_FAILURE, input, labels, null, null, true, 32, null, null);
assertTrue(gradOK);
}
@ -655,9 +655,12 @@ public class CuDNNGradientChecks extends BaseDL4JTest {
};
log.info("*** Starting test: " + msg + " ***");
boolean gradOK = GradientCheckUtil.checkGradients(mln, DEFAULT_EPS, DEFAULT_MAX_REL_ERROR,
DEFAULT_MIN_ABS_ERROR, PRINT_RESULTS, RETURN_ON_FIRST_FAILURE, f, l, null, null,
false, -1, null, c);
boolean gradOK = GradientCheckUtil.checkGradients(
new GradientCheckUtil.MLNConfig().net(mln).epsilon(DEFAULT_EPS)
.maxRelError(DEFAULT_MAX_REL_ERROR).minAbsoluteError(DEFAULT_MIN_ABS_ERROR)
.print(PRINT_RESULTS ? GradientCheckUtil.PrintMode.ZEROS : GradientCheckUtil.PrintMode.FAILURES_ONLY)
.exitOnFirstError(RETURN_ON_FIRST_FAILURE)
.input(f).labels(l).callEachIter(c));
assertTrue(msg, gradOK);
TestUtils.testModelSerialization(mln);
@ -691,7 +694,7 @@ public class CuDNNGradientChecks extends BaseDL4JTest {
//However, numerical gradient will be 0 as forward pass doesn't depend on this "parameter"
Set<String> excludeParams = new HashSet<>(Arrays.asList("1_mean", "1_var", "1_log10stdev"));
boolean gradOK = GradientCheckUtil.checkGradients(net, DEFAULT_EPS, DEFAULT_MAX_REL_ERROR,
DEFAULT_MIN_ABS_ERROR, PRINT_RESULTS, RETURN_ON_FIRST_FAILURE, in, labels, excludeParams);
DEFAULT_MIN_ABS_ERROR, PRINT_RESULTS, RETURN_ON_FIRST_FAILURE, in, labels, null, null, false, -1, excludeParams, null);
assertTrue(gradOK);

3
deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/optimize/solvers/accumulation/EncodedGradientsAccumulator.java
View File

@ -63,6 +63,7 @@ public class EncodedGradientsAccumulator implements GradientsAccumulator, Regist
protected int parties;
@Getter
protected MessageHandler handler;
@Getter
protected List<BlockingQueue<INDArray>> messages = new ArrayList<>();
protected List<MemoryWorkspace> workspaces = new ArrayList<>();
protected List<ReentrantLock> locks = new ArrayList<>();
@ -106,7 +107,7 @@ public class EncodedGradientsAccumulator implements GradientsAccumulator, Regist
this(parties, new EncodingHandler(thresholdAlgorithm, residualPostProcessor, 1.0, encodingDebugMode), DEFAULT_INITIAL_MEMORY, 10, 1.0, encodingDebugMode);
}
protected EncodedGradientsAccumulator(int parties, @NonNull MessageHandler handler, long initialMemory,
public EncodedGradientsAccumulator(int parties, @NonNull MessageHandler handler, long initialMemory,
int queueSize, Double boundary, boolean encodingDebugMode) {
this.parties = parties;
this.handler = handler;

18
deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/optimize/solvers/accumulation/IndexedTail.java
View File

@ -16,6 +16,7 @@
package org.deeplearning4j.optimize.solvers.accumulation;
import lombok.Getter;
import lombok.NonNull;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
@ -44,9 +45,11 @@ import java.util.concurrent.locks.ReentrantReadWriteLock;
@Slf4j
public class IndexedTail {
// here we store positions of individual consumers
@Getter
protected ConcurrentHashMap<Long, AtomicLong> positions = new ConcurrentHashMap<>();
// here we store individual updates
@Getter
protected Map<Long, INDArray> updates = new ConcurrentHashMap<>();
// simple counter for new updates
@ -67,6 +70,7 @@ public class IndexedTail {
protected final boolean allowCollapse;
protected final long[] shape;
protected final int collapseThreshold = 32;
@Getter
protected AtomicBoolean collapsedMode = new AtomicBoolean(false);
protected AtomicLong collapsedIndex = new AtomicLong(-1);
@ -148,7 +152,7 @@ public class IndexedTail {
}
}
protected long firstNotAppliedIndexEverywhere() {
public long firstNotAppliedIndexEverywhere() {
long maxIdx = -1;
// if there's no updates posted yet - just return negative value
@ -163,7 +167,7 @@ public class IndexedTail {
return maxIdx + 1;
}
protected long maxAppliedIndexEverywhere() {
public long maxAppliedIndexEverywhere() {
long maxIdx = Long.MAX_VALUE;
for (val v:positions.values()) {
if (v.get() < maxIdx)
@ -212,7 +216,7 @@ public class IndexedTail {
return getDelta(Thread.currentThread().getId());
}
protected long getDelta(long threadId) {
public long getDelta(long threadId) {
return getGlobalPosition() - getLocalPosition(threadId);
}
@ -293,7 +297,7 @@ public class IndexedTail {
/**
* This method does maintenance of updates within
*/
protected synchronized void maintenance() {
public synchronized void maintenance() {
// first of all we're checking, if all consumers were already registered. if not - just no-op.
if (positions.size() < expectedConsumers) {
log.trace("Skipping maintanance due to not all expected consumers shown up: [{}] vs [{}]", positions.size(), expectedConsumers);
@ -326,7 +330,7 @@ public class IndexedTail {
* This method returns actual number of updates stored within tail
* @return
*/
protected int updatesSize() {
public int updatesSize() {
return updates.size();
}
@ -348,11 +352,11 @@ public class IndexedTail {
return result;
}
protected boolean isDead() {
public boolean isDead() {
return dead.get();
}
protected void notifyDead() {
public void notifyDead() {
dead.set(true);
}

158
deeplearning4j/deeplearning4j-nn/src/test/java/org/deeplearning4j/TestUtils.java
View File

@ -1,158 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j;
import org.apache.commons.compress.utils.IOUtils;
import org.deeplearning4j.nn.conf.ComputationGraphConfiguration;
import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
import org.deeplearning4j.nn.graph.ComputationGraph;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
import org.deeplearning4j.util.ModelSerializer;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.random.impl.BernoulliDistribution;
import org.nd4j.linalg.factory.Nd4j;
import java.io.*;
import java.util.Random;
import static org.junit.Assert.assertEquals;
public class TestUtils {
public static MultiLayerNetwork testModelSerialization(MultiLayerNetwork net){
MultiLayerNetwork restored;
try {
ByteArrayOutputStream baos = new ByteArrayOutputStream();
ModelSerializer.writeModel(net, baos, true);
byte[] bytes = baos.toByteArray();
ByteArrayInputStream bais = new ByteArrayInputStream(bytes);
restored = ModelSerializer.restoreMultiLayerNetwork(bais, true);
assertEquals(net.getLayerWiseConfigurations(), restored.getLayerWiseConfigurations());
assertEquals(net.params(), restored.params());
} catch (IOException e){
//Should never happen
throw new RuntimeException(e);
}
//Also check the MultiLayerConfiguration is serializable (required by Spark etc)
MultiLayerConfiguration conf = net.getLayerWiseConfigurations();
serializeDeserializeJava(conf);
return restored;
}
public static ComputationGraph testModelSerialization(ComputationGraph net){
ComputationGraph restored;
try {
ByteArrayOutputStream baos = new ByteArrayOutputStream();
ModelSerializer.writeModel(net, baos, true);
byte[] bytes = baos.toByteArray();
ByteArrayInputStream bais = new ByteArrayInputStream(bytes);
restored = ModelSerializer.restoreComputationGraph(bais, true);
assertEquals(net.getConfiguration(), restored.getConfiguration());
assertEquals(net.params(), restored.params());
} catch (IOException e){
//Should never happen
throw new RuntimeException(e);
}
//Also check the ComputationGraphConfiguration is serializable (required by Spark etc)
ComputationGraphConfiguration conf = net.getConfiguration();
serializeDeserializeJava(conf);
return restored;
}
private static <T> T serializeDeserializeJava(T object){
byte[] bytes;
try(ByteArrayOutputStream baos = new ByteArrayOutputStream(); ObjectOutputStream oos = new ObjectOutputStream(baos)){
oos.writeObject(object);
oos.close();
bytes = baos.toByteArray();
} catch (IOException e){
//Should never happen
throw new RuntimeException(e);
}
T out;
try(ObjectInputStream ois = new ObjectInputStream(new ByteArrayInputStream(bytes))){
out = (T)ois.readObject();
} catch (IOException | ClassNotFoundException e){
throw new RuntimeException(e);
}
assertEquals(object, out);
return out;
}
public static INDArray randomOneHot(long examples, long nOut){
return randomOneHot(examples, nOut, new Random(12345));
}
public static INDArray randomOneHot(long examples, long nOut, long rngSeed){
return randomOneHot(examples, nOut, new Random(rngSeed));
}
public static INDArray randomOneHot(long examples, long nOut, Random rng){
INDArray arr = Nd4j.create(examples, nOut);
for( int i=0; i<examples; i++ ){
arr.putScalar(i, rng.nextInt((int) nOut), 1.0);
}
return arr;
}
public static INDArray randomOneHotTimeSeries(int minibatch, int outSize, int tsLength){
return randomOneHotTimeSeries(minibatch, outSize, tsLength, new Random());
}
public static INDArray randomOneHotTimeSeries(int minibatch, int outSize, int tsLength, long rngSeed){
return randomOneHotTimeSeries(minibatch, outSize, tsLength, new Random(rngSeed));
}
public static INDArray randomOneHotTimeSeries(int minibatch, int outSize, int tsLength, Random rng){
INDArray out = Nd4j.create(new int[]{minibatch, outSize, tsLength}, 'f');
for( int i=0; i<minibatch; i++ ){
for( int j=0; j<tsLength; j++ ){
out.putScalar(i, rng.nextInt(outSize), j, 1.0);
}
}
return out;
}
public static INDArray randomBernoulli(int... shape) {
return randomBernoulli(0.5, shape);
}
public static INDArray randomBernoulli(double p, int... shape){
INDArray ret = Nd4j.createUninitialized(shape);
Nd4j.getExecutioner().exec(new BernoulliDistribution(ret, p));
return ret;
}
public static void writeStreamToFile(File out, InputStream is) throws IOException {
byte[] b = IOUtils.toByteArray(is);
try (OutputStream os = new BufferedOutputStream(new FileOutputStream(out))) {
os.write(b);
}
}
}

99
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/pom.xml
View File

@ -1,99 +0,0 @@
<!--~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~ Copyright (c) 2015-2018 Skymind, Inc.
~
~ This program and the accompanying materials are made available under the
~ terms of the Apache License, Version 2.0 which is available at
~ https://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.
~
~ SPDX-License-Identifier: Apache-2.0
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-scaleout</artifactId>
<version>1.0.0-SNAPSHOT</version>
</parent>
<artifactId>deeplearning4j-aws_2.11</artifactId>
<name>DeepLearning4j-AWS</name>
<version>1.0.0-SNAPSHOT</version>
<build>
<plugins>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<configuration>
<source>1.8</source>
<target>1.8</target>
</configuration>
</plugin>
</plugins>
</build>
<properties>
<!-- Default scala versions, may be overwritten by build profiles -->
<scala.version>2.11.12</scala.version>
<scala.binary.version>2.11</scala.binary.version>
</properties>
<dependencies>
<dependency>
<groupId>com.amazonaws</groupId>
<artifactId>aws-java-sdk</artifactId>
<version>1.11.24</version>
</dependency>
<dependency>
<groupId>args4j</groupId>
<artifactId>args4j</artifactId>
<version>2.32</version>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
</dependency>
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>nd4j-api</artifactId>
<version>${nd4j.version}</version>
</dependency>
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-util</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>com.jcraft</groupId>
<artifactId>jsch</artifactId>
<version>${jsch.version}</version>
</dependency>
<dependency>
<groupId>org.threadly</groupId>
<artifactId>threadly</artifactId>
<version>${threadly.version}</version>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-lang3</artifactId>
<version>${commons-lang3.version}</version>
</dependency>
</dependencies>
<profiles>
<profile>
<id>test-nd4j-native</id>
</profile>
<profile>
<id>test-nd4j-cuda-10.2</id>
</profile>
</profiles>
</project>

34
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/src/main/java/org/deeplearning4j/aws/dataset/DataSetLoader.java
View File

@ -1,34 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.dataset;
import org.deeplearning4j.aws.s3.reader.S3Downloader;
import java.io.InputStream;
public class DataSetLoader {
private String bucket;
public void onData(InputStream is) {
S3Downloader downloader = new S3Downloader();
}
}

222
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/src/main/java/org/deeplearning4j/aws/ec2/Ec2BoxCreator.java
View File

@ -1,222 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.ec2;
import com.amazonaws.regions.Regions;
import com.amazonaws.services.ec2.AmazonEC2;
import com.amazonaws.services.ec2.model.*;
import org.deeplearning4j.aws.s3.BaseS3;
import org.deeplearning4j.util.ThreadUtils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
/**
* Creates Ec2Boxes
* @author Adam Gibson
*
*/
public class Ec2BoxCreator extends BaseS3 {
private String amiId;
private int numBoxes;
private String size;
private List<String> boxesCreated;
private String securityGroupId;
private String keyPair;
private Regions regions = Regions.DEFAULT_REGION;
private static final Logger log = LoggerFactory.getLogger(Ec2BoxCreator.class);
//centos
public final static String DEFAULT_AMI = "ami-8997afe0";
/**
*
* @param numBoxes number of boxes
* @param size the size of the instances
*/
public Ec2BoxCreator(int numBoxes, String size, String securityGroupId, String keyPair) {
this(DEFAULT_AMI, numBoxes, size, securityGroupId, keyPair);
}
/**
*
* @param amiId amazon image id
* @param numBoxes number of boxes
* @param size the size of the instances
* @param securityGroupId
*/
public Ec2BoxCreator(String amiId, int numBoxes, String size, String securityGroupId, String keyPair) {
super();
this.amiId = amiId;
this.numBoxes = numBoxes;
this.size = size;
this.keyPair = keyPair;
this.securityGroupId = securityGroupId;
}
public void createSpot() {
// Initializes a Spot Instance Request
RequestSpotInstancesRequest requestRequest = new RequestSpotInstancesRequest();
// Request 1 x t1.micro instance with a bid price of $0.03.
requestRequest.setSpotPrice("0.03");
requestRequest.setInstanceCount(Integer.valueOf(1));
// Setup the specifications of the launch. This includes the
// instance type (e.g. t1.micro) and the latest Amazon Linux
// AMI id available. Note, you should always use the latest
// Amazon Linux AMI id or another of your choosing.
LaunchSpecification launchSpecification = new LaunchSpecification();
launchSpecification.setImageId("ami-8c1fece5");
launchSpecification.setInstanceType("t1.micro");
// Add the security group to the request.
List<String> securityGroups = new ArrayList<>();
securityGroups.add("GettingStartedGroup");
launchSpecification.setSecurityGroups(securityGroups);
// Add the launch specifications to the request.
requestRequest.setLaunchSpecification(launchSpecification);
// Call the RequestSpotInstance API.
RequestSpotInstancesResult requestResult = getEc2().requestSpotInstances(requestRequest);
List<SpotInstanceRequest> requestResponses = requestResult.getSpotInstanceRequests();
// Setup an arraylist to collect all of the request ids we want to
// watch hit the running state.
List<String> spotInstanceRequestIds = new ArrayList<>();
// Add all of the request ids to the hashset, so we can determine when they hit the
// active state.
for (SpotInstanceRequest requestResponse : requestResponses) {
System.out.println("Created Spot Request: " + requestResponse.getSpotInstanceRequestId());
spotInstanceRequestIds.add(requestResponse.getSpotInstanceRequestId());
}
}
public void setRegion(Regions regions) {
this.regions = regions;
}
/**
* Create the instances
*/
public void create() {
RunInstancesRequest runInstancesRequest =
new RunInstancesRequest().withImageId(amiId).withInstanceType(size).withKeyName(keyPair)
.withMinCount(1).withSecurityGroupIds(securityGroupId).withMaxCount(numBoxes);
AmazonEC2 ec2 = getEc2();
ec2.setRegion(com.amazonaws.regions.Region.getRegion(regions));
List<Instance> boxes = ec2.runInstances(runInstancesRequest).getReservation().getInstances();
if (boxesCreated == null) {
boxesCreated = new ArrayList<>();
for (Instance i : boxes)
boxesCreated.add(i.getInstanceId());
log.info("Boxes created " + boxesCreated);
} else {
blowupBoxes();
boxesCreated.clear();
for (Instance i : boxes)
boxesCreated.add(i.getInstanceId());
}
}
public List<InstanceStateChange> blowupBoxes() {
TerminateInstancesRequest request = new TerminateInstancesRequest().withInstanceIds(boxesCreated);
if (boxesCreated != null) {
TerminateInstancesResult result = getEc2().terminateInstances(request);
List<InstanceStateChange> change = result.getTerminatingInstances();
log.info("Boxes destroyed " + boxesCreated);
return change;
}
return Collections.emptyList();
}
public void blockTillAllRunning() {
while (!allRunning()) {
ThreadUtils.uncheckedSleep(1000);
log.info("Not all created...");
}
}
public boolean allRunning() {
if (boxesCreated == null)
return false;
else {
DescribeInstancesResult result = getEc2().describeInstances();
List<Reservation> reservations = result.getReservations();
for (Reservation r : reservations) {
List<Instance> instances = r.getInstances();
for (Instance instance : instances) {
InstanceState state = instance.getState();
if (state.getCode() == 48)
continue;
if (state.getCode() != 16)
return false;
}
}
return true;
}
}
public List<String> getHosts() {
DescribeInstancesResult result = getEc2().describeInstances();
List<String> hosts = new ArrayList<>();
List<Reservation> reservations = result.getReservations();
for (Reservation r : reservations) {
List<Instance> instances = r.getInstances();
for (Instance instance : instances) {
InstanceState state = instance.getState();
if (state.getCode() == 48)
continue;
hosts.add(instance.getPublicDnsName());
}
}
return hosts;
}
public List<String> getBoxesCreated() {
return boxesCreated;
}
}

122
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/src/main/java/org/deeplearning4j/aws/ec2/provision/ClusterSetup.java
View File

@ -1,122 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.ec2.provision;
import com.amazonaws.regions.Regions;
import org.deeplearning4j.aws.ec2.Ec2BoxCreator;
import org.kohsuke.args4j.CmdLineException;
import org.kohsuke.args4j.CmdLineParser;
import org.kohsuke.args4j.Option;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.threadly.concurrent.PriorityScheduler;
import java.util.List;
/**
* Sets up a DL4J cluster
* @author Adam Gibson
*
*/
public class ClusterSetup {
@Option(name = "-w", usage = "Number of workers")
private int numWorkers = 1;
@Option(name = "-ami", usage = "Amazon machine image: default, amazon linux (only works with RHEL right now")
private String ami = "ami-fb8e9292";
@Option(name = "-s", usage = "size of instance: default m1.medium")
private String size = "m3.xlarge";
@Option(name = "-sg", usage = "security group, this needs to be applyTransformToDestination")
private String securityGroupName;
@Option(name = "-kp", usage = "key pair name, also needs to be applyTransformToDestination.")
private String keyPairName;
@Option(name = "-kpath",
usage = "path to private key - needs to be applyTransformToDestination, this is used to login to amazon.")
private String pathToPrivateKey;
@Option(name = "-wscript", usage = "path to worker script to run, this will allow customization of dependencies")
private String workerSetupScriptPath;
@Option(name = "-mscript", usage = "path to master script to run this will allow customization of the dependencies")
private String masterSetupScriptPath;
@Option(name = "-region", usage = "specify a region")
private String region = Regions.US_EAST_1.getName();
private PriorityScheduler as;
private static final Logger log = LoggerFactory.getLogger(ClusterSetup.class);
public ClusterSetup(String[] args) {
CmdLineParser parser = new CmdLineParser(this);
try {
parser.parseArgument(args);
} catch (CmdLineException e) {
parser.printUsage(System.err);
log.error("Unable to parse args", e);
}
}
public void exec() {
//master + workers
Ec2BoxCreator boxCreator = new Ec2BoxCreator(ami, numWorkers, size, securityGroupName, keyPairName);
boxCreator.setRegion(Regions.fromName(region));
boxCreator.create();
boxCreator.blockTillAllRunning();
List<String> hosts = boxCreator.getHosts();
//provisionMaster(hosts.get(0));
provisionWorkers(hosts);
}
private void provisionWorkers(List<String> workers) {
as = new PriorityScheduler(Runtime.getRuntime().availableProcessors());
for (final String workerHost : workers) {
try {
as.execute(new Runnable() {
@Override
public void run() {
HostProvisioner uploader = new HostProvisioner(workerHost, "ec2-user");
try {
uploader.addKeyFile(pathToPrivateKey);
//uploader.runRemoteCommand("sudo hostname " + workerHost);
uploader.uploadAndRun(workerSetupScriptPath, "");
} catch (Exception e) {
e.printStackTrace();
}
}
});
} catch (Exception e) {
log.error("Error ", e);
}
}
}
/**
* @param args
*/
public static void main(String[] args) {
new ClusterSetup(args).exec();
}
}

31
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@ -1,31 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.ec2.provision;
public class DistributedDeepLearningTrainer {
private DistributedDeepLearningTrainer() {}
/**
* @param args
*/
public static void main(String[] args) {
ClusterSetup clusterSet = new ClusterSetup(args);
}
}

311
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@ -1,311 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.ec2.provision;
import com.jcraft.jsch.*;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.BufferedInputStream;
import java.io.File;
import java.io.FileInputStream;
import java.io.InputStream;
import java.util.Arrays;
import java.util.Collection;
/**
* Meant for uploading files to remote servers
* @author Adam Gibson
*
*/
public class HostProvisioner implements UserInfo {
private String host;
private JSch jsch;
private String user;
private int port = 22;
private String password;
private static final Logger log = LoggerFactory.getLogger(HostProvisioner.class);
/**
*
* @param host host to connect to (public facing dns)
* @param user the user to connect with (default root otherwise)
* @param password the password to use if any
* @param port the port to connect to(default 22)
*/
public HostProvisioner(String host, String user, String password, int port) {
super();
this.host = host;
this.user = user;
this.port = port;
this.password = password;
jsch = new JSch();
}
/**
* Connects to port 22
* @param host host to connect to (public facing dns)
* @param user the user to connect with (default root otherwise)
* @param password the password to use if any
*/
public HostProvisioner(String host, String user, String password) {
this(host, user, password, 22);
}
/**
* Connects to port 22
* @param host host to connect to (public facing dns)
* @param user the user to connect with (default root otherwise)
*/
public HostProvisioner(String host, String user) {
this(host, user, "", 22);
}
/**
* Connects to port 22, user root, with no password
* @param host host to connect to (public facing dns)
*/
public HostProvisioner(String host) {
this(host, "root", "", 22);
}
public void uploadAndRun(String script, String rootDir) throws Exception {
String remoteName = rootDir.isEmpty() ? new File(script).getName() : rootDir + "/" + new File(script).getName();
upload(new File(script), remoteName);
String remoteCommand = remoteName.charAt(0) != '/' ? "./" + remoteName : remoteName;
remoteCommand = "chmod +x " + remoteCommand + " && " + remoteCommand;
runRemoteCommand(remoteCommand);
}
public void runRemoteCommand(String remoteCommand) throws Exception {
Session session = getSession();
session.connect();
ChannelExec channel = (ChannelExec) session.openChannel("exec");
channel.setCommand(remoteCommand);
channel.setErrStream(System.err);
channel.setPty(true);
channel.setOutputStream(System.out);
channel.connect();
channel.start();
InputStream input = channel.getInputStream();
//start reading the input from the executed commands on the shell
byte[] tmp = new byte[60000];
while (true) {
while (input.available() > 0) {
int i = input.read(tmp, 0, tmp.length);
if (i < 0)
break;
log.info(new String(tmp, 0, i));
}
if (channel.isClosed()) {
log.info("exit-status: " + channel.getExitStatus());
break;
}
}
channel.disconnect();
session.disconnect();
}
private Session getSession() throws Exception {
Session session = jsch.getSession(user, host, port);
session.setUserInfo(this);
return session;
}
/**
* Creates the directory for the file if necessary
* and uploads the file
* @param from the directory to upload from
* @param to the destination directory on the remote server
* @throws Exception
*/
public void uploadForDeployment(String from, String to) throws Exception {
File fromFile = new File(from);
if (!to.isEmpty() && fromFile.isDirectory())
mkDir(to);
else
upload(from, to);
}
public void addKeyFile(String keyFile) throws Exception {
jsch.addIdentity(keyFile);
}
//creates the directory to upload to
private void mkDir(String dir) throws Exception {
Session session = getSession();
session.connect();
Channel channel = session.openChannel("sftp");
channel.connect();
ChannelSftp c = (ChannelSftp) channel;
if (!fileExists(dir, c))
c.mkdir(dir);
c.exit();
session.disconnect();
}
private boolean fileExists(String dir, ChannelSftp channel) {
try {
channel.stat(dir);
return true;
} catch (Exception e) {
return false;
}
}
//uploads the file or listed files in a directory
private void upload(String fileOrDir, String uploadRootDir) throws Exception {
if (uploadRootDir.isEmpty())
uploadRootDir = ".";
File origin = new File(fileOrDir);
if (fileOrDir.endsWith(".tar") || fileOrDir.endsWith(".tar.gz")) {
upload(new File(fileOrDir), uploadRootDir);
untar(uploadRootDir);
} else if (origin.isFile()) {
upload(new File(fileOrDir), uploadRootDir);
} else {
File[] childFiles = origin.listFiles();
if (childFiles != null)
upload(Arrays.asList(childFiles), uploadRootDir);
}
}
private void untar(String targetRemoteFile) throws Exception {
this.runRemoteCommand("tar xvf " + targetRemoteFile);
}
private void upload(Collection<File> files, String rootDir) throws Exception {
Session session = getSession();
session.connect();
Channel channel = session.openChannel("sftp");
channel.connect();
ChannelSftp c = (ChannelSftp) channel;
for (File f : files) {
if (f.isDirectory()) {
log.warn("Skipping " + f.getName());
continue;
}
log.info("Uploading " + f.getName());
BufferedInputStream bis = new BufferedInputStream(new FileInputStream(f));
c.put(bis, rootDir + "/" + f.getName());
bis.close();
}
channel.disconnect();
session.disconnect();
}
private void upload(File f, String remoteFile) throws Exception {
Session session = getSession();
int numRetries = 0;
while (numRetries < 3 && !session.isConnected()) {
try {
session.connect();
} catch (Exception e) {
numRetries++;
}
}
try {
Channel channel = session.openChannel("sftp");
channel.connect();
ChannelSftp c = (ChannelSftp) channel;
BufferedInputStream bis = new BufferedInputStream(new FileInputStream(f));
if (this.fileExists(remoteFile, c))
if (f.isDirectory())
c.rmdir(remoteFile);
else
c.rm(remoteFile);
c.put(bis, remoteFile);
bis.close();
c.exit();
session.disconnect();
} catch (Exception e) {
log.info("Session was down...trying again", e);
upload(f, remoteFile);
}
}
@Override
public String getPassphrase() {
return this.password;
}
@Override
public String getPassword() {
return this.password;
}
@Override
public boolean promptPassphrase(String arg0) {
return true;
}
@Override
public boolean promptPassword(String arg0) {
return true;
}
@Override
public boolean promptYesNo(String arg0) {
return true;
}
@Override
public void showMessage(String arg0) {
log.info(arg0);
}
}

47
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@ -1,47 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.emr;
import com.amazonaws.services.elasticmapreduce.model.Configuration;
import lombok.*;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
@Data
@AllArgsConstructor(access = AccessLevel.PRIVATE)
@NoArgsConstructor
@Builder
public class EmrConfig {
protected String classification;
protected Map<String, String> properties;
protected List<EmrConfig> configs;
Configuration toAwsConfig() {
Configuration config = new Configuration().withClassification(classification).withProperties(properties);
List<Configuration> subConfigs = new ArrayList<>();
for (EmrConfig conf : configs){
subConfigs.add(conf.toAwsConfig());
}
return config.withConfigurations(subConfigs);
}
}

531
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@ -1,531 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.emr;
import com.amazonaws.services.elasticmapreduce.AmazonElasticMapReduce;
import com.amazonaws.services.elasticmapreduce.AmazonElasticMapReduceClientBuilder;
import com.amazonaws.services.elasticmapreduce.model.*;
import com.amazonaws.services.s3.AmazonS3ClientBuilder;
import com.amazonaws.services.s3.AmazonS3URI;
import com.amazonaws.services.s3.model.PutObjectRequest;
import lombok.AccessLevel;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.RandomStringUtils;
import org.nd4j.linalg.function.Function;
import java.io.File;
import java.util.*;
/**
* Configuration for a Spark EMR cluster
*/
@Data
@AllArgsConstructor(access = AccessLevel.PRIVATE)
@NoArgsConstructor
@Slf4j
public class SparkEMRClient {
protected String sparkClusterName = RandomStringUtils.randomAlphanumeric(12);
protected String sparkAwsRegion = "us-east-1";
protected String sparkEmrRelease = "emr-5.9.0";
protected String sparkEmrServiceRole = "EMR_DefaultRole";
protected List<EmrConfig> sparkEmrConfigs = Collections.emptyList();
protected String sparkSubnetId = null;
protected List<String> sparkSecurityGroupIds = Collections.emptyList();
protected int sparkInstanceCount = 1;
protected String sparkInstanceType = "m3.xlarge";
protected Optional<Float> sparkInstanceBidPrice = Optional.empty();
protected String sparkInstanceRole = "EMR_EC2_DefaultRole";
protected String sparkS3JarFolder = "changeme";
protected int sparkTimeoutDurationMinutes = 90;
//underlying configs
protected AmazonElasticMapReduceClientBuilder sparkEmrClientBuilder;
protected AmazonS3ClientBuilder sparkS3ClientBuilder;
protected JobFlowInstancesConfig sparkJobFlowInstancesConfig;
protected RunJobFlowRequest sparkRunJobFlowRequest;
protected Function<PutObjectRequest, PutObjectRequest> sparkS3PutObjectDecorator;
protected Map<String, String> sparkSubmitConfs;
private static ClusterState[] activeClusterStates = new ClusterState[]{
ClusterState.RUNNING,
ClusterState.STARTING,
ClusterState.WAITING,
ClusterState.BOOTSTRAPPING};
private Optional<ClusterSummary> findClusterWithName(AmazonElasticMapReduce emr, String name) {
List<ClusterSummary> csrl = emr.listClusters((new ListClustersRequest()).withClusterStates(activeClusterStates)).getClusters();
for (ClusterSummary csr : csrl) {
if (csr.getName().equals(name)) return Optional.of(csr);
}
return Optional.empty();
}
/**
* Creates the current cluster
*/
public void createCluster() {
AmazonElasticMapReduce emr = sparkEmrClientBuilder.build();
Optional<ClusterSummary> csr = findClusterWithName(emr, sparkClusterName);
if (csr.isPresent()) {
String msg = String.format("A cluster with name %s and id %s is already deployed", sparkClusterName, csr.get().getId());
log.error(msg);
throw new IllegalStateException(msg);
} else {
RunJobFlowResult res = emr.runJobFlow(sparkRunJobFlowRequest);
String msg = String.format("Your cluster is launched with name %s and id %s.", sparkClusterName, res.getJobFlowId());
log.info(msg);
}
}
private void logClusters(List<ClusterSummary> csrl) {
if (csrl.isEmpty()) log.info("No cluster found.");
else {
log.info(String.format("%d clusters found.", csrl.size()));
for (ClusterSummary csr : csrl) {
log.info(String.format("Name: %s | Id: %s", csr.getName(), csr.getId()));
}
}
}
/**
* Lists existing active clusters Names
*
* @return cluster names
*/
public List<String> listActiveClusterNames() {
AmazonElasticMapReduce emr = sparkEmrClientBuilder.build();
List<ClusterSummary> csrl =
emr.listClusters(new ListClustersRequest().withClusterStates(activeClusterStates)).getClusters();
logClusters(csrl);
List<String> res = new ArrayList<>(csrl.size());
for (ClusterSummary csr : csrl) res.add(csr.getName());
return res;
}
/**
* List existing active cluster IDs
*
* @return cluster IDs
*/
public List<String> listActiveClusterIds() {
AmazonElasticMapReduce emr = sparkEmrClientBuilder.build();
List<ClusterSummary> csrl =
emr.listClusters(new ListClustersRequest().withClusterStates(activeClusterStates)).getClusters();
logClusters(csrl);
List<String> res = new ArrayList<>(csrl.size());
for (ClusterSummary csr : csrl) res.add(csr.getId());
return res;
}
/**
* Terminates a cluster
*/
public void terminateCluster() {
AmazonElasticMapReduce emr = sparkEmrClientBuilder.build();
Optional<ClusterSummary> optClusterSum = findClusterWithName(emr, sparkClusterName);
if (!optClusterSum.isPresent()) {
log.error(String.format("The cluster with name %s , requested for deletion, does not exist.", sparkClusterName));
} else {
String id = optClusterSum.get().getId();
emr.terminateJobFlows((new TerminateJobFlowsRequest()).withJobFlowIds(id));
log.info(String.format("The cluster with id %s is terminating.", id));
}
}
// The actual job-sumission logic
private void submitJob(AmazonElasticMapReduce emr, String mainClass, List<String> args, Map<String, String> sparkConfs, File uberJar) throws Exception {
AmazonS3URI s3Jar = new AmazonS3URI(sparkS3JarFolder + "/" + uberJar.getName());
log.info(String.format("Placing uberJar %s to %s", uberJar.getPath(), s3Jar.toString()));
PutObjectRequest putRequest = sparkS3PutObjectDecorator.apply(
new PutObjectRequest(s3Jar.getBucket(), s3Jar.getKey(), uberJar)
);
sparkS3ClientBuilder.build().putObject(putRequest);
// The order of these matters
List<String> sparkSubmitArgs = Arrays.asList(
"spark-submit",
"--deploy-mode",
"cluster",
"--class",
mainClass
);
for (Map.Entry<String, String> e : sparkConfs.entrySet()) {
sparkSubmitArgs.add(String.format("--conf %s = %s ", e.getKey(), e.getValue()));
}
sparkSubmitArgs.add(s3Jar.toString());
sparkSubmitArgs.addAll(args);
StepConfig step = new StepConfig()
.withActionOnFailure(ActionOnFailure.CONTINUE)
.withName("Spark step")
.withHadoopJarStep(
new HadoopJarStepConfig()
.withJar("command-runner.jar")
.withArgs(sparkSubmitArgs)
);
Optional<ClusterSummary> optCsr = findClusterWithName(emr, sparkClusterName);
if (optCsr.isPresent()) {
ClusterSummary csr = optCsr.get();
emr.addJobFlowSteps(
new AddJobFlowStepsRequest()
.withJobFlowId(csr.getId())
.withSteps(step));
log.info(
String.format("Your job is added to the cluster with id %s.", csr.getId())
);
} else {
// If the cluster wasn't started, it's assumed ot be throwaway
List<StepConfig> steps = sparkRunJobFlowRequest.getSteps();
steps.add(step);
RunJobFlowRequest jobFlowRequest = sparkRunJobFlowRequest
.withSteps(steps)
.withInstances(sparkJobFlowInstancesConfig.withKeepJobFlowAliveWhenNoSteps(false));
RunJobFlowResult res = emr.runJobFlow(jobFlowRequest);
log.info("Your new cluster's id is %s.", res.getJobFlowId());
}
}
/**
* Submit a Spark Job with a specified main class
*/
public void sparkSubmitJobWithMain(String[] args, String mainClass, File uberJar) throws Exception {
AmazonElasticMapReduce emr = sparkEmrClientBuilder.build();
submitJob(emr, mainClass, Arrays.asList(args), sparkSubmitConfs, uberJar);
}
private void checkStatus(AmazonElasticMapReduce emr, String clusterId) throws InterruptedException {
log.info(".");
com.amazonaws.services.elasticmapreduce.model.Cluster dcr =
emr.describeCluster((new DescribeClusterRequest()).withClusterId(clusterId)).getCluster();
String state = dcr.getStatus().getState();
long timeOutTime = System.currentTimeMillis() + ((long) sparkTimeoutDurationMinutes * 60 * 1000);
Boolean activated = Arrays.asList(activeClusterStates).contains(ClusterState.fromValue(state));
Boolean timedOut = System.currentTimeMillis() > timeOutTime;
if (activated && timedOut) {
emr.terminateJobFlows(
new TerminateJobFlowsRequest().withJobFlowIds(clusterId)
);
log.error("Timeout. Cluster terminated.");
} else if (!activated) {
Boolean hasAbnormalStep = false;
StepSummary stepS = null;
List<StepSummary> steps = emr.listSteps(new ListStepsRequest().withClusterId(clusterId)).getSteps();
for (StepSummary step : steps) {
if (step.getStatus().getState() != StepState.COMPLETED.toString()) {
hasAbnormalStep = true;
stepS = step;
}
}
if (hasAbnormalStep && stepS != null)
log.error(String.format("Cluster %s terminated with an abnormal step, name %s, id %s", clusterId, stepS.getName(), stepS.getId()));
else
log.info("Cluster %s terminated without error.", clusterId);
} else {
Thread.sleep(5000);
checkStatus(emr, clusterId);
}
}
/**
* Monitor the cluster and terminates when it times out
*/
public void sparkMonitor() throws InterruptedException {
AmazonElasticMapReduce emr = sparkEmrClientBuilder.build();
Optional<ClusterSummary> optCsr = findClusterWithName(emr, sparkClusterName);
if (!optCsr.isPresent()) {
log.error(String.format("The cluster with name %s does not exist.", sparkClusterName));
} else {
ClusterSummary csr = optCsr.get();
log.info(String.format("found cluster with id %s, starting monitoring", csr.getId()));
checkStatus(emr, csr.getId());
}
}
@Data
public static class Builder {
protected String sparkClusterName = RandomStringUtils.randomAlphanumeric(12);
protected String sparkAwsRegion = "us-east-1";
protected String sparkEmrRelease = "emr-5.9.0";
protected String sparkEmrServiceRole = "EMR_DefaultRole";
protected List<EmrConfig> sparkEmrConfigs = Collections.emptyList();
protected String sparkSubNetid = null;
protected List<String> sparkSecurityGroupIds = Collections.emptyList();
protected int sparkInstanceCount = 1;
protected String sparkInstanceType = "m3.xlarge";
protected Optional<Float> sparkInstanceBidPrice = Optional.empty();
protected String sparkInstanceRole = "EMR_EC2_DefaultRole";
protected String sparkS3JarFolder = "changeme";
protected int sparkTimeoutDurationMinutes = 90;
protected AmazonElasticMapReduceClientBuilder sparkEmrClientBuilder;
protected AmazonS3ClientBuilder sparkS3ClientBuilder;
protected JobFlowInstancesConfig sparkJobFlowInstancesConfig;
protected RunJobFlowRequest sparkRunJobFlowRequest;
// This should allow the user to decorate the put call to add metadata to the jar put command, such as security groups,
protected Function<PutObjectRequest, PutObjectRequest> sparkS3PutObjectDecorator = new Function<PutObjectRequest, PutObjectRequest>() {
@Override
public PutObjectRequest apply(PutObjectRequest putObjectRequest) {
return putObjectRequest;
}
};
protected Map<String, String> sparkSubmitConfs;
/**
* Defines the EMR cluster's name
*
* @param clusterName the EMR cluster's name
* @return an EMR cluster builder
*/
public Builder clusterName(String clusterName) {
this.sparkClusterName = clusterName;
return this;
}
/**
* Defines the EMR cluster's region
* See https://docs.aws.amazon.com/general/latest/gr/rande.html
*
* @param region the EMR cluster's region
* @return an EMR cluster builder
*/
public Builder awsRegion(String region) {
this.sparkAwsRegion = region;
return this;
}
/**
* Defines the EMR release version to be used in this cluster
* uses a release label
* See https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-4.2.0/emr-release-differences.html#emr-release-label
*
* @param releaseLabel the EMR release label
* @return an EM cluster Builder
*/
public Builder emrRelease(String releaseLabel) {
this.sparkEmrRelease = releaseLabel;
return this;
}
/**
* Defines the IAM role to be assumed by the EMR service
* <p>
* https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create_for-service.html
*
* @param serviceRole the service role
* @return an EM cluster Builder
*/
public Builder emrServiceRole(String serviceRole) {
this.sparkEmrServiceRole = serviceRole;
return this;
}
/**
* A list of configuration parameters to apply to EMR instances.
*
* @param configs the EMR configurations to apply to this cluster
* @return an EMR cluster builder
*/
public Builder emrConfigs(List<EmrConfig> configs) {
this.sparkEmrConfigs = configs;
return this;
}
/**
* The id of the EC2 subnet to be used for this Spark EMR service
* see https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Subnets.html
*
* @param id the subnet ID
* @return an EMR cluster builder
*/
public Builder subnetId(String id) {
this.sparkSubNetid = id;
return this;
}
/**
* The id of additional security groups this deployment should adopt for both master and slaves
*
* @param securityGroups
* @return an EMR cluster builder
*/
public Builder securityGroupIDs(List<String> securityGroups) {
this.sparkSecurityGroupIds = securityGroups;
return this;
}
/**
* The number of instances this deployment should comprise of
*
* @param count the number of instances for this cluster
* @rturn an EMR cluster buidler
*/
public Builder instanceCount(int count) {
this.sparkInstanceCount = count;
return this;
}
/**
* The type of instance this cluster should comprise of
* See https://aws.amazon.com/ec2/instance-types/
*
* @param instanceType the type of instance for this cluster
* @return an EMR cluster builder
*/
public Builder instanceType(String instanceType) {
this.sparkInstanceType = instanceType;
return this;
}
/**
* The optional bid value for this cluster's spot instances
* see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/how-spot-instances-work.html
* Uses the on-demand market if empty.
*
* @param optBid the Optional bid price for this cluster's instnces
* @return an EMR cluster Builder
*/
public Builder instanceBidPrice(Optional<Float> optBid) {
this.sparkInstanceBidPrice = optBid;
return this;
}
/**
* The EC2 instance role that this cluster's instances should assume
* see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/iam-roles-for-amazon-ec2.html
*
* @param role the intended instance role
* @return an EMR cluster builder
*/
public Builder instanceRole(String role) {
this.sparkInstanceRole = role;
return this;
}
/**
* the S3 folder in which to find the application jar
*
* @param jarfolder the S3 folder in which to find a jar
* @return an EMR cluster builder
*/
public Builder s3JarFolder(String jarfolder) {
this.sparkS3JarFolder = jarfolder;
return this;
}
/**
* The timeout duration for this Spark EMR cluster, in minutes
*
* @param timeoutMinutes
* @return an EMR cluster builder
*/
public Builder sparkTimeOutDurationMinutes(int timeoutMinutes) {
this.sparkTimeoutDurationMinutes = timeoutMinutes;
return this;
}
/**
* Creates an EMR Spark cluster deployment
*
* @return a SparkEMRClient
*/
public SparkEMRClient build() {
this.sparkEmrClientBuilder = AmazonElasticMapReduceClientBuilder.standard().withRegion(sparkAwsRegion);
this.sparkS3ClientBuilder = AmazonS3ClientBuilder.standard().withRegion(sparkAwsRegion);
// note this will be kept alive without steps, an arbitrary choice to avoid rapid test-teardown-restart cycles
this.sparkJobFlowInstancesConfig = (new JobFlowInstancesConfig()).withKeepJobFlowAliveWhenNoSteps(true);
if (this.sparkSubNetid != null)
this.sparkJobFlowInstancesConfig = this.sparkJobFlowInstancesConfig.withEc2SubnetId(this.sparkSubNetid);
if (!this.sparkSecurityGroupIds.isEmpty()) {
this.sparkJobFlowInstancesConfig = this.sparkJobFlowInstancesConfig.withAdditionalMasterSecurityGroups(this.sparkSecurityGroupIds);
this.sparkJobFlowInstancesConfig = this.sparkJobFlowInstancesConfig.withAdditionalSlaveSecurityGroups(this.sparkSecurityGroupIds);
}
InstanceGroupConfig masterConfig =
(new InstanceGroupConfig()).withInstanceCount(1).withInstanceRole(InstanceRoleType.MASTER).withInstanceType(sparkInstanceType);
if (sparkInstanceBidPrice.isPresent()) {
masterConfig = masterConfig.withMarket(MarketType.SPOT).withBidPrice(sparkInstanceBidPrice.get().toString());
} else {
masterConfig = masterConfig.withMarket(MarketType.ON_DEMAND);
}
int slaveCount = sparkInstanceCount - 1;
InstanceGroupConfig slaveConfig =
(new InstanceGroupConfig()).withInstanceCount(slaveCount).withInstanceRole(InstanceRoleType.CORE).withInstanceRole(sparkInstanceType);
if (sparkInstanceBidPrice.isPresent()) {
slaveConfig = slaveConfig.withMarket(MarketType.SPOT).withBidPrice(sparkInstanceBidPrice.get().toString());
} else {
slaveConfig = slaveConfig.withMarket(MarketType.ON_DEMAND);
}
if (slaveCount > 0) {
this.sparkJobFlowInstancesConfig = this.sparkJobFlowInstancesConfig.withInstanceGroups(Arrays.asList(masterConfig, slaveConfig));
} else {
this.sparkJobFlowInstancesConfig = this.sparkJobFlowInstancesConfig.withInstanceGroups(slaveConfig);
}
this.sparkRunJobFlowRequest = new RunJobFlowRequest();
if (!sparkEmrConfigs.isEmpty()) {
List<Configuration> emrConfigs = new ArrayList<>();
for (EmrConfig config : sparkEmrConfigs) {
emrConfigs.add(config.toAwsConfig());
}
this.sparkRunJobFlowRequest = this.sparkRunJobFlowRequest.withConfigurations(emrConfigs);
}
this.sparkRunJobFlowRequest =
this.sparkRunJobFlowRequest.withName(sparkClusterName).withApplications((new Application()).withName("Spark"))
.withReleaseLabel(sparkEmrRelease)
.withServiceRole(sparkEmrServiceRole)
.withJobFlowRole(sparkInstanceRole)
.withInstances(this.sparkJobFlowInstancesConfig);
return new SparkEMRClient(
this.sparkClusterName,
this.sparkAwsRegion,
this.sparkEmrRelease,
this.sparkEmrServiceRole,
this.sparkEmrConfigs,
this.sparkSubNetid,
this.sparkSecurityGroupIds,
this.sparkInstanceCount,
this.sparkInstanceType,
this.sparkInstanceBidPrice,
this.sparkInstanceRole,
this.sparkS3JarFolder,
this.sparkTimeoutDurationMinutes,
this.sparkEmrClientBuilder,
this.sparkS3ClientBuilder,
this.sparkJobFlowInstancesConfig,
this.sparkRunJobFlowRequest,
this.sparkS3PutObjectDecorator,
this.sparkSubmitConfs
);
}
}
}

117
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/src/main/java/org/deeplearning4j/aws/s3/BaseS3.java
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@ -1,117 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.s3;
import com.amazonaws.auth.AWSCredentials;
import com.amazonaws.auth.BasicAWSCredentials;
import com.amazonaws.auth.PropertiesCredentials;
import com.amazonaws.services.ec2.AmazonEC2;
import com.amazonaws.services.ec2.AmazonEC2Client;
import com.amazonaws.services.s3.AmazonS3;
import com.amazonaws.services.s3.AmazonS3Client;
import java.io.File;
import java.io.InputStream;
/**
* The S3 Credentials works via discovering the credentials
* from the system properties (passed in via -D or System wide)
* If you invoke the JVM with -Dorg.deeplearning4j.aws.accessKey=YOUR_ACCESS_KEY
* and -Dorg.deeplearning4j.aws.accessSecret=YOUR_SECRET_KEY
* this will pick up the credentials from there, otherwise it will also attempt to look in
* the system environment for the following variables:
*
*
* AWS_ACCESS_KEY_ID
* AWS_SECRET_ACCESS_KEY
* @author Adam Gibson
*
*/
public abstract class BaseS3 {
/**
*
*/
protected static final long serialVersionUID = -2280107690193651289L;
protected String accessKey;
protected String secretKey;
protected AWSCredentials creds;
public final static String ACCESS_KEY = "org.deeplearning4j.aws.accessKey";
public final static String ACCESS_SECRET = "org.deeplearning4j.aws.accessSecret";
public final static String AWS_ACCESS_KEY = "AWS_ACCESS_KEY"; //"AWS_ACCESS_KEY_ID";
public final static String AWS_SECRET_KEY = "AWS_SECRET_KEY"; //"AWS_SECRET_ACCESS_KEY";
protected void findCreds() {
if (System.getProperty(ACCESS_KEY) != null && System.getProperty(ACCESS_SECRET) != null) {
accessKey = System.getProperty(ACCESS_KEY);
secretKey = System.getProperty(ACCESS_SECRET);
}
else if (System.getenv(AWS_ACCESS_KEY) != null && System.getenv(AWS_SECRET_KEY) != null) {
accessKey = System.getenv(AWS_ACCESS_KEY);
secretKey = System.getenv(AWS_SECRET_KEY);
}
}
public BaseS3() {
findCreds();
if (accessKey != null && secretKey != null)
creds = new BasicAWSCredentials(accessKey, secretKey);
if (creds == null)
throw new IllegalStateException("Unable to find ec2 credentials");
}
public BaseS3(File file) throws Exception {
if (accessKey != null && secretKey != null)
creds = new BasicAWSCredentials(accessKey, secretKey);
else
creds = new PropertiesCredentials(file);
}
public BaseS3(InputStream is) throws Exception {
if (accessKey != null && secretKey != null)
creds = new BasicAWSCredentials(accessKey, secretKey);
else
creds = new PropertiesCredentials(is);
}
public AWSCredentials getCreds() {
return creds;
}
public void setCreds(AWSCredentials creds) {
this.creds = creds;
}
public AmazonS3 getClient() {
return new AmazonS3Client(creds);
}
public AmazonEC2 getEc2() {
return new AmazonEC2Client(creds);
}
}

83
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/src/main/java/org/deeplearning4j/aws/s3/reader/BaseS3DataSetIterator.java
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@ -1,83 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.s3.reader;
import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
import java.io.InputStream;
import java.util.Iterator;
import java.util.List;
/**
* baseline data applyTransformToDestination iterator for
* @author Adam Gibson
*
*/
public abstract class BaseS3DataSetIterator implements DataSetIterator {
/**
*
*/
private static final long serialVersionUID = 885205002006822431L;
private S3Downloader downloader;
private List<String> buckets;
private int currBucket;
private Iterator<InputStream> currIterator;
public BaseS3DataSetIterator() {
downloader = new S3Downloader();
buckets = downloader.buckets();
currBucket = 0;
currIterator = downloader.iterateBucket(buckets.get(currBucket));
}
public InputStream nextObject() {
if (currIterator.hasNext())
return currIterator.next();
else if (currBucket < buckets.size()) {
currBucket++;
currIterator = downloader.iterateBucket(buckets.get(currBucket));
return currIterator.next();
}
return null;
}
@Override
public boolean hasNext() {
return currBucket < buckets.size() && currIterator.hasNext();
}
public String currBucket() {
return buckets.get(currBucket);
}
public void nextBucket() {
currBucket++;
}
}

93
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/src/main/java/org/deeplearning4j/aws/s3/reader/BucketIterator.java
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@ -1,93 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.s3.reader;
import com.amazonaws.services.s3.model.ObjectListing;
import com.amazonaws.services.s3.model.S3ObjectSummary;
import java.io.InputStream;
import java.util.Iterator;
import java.util.List;
/**
* Iterator over individual S3 bucket
* @author Adam Gibson
*
*/
public class BucketIterator implements Iterator<InputStream> {
private S3Downloader s3;
private String bucket;
private ObjectListing currList;
private List<S3ObjectSummary> currObjects;
private int currObject;
public BucketIterator(String bucket) {
this(bucket, null);
}
public BucketIterator(String bucket, S3Downloader s3) {
this.bucket = bucket;
if (s3 == null)
this.s3 = new S3Downloader();
else
this.s3 = s3;
currList = this.s3.listObjects(bucket);
currObjects = currList.getObjectSummaries();
}
@Override
public boolean hasNext() {
return currObject < currObjects.size();
}
@Override
public InputStream next() {
if (currObject < currObjects.size()) {
InputStream ret = s3.objectForKey(bucket, currObjects.get(currObject).getKey());
currObject++;
return ret;
} else if (currList.isTruncated()) {
currList = s3.nextList(currList);
currObjects = currList.getObjectSummaries();
currObject = 0;
InputStream ret = s3.objectForKey(bucket, currObjects.get(currObject).getKey());
currObject++;
return ret;
}
throw new IllegalStateException("Indeterminate state");
}
@Override
public void remove() {
throw new UnsupportedOperationException();
}
}

38
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/src/main/java/org/deeplearning4j/aws/s3/reader/BucketKeyListener.java
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@ -1,38 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.s3.reader;
import com.amazonaws.services.s3.AmazonS3;
/**
* When paginating through a result applyTransformToDestination,
* allows the user to react to a bucket result being found
* @author Adam Gibson
*
*/
public interface BucketKeyListener {
/**
*
* @param s3 an s3 client
* @param bucket the bucket being iterated on
* @param key the current key
*/
void onKey(AmazonS3 s3, String bucket, String key);
}

178
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/src/main/java/org/deeplearning4j/aws/s3/reader/S3Downloader.java
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@ -1,178 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.s3.reader;
import com.amazonaws.services.s3.AmazonS3;
import com.amazonaws.services.s3.model.*;
import com.amazonaws.services.s3.transfer.MultipleFileDownload;
import com.amazonaws.services.s3.transfer.TransferManager;
import org.apache.commons.io.IOUtils;
import org.deeplearning4j.aws.s3.BaseS3;
import java.io.*;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
/**
* Downloads files from S3
* @author Adam Gibson
*
*/
public class S3Downloader extends BaseS3 {
/**
* Return the keys for a bucket
* @param bucket the bucket to get the keys for
* @return the bucket's keys
*/
public List<String> keysForBucket(String bucket) {
AmazonS3 s3 = getClient();
List<String> ret = new ArrayList<>();
ListObjectsRequest listObjectsRequest = new ListObjectsRequest().withBucketName(bucket);
ObjectListing objectListing;
do {
objectListing = s3.listObjects(listObjectsRequest);
for (S3ObjectSummary objectSummary : objectListing.getObjectSummaries()) {
ret.add(objectSummary.getKey());
}
listObjectsRequest.setMarker(objectListing.getNextMarker());
} while (objectListing.isTruncated());
return ret;
}
/**
* Returns the list of buckets in s3
* @return the list of buckets
*/
public List<String> buckets() {
List<String> ret = new ArrayList<>();
AmazonS3 s3 = getClient();
List<Bucket> buckets = s3.listBuckets();
for (Bucket b : buckets)
ret.add(b.getName());
return ret;
}
/**
* Iterate over individual buckets.
* Returns input streams to each object.
* It is your responsibility to close the input streams
* @param bucket the bucket to iterate over
* @return an iterator over the objects in an s3 bucket
*/
public Iterator<InputStream> iterateBucket(String bucket) {
return new BucketIterator(bucket, this);
}
/**
* Iterator style one list at a time
* @param list the list to get the next batch for
* @return the next batch of objects or null if
* none are left
*/
public ObjectListing nextList(ObjectListing list) {
AmazonS3 s3 = getClient();
if (list.isTruncated())
return s3.listNextBatchOfObjects(list);
return null;
}
/**
* Simple way of retrieving the listings for a bucket
* @param bucket the bucket to retrieve listings for
* @return the object listing for this bucket
*/
public ObjectListing listObjects(String bucket) {
AmazonS3 s3 = getClient();
ObjectListing list = s3.listObjects(bucket);
return list;
}
/**
* Paginates through a bucket's keys invoking the listener
* at each key
* @param bucket the bucket to iterate
* @param listener the listener
*/
public void paginate(String bucket, BucketKeyListener listener) {
AmazonS3 s3 = getClient();
ObjectListing list = s3.listObjects(bucket);
for (S3ObjectSummary summary : list.getObjectSummaries()) {
if (listener != null)
listener.onKey(s3, bucket, summary.getKey());
}
while (list.isTruncated()) {
list = s3.listNextBatchOfObjects(list);
for (S3ObjectSummary summary : list.getObjectSummaries()) {
if (listener != null)
listener.onKey(s3, bucket, summary.getKey());
}
}
}
/**
* Returns an input stream for the given bucket and key
* @param bucket the bucket to retrieve from
* @param key the key of the objec t
* @return an input stream to the object
*/
public InputStream objectForKey(String bucket, String key) {
AmazonS3 s3 = getClient();
S3Object obj = s3.getObject(bucket, key);
InputStream is = obj.getObjectContent();
return is;
}
public void download(String bucket, String key, File to) throws IOException {
AmazonS3 s3 = getClient();
S3Object obj = s3.getObject(bucket, key);
InputStream is = obj.getObjectContent();
BufferedOutputStream bos = new BufferedOutputStream(new FileOutputStream(to));
IOUtils.copy(is, bos);
bos.close();
is.close();
obj.close();
}
public void download(String bucket, String key, OutputStream to) throws IOException {
AmazonS3 s3 = getClient();
S3Object obj = s3.getObject(bucket, key);
InputStream is = obj.getObjectContent();
BufferedOutputStream bos = new BufferedOutputStream(to);
IOUtils.copy(is, bos);
bos.close();
is.close();
obj.close();
}
public MultipleFileDownload downloadFolder(String bucketName, String keyPrefix, File folderPath) {
TransferManager transfer = new TransferManager(getClient());
return transfer.downloadDirectory(bucketName, keyPrefix, folderPath);
}
}

172
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/src/main/java/org/deeplearning4j/aws/s3/uploader/S3Uploader.java
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@ -1,172 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.aws.s3.uploader;
import com.amazonaws.services.s3.AmazonS3;
import com.amazonaws.services.s3.AmazonS3Client;
import com.amazonaws.services.s3.model.*;
import com.amazonaws.services.s3.transfer.MultipleFileUpload;
import com.amazonaws.services.s3.transfer.TransferManager;
import org.deeplearning4j.aws.s3.BaseS3;
import java.io.File;
import java.util.ArrayList;
import java.util.List;
/**
* Uploads files to S3
*
* @see {@link BaseS3}
* @author Adam Gibson
*
*/
public class S3Uploader extends BaseS3 {
/**
* Multi part upload for big files
* @param file the file to upload
* @param bucketName the bucket name to upload
*/
public void multiPartUpload(File file, String bucketName) {
AmazonS3 client = new AmazonS3Client(creds);
bucketName = ensureValidBucketName(bucketName);
List<Bucket> buckets = client.listBuckets();
for (Bucket b : buckets)
if (b.getName().equals(bucketName)) {
doMultiPart(client, bucketName, file);
return;
}
//bucket didn't exist: create it
client.createBucket(bucketName);
doMultiPart(client, bucketName, file);
}
/**
* Upload the file to the bucket.
* Will create the bucket if it hasn't already been created
* @param file the file to upload
* @param bucketName the name of the bucket
*/
public void upload(File file, String bucketName) {
AmazonS3 client = new AmazonS3Client(creds);
bucketName = ensureValidBucketName(bucketName);
List<Bucket> buckets = client.listBuckets();
for (Bucket b : buckets)
if (b.getName().equals(bucketName)) {
client.putObject(bucketName, file.getName(), file);
return;
}
//bucket didn't exist: create it
client.createBucket(bucketName);
client.putObject(bucketName, file.getName(), file);
}
private void doMultiPart(AmazonS3 s3Client, String bucketName, File file) {
// Create a list of UploadPartResponse objects. You get one of these
// for each part upload.
List<PartETag> partETags = new ArrayList<>();
// Step 1: Initialize.
InitiateMultipartUploadRequest initRequest = new InitiateMultipartUploadRequest(bucketName, file.getName());
InitiateMultipartUploadResult initResponse = s3Client.initiateMultipartUpload(initRequest);
long contentLength = file.length();
long partSize = 5242880; // Set part size to 5 MB.
try {
// Step 2: Upload parts.
long filePosition = 0;
for (int i = 1; filePosition < contentLength; i++) {
// Last part can be less than 5 MB. Adjust part size.
partSize = Math.min(partSize, (contentLength - filePosition));
// Create request to upload a part.
UploadPartRequest uploadRequest = new UploadPartRequest().withBucketName(bucketName)
.withKey(file.getName()).withUploadId(initResponse.getUploadId()).withPartNumber(i)
.withFileOffset(filePosition).withFile(file).withPartSize(partSize);
// Upload part and add response to our list.
partETags.add(s3Client.uploadPart(uploadRequest).getPartETag());
filePosition += partSize;
}
// Step 3: Complete.
CompleteMultipartUploadRequest compRequest = new CompleteMultipartUploadRequest(bucketName, file.getName(),
initResponse.getUploadId(), partETags);
s3Client.completeMultipartUpload(compRequest);
} catch (Exception e) {
s3Client.abortMultipartUpload(
new AbortMultipartUploadRequest(bucketName, file.getName(), initResponse.getUploadId()));
}
}
private String ensureValidBucketName(String bucketName) {
String formatted = bucketName.replaceAll("\\s+", "_");
int length = bucketName.length();
if (length >= 62)
length = 62;
formatted = formatted.substring(0, length);
formatted = formatted.replace(".", "d");
formatted = formatted.toLowerCase();
if (formatted.endsWith("-"))
formatted = formatted.substring(0, length - 1);
return formatted;
}
public void upload(File file, String name, String bucketName) {
AmazonS3 client = getClient();
bucketName = ensureValidBucketName(bucketName);
List<Bucket> buckets = client.listBuckets();
// ObjectMetadata med = new ObjectMetadata();
// med.setContentLength(fileLength);
for (Bucket b : buckets)
if (b.getName().equals(bucketName)) {
//client.putObject(bucketName, name, is, med);
client.putObject(new PutObjectRequest(bucketName, name, file));
return;
}
//bucket didn't exist: createComplex it
client.createBucket(bucketName);
//client.putObject(bucketName, name, is, med);
client.putObject(new PutObjectRequest(bucketName, name, file));
}
public MultipleFileUpload uploadFolder(String bucketName, String keyPrefix, File folderPath,
boolean includeSubDir) {
TransferManager transfer = new TransferManager(getClient());
return transfer.uploadDirectory(bucketName, keyPrefix, folderPath, includeSubDir);
}
public MultipleFileUpload uploadFileList(String bucketName, File folderPath, List<File> fileList,
String keyPrefix) {
TransferManager transfer = new TransferManager(getClient());
return transfer.uploadFileList(bucketName, keyPrefix, folderPath, fileList);
}
}

45
deeplearning4j/deeplearning4j-scaleout/deeplearning4j-aws/src/main/resources/provision-master.sh
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@ -1,45 +0,0 @@
#!/bin/bash
################################################################################
# Copyright (c) 2015-2018 Skymind, Inc.
#
# This program and the accompanying materials are made available under the
# terms of the Apache License, Version 2.0 which is available at
# https://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.
#
# SPDX-License-Identifier: Apache-2.0
################################################################################
sudo yum -y install blas java-1.7.0-openjdk-devel
if [ ! -f "/opt/dl4j" ];
then
sudo mkdir /opt/dl4j
sudo yum -y install git
git clone https://github.com/agibsonccc/java-deeplearning
wget http://www.trieuvan.com/apache/maven/maven-3/3.1.1/binaries/apache-maven-3.1.1-bin.tar.gz
sudo mv apache-maven-3.1.1-bin.tar.gz /opt
cd /opt && sudo tar xvf apache-maven-3.1.1-bin.tar.gz && sudo mv apache-maven-3.1.1 /opt/mvn
cd /home/ec2-user/java-deeplearning/ && /opt/mvn/bin/mvn -DskipTests clean install
echo "Printing distribution"
ls /home/ec2-user/java-deeplearning/deeplearning4j-distribution/target
echo "Before moving distribution"
sudo mv deeplearning4j-distribution/target/deeplearning4j-dist.tar.gz /opt
echo "Moving distribution to opt directory..."
echo "Moving in to opt directory"
cd /opt
sudo tar xzvf deeplearning4j-dist.tar.gz
#sudo mkdir /opt/dl4j
echo "Moving jars in to /opt/dl4j/..."
sudo mv *.jar /opt/dl4j
fi

1
deeplearning4j/deeplearning4j-scaleout/pom.xml
View File

@ -28,7 +28,6 @@
<name>DeepLearning4j-scaleout-parent</name>
<modules>
<module>deeplearning4j-aws</module>
<module>spark</module>
<module>deeplearning4j-scaleout-parallelwrapper</module>
<module>deeplearning4j-scaleout-parallelwrapper-parameter-server</module>

58
deeplearning4j/deeplearning4j-util/pom.xml
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@ -1,58 +0,0 @@
<!--~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~ Copyright (c) 2015-2018 Skymind, Inc.
~
~ This program and the accompanying materials are made available under the
~ terms of the Apache License, Version 2.0 which is available at
~ https://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.
~
~ SPDX-License-Identifier: Apache-2.0
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<parent>
<artifactId>deeplearning4j-parent</artifactId>
<groupId>org.deeplearning4j</groupId>
<version>1.0.0-SNAPSHOT</version>
</parent>
<modelVersion>4.0.0</modelVersion>
<artifactId>deeplearning4j-util</artifactId>
<packaging>jar</packaging>
<name>deeplearning4j-util</name>
<url>http://maven.apache.org</url>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
</properties>
<dependencies>
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>nd4j-api</artifactId>
<version>${nd4j.version}</version>
</dependency>
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>nd4j-common</artifactId>
<version>${nd4j.version}</version>
</dependency>
</dependencies>
<profiles>
<profile>
<id>test-nd4j-native</id>
</profile>
<profile>
<id>test-nd4j-cuda-10.2</id>
</profile>
</profiles>
</project>

193
deeplearning4j/deeplearning4j-util/src/main/java/org/deeplearning4j/util/DiskBasedQueue.java
View File

@ -1,193 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.util;
import org.apache.commons.io.FileUtils;
import org.nd4j.linalg.util.SerializationUtils;
import java.io.File;
import java.io.IOException;
import java.io.Serializable;
import java.util.Collection;
import java.util.Iterator;
import java.util.Queue;
import java.util.UUID;
import java.util.concurrent.ConcurrentLinkedDeque;
import java.util.concurrent.Executors;
import java.util.concurrent.atomic.AtomicBoolean;
/**
* Naive disk based queue for storing items on disk.
* Only meant for poll and adding items.
* @author Adam Gibson
*/
public class DiskBasedQueue<E> implements Queue<E>, Serializable {
private File dir;
private Queue<String> paths = new ConcurrentLinkedDeque<>();
private AtomicBoolean running = new AtomicBoolean(true);
private Queue<E> save = new ConcurrentLinkedDeque<>();
public DiskBasedQueue() {
this(".queue");
}
public DiskBasedQueue(String path) {
this(new File(path));
}
public DiskBasedQueue(File dir) {
this.dir = dir;
if (!dir.exists() && dir.isDirectory()) {
throw new IllegalArgumentException("Illegal queue: must be a directory");
}
if (!dir.exists())
dir.mkdirs();
if (dir.listFiles() != null && dir.listFiles().length > 1)
try {
FileUtils.deleteDirectory(dir);
} catch (IOException e) {
e.printStackTrace();
}
dir.mkdir();
Thread t = Executors.defaultThreadFactory().newThread(new Runnable() {
@Override
public void run() {
while (running.get()) {
while (!save.isEmpty())
addAndSave(save.poll());
ThreadUtils.uncheckedSleep(1000);
}
}
});
t.setName("DiskBasedQueueSaver");
t.setDaemon(true);
t.start();
}
@Override
public int size() {
return paths.size();
}
@Override
public boolean isEmpty() {
return paths.isEmpty();
}
@Override
public boolean contains(Object o) {
throw new UnsupportedOperationException();
}
@Override
public Iterator<E> iterator() {
throw new UnsupportedOperationException();
}
@Override
public Object[] toArray() {
throw new UnsupportedOperationException();
}
@Override
public <T> T[] toArray(T[] a) {
throw new UnsupportedOperationException();
}
@Override
public boolean add(E e) {
save.add(e);
return true;
}
@Override
public boolean remove(Object o) {
throw new UnsupportedOperationException();
}
@Override
public boolean containsAll(Collection<?> c) {
throw new UnsupportedOperationException();
}
@Override
public boolean addAll(Collection<? extends E> c) {
for (E e : c)
addAndSave(e);
return true;
}
@Override
public boolean removeAll(Collection<?> c) {
throw new UnsupportedOperationException();
}
@Override
public boolean retainAll(Collection<?> c) {
throw new UnsupportedOperationException();
}
@Override
public void clear() {
throw new UnsupportedOperationException();
}
@Override
public boolean offer(E e) {
throw new UnsupportedOperationException();
}
@Override
public E remove() {
throw new UnsupportedOperationException();
}
@Override
public E poll() {
String path = paths.poll();
E ret = SerializationUtils.readObject(new File(path));
File item = new File(path);
item.delete();
return ret;
}
@Override
public E element() {
throw new UnsupportedOperationException();
}
@Override
public E peek() {
throw new UnsupportedOperationException();
}
private void addAndSave(E e) {
File path = new File(dir, UUID.randomUUID().toString());
SerializationUtils.saveObject(e, path);
paths.add(path.getAbsolutePath());
}
}

132
deeplearning4j/deeplearning4j-util/src/main/java/org/deeplearning4j/util/Dl4jReflection.java
View File

@ -1,132 +0,0 @@
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.util;
import java.lang.reflect.Constructor;
import java.lang.reflect.Field;
import java.lang.reflect.Modifier;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Properties;
/**
* @author Adam Gibson
*/
public class Dl4jReflection {
private Dl4jReflection() {}
/**
* Gets the empty constructor from a class
* @param clazz the class to get the constructor from
* @return the empty constructor for the class
*/
public static Constructor<?> getEmptyConstructor(Class<?> clazz) {
Constructor<?> c = clazz.getDeclaredConstructors()[0];
for (int i = 0; i < clazz.getDeclaredConstructors().length; i++) {
if (clazz.getDeclaredConstructors()[i].getParameterTypes().length < 1) {
c = clazz.getDeclaredConstructors()[i];
break;
}
}
return c;
}
public static Field[] getAllFields(Class<?> clazz) {
// Keep backing up the inheritance hierarchy.
Class<?> targetClass = clazz;
List<Field> fields = new ArrayList<>();
do {
fields.addAll(Arrays.asList(targetClass.getDeclaredFields()));
targetClass = targetClass.getSuperclass();
} while (targetClass != null && targetClass != Object.class);
return fields.toArray(new Field[fields.size()]);
}
/**
* Sets the properties of the given object
* @param obj the object o set
* @param props the properties to set
*/
public static void setProperties(Object obj, Properties props) throws Exception {
for (Field field : obj.getClass().getDeclaredFields()) {
field.setAccessible(true);
if (props.containsKey(field.getName())) {
set(field, obj, props.getProperty(field.getName()));
}
}
}
/* sets a field with a fairly basic strategy */
private static void set(Field field, Object obj, String value) throws Exception {
Class<?> clazz = field.getType();
field.setAccessible(true);
if (clazz.equals(Double.class) || clazz.equals(double.class)) {
double val = Double.valueOf(value);
field.set(obj, val);
} else if (clazz.equals(String.class)) {
field.set(obj, value);
} else if (clazz.equals(Integer.class) || clazz.equals(int.class)) {
int val = Integer.parseInt(value);
field.set(obj, val);
} else if (clazz.equals(Float.class) || clazz.equals(float.class)) {
float f = Float.parseFloat(value);
field.set(obj, f);
}
}
/**
* Get fields as properties
* @param obj the object to get fields for
* @param clazzes the classes to use for reflection and properties.
* T
* @return the fields as properties
*/
public static Properties getFieldsAsProperties(Object obj, Class<?>[] clazzes) throws Exception {
Properties props = new Properties();
for (Field field : obj.getClass().getDeclaredFields()) {
if (Modifier.isStatic(field.getModifiers()))
continue;
field.setAccessible(true);
Class<?> type = field.getType();
if (clazzes == null || contains(type, clazzes)) {
Object val = field.get(obj);
if (val != null)
props.put(field.getName(), val.toString());
}
}
return props;
}
private static boolean contains(Class<?> test, Class<?>[] arr) {
for (Class<?> c : arr)
if (c.equals(test))
return true;
return false;
}
}

135
deeplearning4j/dl4j-perf/pom.xml
View File

@ -1,135 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<!--~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~ Copyright (c) 2015-2018 Skymind, Inc.
~
~ This program and the accompanying materials are made available under the
~ terms of the Apache License, Version 2.0 which is available at
~ https://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.
~
~ SPDX-License-Identifier: Apache-2.0
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<parent>
<artifactId>deeplearning4j-parent</artifactId>
<groupId>org.deeplearning4j</groupId>
<version>1.0.0-SNAPSHOT</version>
</parent>
<modelVersion>4.0.0</modelVersion>
<artifactId>dl4j-perf</artifactId>
<name>dl4j-perf</name>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<maven.compiler.source>1.7</maven.compiler.source>
<maven.compiler.target>1.7</maven.compiler.target>
</properties>
<dependencies>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
</dependency>
<dependency>
<groupId>com.github.oshi</groupId>
<artifactId>oshi-json</artifactId>
<version>${oshi.version}</version>
</dependency>
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-nn</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>com.github.oshi</groupId>
<artifactId>oshi-core</artifactId>
<version>${oshi.version}</version>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>${lombok.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>ch.qos.logback</groupId>
<artifactId>logback-classic</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-datasets</artifactId>
<version>${project.version}</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.deeplearning4j</groupId>
<artifactId>deeplearning4j-common-tests</artifactId>
<version>${project.version}</version>
<scope>test</scope>
</dependency>
</dependencies>
<build>
<pluginManagement><!-- lock down plugins versions to avoid using Maven defaults (may be moved to parent pom) -->
<plugins>
<plugin>
<artifactId>maven-clean-plugin</artifactId>
<version>3.0.0</version>
</plugin>
<!-- see http://maven.apache.org/ref/current/maven-core/default-bindings.html#Plugin_bindings_for_jar_packaging -->
<plugin>
<artifactId>maven-resources-plugin</artifactId>
<version>3.0.2</version>
</plugin>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.7.0</version>
</plugin>
<plugin>
<artifactId>maven-surefire-plugin</artifactId>
<version>2.20.1</version>
</plugin>
<plugin>
<artifactId>maven-jar-plugin</artifactId>
<version>3.0.2</version>
</plugin>
<plugin>
<artifactId>maven-install-plugin</artifactId>
<version>2.5.2</version>
</plugin>
<plugin>
<artifactId>maven-deploy-plugin</artifactId>
<version>2.8.2</version>
</plugin>
</plugins>
</pluginManagement>
</build>
<profiles>
<profile>
<id>test-nd4j-native</id>
</profile>
<profile>
<id>test-nd4j-cuda-10.2</id>
</profile>
</profiles>
</project>

50
deeplearning4j/dl4j-perf/src/test/resources/logback-test.xml
View File

@ -1,50 +0,0 @@
<!--~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~ Copyright (c) 2015-2018 Skymind, Inc.
~
~ This program and the accompanying materials are made available under the
~ terms of the Apache License, Version 2.0 which is available at
~ https://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.
~
~ SPDX-License-Identifier: Apache-2.0
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~-->
<configuration>
<appender name="FILE" class="ch.qos.logback.core.FileAppender">
<file>logs/application.log</file>
<encoder>
<pattern>%date - [%level] - from %logger in %thread
%n%message%n%xException%n</pattern>
</encoder>
</appender>
<appender name="STDOUT" class="ch.qos.logback.core.ConsoleAppender">
<encoder>
<pattern> %logger{15} - %message%n%xException{5}
</pattern>
</encoder>
</appender>
<logger name="org.apache.catalina.core" level="DEBUG" />
<logger name="org.springframework" level="DEBUG" />
<logger name="org.deeplearning4j" level="INFO" />
<logger name="org.datavec" level="INFO" />
<logger name="org.nd4j" level="INFO" />
<logger name="opennlp.uima.util" level="OFF" />
<logger name="org.apache.uima" level="OFF" />
<logger name="org.cleartk" level="OFF" />
<root level="ERROR">
<appender-ref ref="STDOUT" />
<appender-ref ref="FILE" />
</root>
</configuration>

2
deeplearning4j/pom.xml
View File

@ -140,8 +140,6 @@
<module>deeplearning4j-nearestneighbors-parent</module>
<module>deeplearning4j-data</module>
<module>deeplearning4j-manifold</module>
<module>deeplearning4j-util</module>
<module>dl4j-perf</module>
<module>dl4j-integration-tests</module>
<module>deeplearning4j-common</module>
<module>deeplearning4j-remote</module>

4
libnd4j/tests_cpu/run_tests.sh
View File

@ -39,6 +39,7 @@ do
done
CHIP="${CHIP:-cpu}"
export GTEST_OUTPUT="xml:../target/surefire-reports/TEST-${CHIP}-results.xml"
# On Mac, make sure it can find libraries for GCC
export DYLD_LIBRARY_PATH=/usr/local/lib/gcc/8/:/usr/local/lib/gcc/7/:/usr/local/lib/gcc/6/:/usr/local/lib/gcc/5/
@ -47,8 +48,9 @@ export DYLD_LIBRARY_PATH=/usr/local/lib/gcc/8/:/usr/local/lib/gcc/7/:/usr/local/
if [ -n "$BUILD_PATH" ]; then
if which cygpath; then
BUILD_PATH=$(cygpath -p $BUILD_PATH)
export GTEST_OUTPUT="xml:'..\target\surefire-reports\TEST-${CHIP}-results.xml'"
fi
export PATH="$PATH:$BUILD_PATH"
fi
../blasbuild/${CHIP}/tests_cpu/layers_tests/runtests --gtest_output="xml:../target/surefire-reports/TEST-${CHIP}-results.xml"
../blasbuild/${CHIP}/tests_cpu/layers_tests/runtests

20
nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/pom.xml
View File

@ -217,16 +217,6 @@
<artifactId>commons-net</artifactId>
<version>${commons-net.version}</version>
</dependency>
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>nd4j-buffer</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>nd4j-context</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>net.ericaro</groupId>
<artifactId>neoitertools</artifactId>
@ -238,6 +228,16 @@
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.nd4j</groupId>
<artifactId>nd4j-common</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.bytedeco</groupId>
<artifactId>javacpp</artifactId>
<version>${javacpp.version}</version>
</dependency>
</dependencies>
<profiles>

0
nd4j/nd4j-context/src/main/java/org/nd4j/context/Nd4jContext.java → nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/context/Nd4jContext.java
View File

5
nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/broadcast/BroadcastMax.java
View File

@ -81,11 +81,6 @@ public class BroadcastMax extends BaseBroadcastOp {
throw new NoOpNameFoundException("No ONNX op name found for: " + getClass().getName());
}
@Override
public String tensorflowName() {
return "Max";
}
@Override
public List<SDVariable> doDiff(List<SDVariable> f1) {
return null;

5
nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/broadcast/BroadcastMin.java
View File

@ -81,11 +81,6 @@ public class BroadcastMin extends BaseBroadcastOp {
throw new NoOpNameFoundException("No ONNX op name found for: " + getClass().getName());
}
@Override
public String tensorflowName() {
return "Min";
}
@Override
public List<SDVariable> doDiff(List<SDVariable> f1) {
return null;

5
nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/broadcast/BroadcastMulOp.java
View File

@ -75,11 +75,6 @@ public class BroadcastMulOp extends BaseBroadcastOp {
throw new NoOpNameFoundException("No ONNX op name found for: " + getClass().getName());
}
@Override
public String tensorflowName() {
return "Mul";
}
@Override
public List<SDVariable> doDiff(List<SDVariable> f1) {
return null;

5
nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/broadcast/BroadcastSubOp.java
View File

@ -75,11 +75,6 @@ public class BroadcastSubOp extends BaseBroadcastOp {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName(){
throw new NoOpNameFoundException("No tensorflow op opName found for " + opName());
}
@Override
public List<SDVariable> doDiff(List<SDVariable> f1) {
return null;

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