System info export for debugging and bug reporting (#34)
* System info export for debugging and bug reporting Signed-off-by: Ryan Nett <rnett@skymind.io> * class name fix Signed-off-by: Ryan Nett <rnett@skymind.io> * add version information, pointer memory info Signed-off-by: Ryan Nett <rnett@skymind.io> * add nvidia-smi and nvcc info Signed-off-by: Ryan Nett <rnett@skymind.io> * line cleanup Signed-off-by: Ryan Nett <rnett@skymind.io> * nvidia-smi run works Signed-off-by: Ryan Nett <rnett@skymind.io> * add oshi dependency Signed-off-by: Ryan Nett <rnett@skymind.io> * use OS info, add workspaces info Signed-off-by: Ryan Nett <rnett@skymind.io> * use ServiceLoader to load GPU information Signed-off-by: Ryan Nett <rnett@skymind.io> * register service Signed-off-by: Ryan Nett <rnett@skymind.io> * moved service out of NativeOpsHolder (private constructor) Signed-off-by: Ryan Nett <rnett@skymind.io> * added newline Signed-off-by: Ryan Nett <rnett@skymind.io> * added license Signed-off-by: Ryan Nett <rnett@skymind.io> * and one more Signed-off-by: Ryan Nett <rnett@skymind.io> * copyright update Signed-off-by: Ryan Nett <rnett@skymind.io> * fixes Signed-off-by: Ryan Nett <rnett@skymind.io> * removed unused imports Signed-off-by: Ryan Nett <rnett@skymind.io> * removed more unused imports Signed-off-by: Ryan Nett <rnett@skymind.io> * close streams Signed-off-by: Ryan Nett <rnett@skymind.io> * and another one Signed-off-by: Ryan Nett <rnett@skymind.io> * use method Signed-off-by: Ryan Nett <rnett@skymind.io> * one more copyright Signed-off-by: Ryan Nett <rnett@skymind.io> * remove double license Signed-off-by: Ryan Nett <rnett@skymind.io> * moved test to correct package Signed-off-by: Ryan Nett <rnett@skymind.io> * classpath update Signed-off-by: Ryan Nett <rnett@skymind.io> * classpath for java >8 fix Signed-off-by: Ryan Nett <rnett@skymind.io>master
parent
e67e25ba30
commit
d854e28b34
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@ -16,7 +16,24 @@
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package org.deeplearning4j.util;
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import static org.deeplearning4j.nn.conf.inputs.InputType.inferInputType;
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import static org.deeplearning4j.nn.conf.inputs.InputType.inferInputTypes;
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import static org.nd4j.systeminfo.SystemInfo.inferVersion;
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import com.jakewharton.byteunits.BinaryByteUnit;
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import java.io.File;
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import java.io.IOException;
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import java.text.SimpleDateFormat;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.Collection;
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import java.util.Collections;
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import java.util.HashMap;
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import java.util.HashSet;
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import java.util.List;
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import java.util.Map;
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import java.util.Properties;
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import java.util.Set;
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import lombok.Getter;
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import lombok.NonNull;
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import lombok.extern.slf4j.Slf4j;
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@ -45,20 +62,9 @@ import org.nd4j.linalg.primitives.Pair;
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import org.nd4j.linalg.util.ArrayUtil;
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import org.nd4j.nativeblas.NativeOps;
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import org.nd4j.nativeblas.NativeOpsHolder;
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import org.nd4j.versioncheck.VersionCheck;
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import org.nd4j.versioncheck.VersionInfo;
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import oshi.SystemInfo;
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import oshi.software.os.OperatingSystem;
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import java.io.File;
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import java.io.IOException;
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import java.lang.reflect.Constructor;
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import java.text.SimpleDateFormat;
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import java.util.*;
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import static org.deeplearning4j.nn.conf.inputs.InputType.inferInputType;
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import static org.deeplearning4j.nn.conf.inputs.InputType.inferInputTypes;
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/**
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* A utility for generating crash reports when an out of memory error occurs.
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*
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@ -396,8 +402,6 @@ public class CrashReportingUtil {
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sb.append(String.format(fGpu, "Name", "CC", "Total Memory", "Used Memory", "Free Memory")).append("\n");
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for (int i = 0; i < nDevices; i++) {
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try {
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Class<?> c = Class.forName("org.nd4j.jita.allocator.pointers.CudaPointer");
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Constructor<?> constructor = c.getConstructor(long.class);
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String name = nativeOps.getDeviceName(i);
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long total = nativeOps.getDeviceTotalMemory(i);
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long free = nativeOps.getDeviceFreeMemory(i);
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@ -638,25 +642,4 @@ public class CrashReportingUtil {
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sb.append(fBytes("Total Activation Gradient Memory", totalExOutput));
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}
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public static Pair<String,String> inferVersion(){
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List<VersionInfo> vi = VersionCheck.getVersionInfos();
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String dl4jVersion = null;
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String dl4jCudaArtifact = null;
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for(VersionInfo v : vi){
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if("org.deeplearning4j".equals(v.getGroupId()) && "deeplearning4j-core".equals(v.getArtifactId())){
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String version = v.getBuildVersion();
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if(version.contains("SNAPSHOT")){
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dl4jVersion = version + " (" + v.getCommitIdAbbrev() + ")";
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}
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dl4jVersion = version;
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} else if("org.deeplearning4j".equals(v.getGroupId()) && v.getArtifactId() != null && v.getArtifactId().contains("deeplearning4j-cuda")){
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dl4jCudaArtifact = v.getArtifactId();
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}
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}
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return new Pair<>(dl4jVersion, dl4jCudaArtifact);
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}
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}
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@ -174,6 +174,13 @@
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</dependency>
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<!-- oshi: Used for collecting system information for system info reporting -->
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<dependency>
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<groupId>com.github.oshi</groupId>
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<artifactId>oshi-core</artifactId>
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<version>${oshi.version}</version>
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</dependency>
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<dependency>
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<groupId>junit</groupId>
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<artifactId>junit</artifactId>
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@ -0,0 +1,39 @@
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/*******************************************************************************
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* Copyright (c) 2015-2019 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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package org.nd4j.systeminfo;
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import lombok.AllArgsConstructor;
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import lombok.Data;
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@Data
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@AllArgsConstructor
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public class GPUInfo {
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public static final String fGpu = " %-30s %-5s %24s %24s %24s";
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private String name;
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private long totalMemory;
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private long freeMemory;
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int major;
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int minor;
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@Override
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public String toString(){
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return String.format(fGpu, name, major + "." + minor, SystemInfo.fBytes(totalMemory),
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SystemInfo.fBytes(totalMemory - freeMemory), SystemInfo.fBytes(freeMemory));
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}
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}
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@ -0,0 +1,23 @@
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/*******************************************************************************
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* Copyright (c) 2015-2019 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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package org.nd4j.systeminfo;
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import java.util.List;
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public interface GPUInfoProvider {
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List<GPUInfo> getGPUs();
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}
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@ -0,0 +1,442 @@
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/*******************************************************************************
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* Copyright (c) 2015-2019 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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package org.nd4j.systeminfo;
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import static org.nd4j.systeminfo.GPUInfo.fGpu;
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import com.jakewharton.byteunits.BinaryByteUnit;
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import java.io.BufferedReader;
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import java.io.File;
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import java.io.IOException;
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import java.io.InputStreamReader;
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import java.lang.management.ManagementFactory;
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import java.net.URL;
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import java.net.URLClassLoader;
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import java.util.Iterator;
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import java.util.List;
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import java.util.Map;
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import java.util.Properties;
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import java.util.ServiceLoader;
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import org.apache.commons.io.FileUtils;
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import org.apache.commons.lang3.SystemUtils;
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import org.apache.commons.lang3.exception.ExceptionUtils;
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import org.bytedeco.javacpp.Pointer;
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import org.nd4j.linalg.api.environment.Nd4jEnvironment;
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import org.nd4j.linalg.api.memory.MemoryWorkspace;
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import org.nd4j.linalg.factory.Nd4j;
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import org.nd4j.linalg.primitives.Pair;
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import org.nd4j.versioncheck.VersionCheck;
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import org.nd4j.versioncheck.VersionInfo;
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import oshi.software.os.OperatingSystem;
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/**
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* Utility class to get system info for debugging and error reporting
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*/
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public class SystemInfo {
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private static void appendField(StringBuilder sb, String name, Object value){
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sb.append(name).append(": ").append(value.toString()).append("\n");
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}
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private static void appendProperty(StringBuilder sb, String name, String property){
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appendField(sb, name, System.getProperty(property));
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}
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private static void appendHeader(StringBuilder sb, String name){
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sb.append("\n\n---------------").append(name).append("---------------\n\n");
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}
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private static final String FORMAT = "%-40s%s";
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public static String f(String s1, Object o){
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return String.format(FORMAT, s1, (o == null ? "null" : o.toString())) + "\n";
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}
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public static String fBytes(long bytes){
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String s = BinaryByteUnit.format(bytes, "#.00");
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String format = "%10s";
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s = String.format(format, s);
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if(bytes >= 1024){
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s += " (" + bytes + ")";
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}
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return s;
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}
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public static String fBytes(String s1, long bytes){
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String s = fBytes(bytes);
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return f(s1, s);
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}
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private static void appendCUDAInfo(StringBuilder sb, boolean isWindows){
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sb.append("Nvidia-smi:\n");
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try {
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ProcessBuilder pb = new ProcessBuilder("nvidia-smi");
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appendOutput(sb, pb);
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} catch (IOException e) {
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sb.append("nvidia-smi run failed.");
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if(isWindows) {
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sb.append(" Trying in C:\\Program Files\\NVIDIA Corporation\\NVSMI\n");
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try {
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ProcessBuilder pb = new ProcessBuilder(
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"C:\\Program Files\\NVIDIA Corporation\\NVSMI\\nvidia-smi.exe");
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appendOutput(sb, pb);
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} catch (IOException e1) {
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sb.append("C:\\Program Files\\NVIDIA Corporation\\NVSMI\\nvidia-smi run failed\n");
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sb.append(e1.getMessage());
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}
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} else {
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sb.append("\n");
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}
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}
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sb.append("\nnvcc --version:\n");
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try {
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ProcessBuilder pb = new ProcessBuilder("nvcc", "--version");
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appendOutput(sb, pb);
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} catch (IOException e) {
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sb.append("nvcc --version run failed.");
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}
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}
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private static void appendOutput(StringBuilder sb, ProcessBuilder pb) throws IOException {
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pb.redirectErrorStream(true);
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pb.redirectOutput();
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Process p = pb.start();
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try(InputStreamReader isr = new InputStreamReader(p.getInputStream())) {
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try(BufferedReader reader = new BufferedReader(isr)) {
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String line = null;
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while ((line = reader.readLine()) != null) {
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sb.append(line);
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sb.append(System.getProperty("line.separator"));
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}
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}
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}
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sb.append("\n");
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}
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/**
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* Gets system info in a string
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*/
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public static String getSystemInfo(){
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StringBuilder sb = new StringBuilder();
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//nd4j info
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appendHeader(sb, "ND4J Info");
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Pair<String,String> pair = inferVersion();
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sb.append(f("Deeplearning4j Version", (pair.getFirst() == null ? "<could not determine>" : pair.getFirst())));
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sb.append(f("Deeplearning4j CUDA", (pair.getSecond() == null ? "<not present>" : pair.getSecond())));
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sb.append("\n");
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boolean isCUDA = false;
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try {
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appendField(sb, "Nd4j Backend", Nd4j.getBackend().getClass().getSimpleName());
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Properties props = Nd4j.getExecutioner().getEnvironmentInformation();
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double memory = ((Long) props.get("memory.available")) / (double) 1024 / 1024 / 1024;
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String fm = String.format("%.1f", memory);
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sb.append("Backend used: [").append(props.get("backend")).append("]; OS: [").append(props.get("os"))
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.append("]\n");
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sb.append("Cores: [").append(props.get("cores")).append("]; Memory: [").append(fm).append("GB];\n");
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sb.append("Blas vendor: [").append(props.get("blas.vendor")).append("]\n");
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if (Nd4j.getExecutioner().getClass().getSimpleName().equals("CudaExecutioner")) {
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isCUDA = true;
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List<Map<String, Object>> devicesList = (List<Map<String, Object>>) props.get(Nd4jEnvironment.CUDA_DEVICE_INFORMATION_KEY);
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for (Map<String, Object> dev : devicesList) {
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sb.append("Device Name: [").append(dev.get(Nd4jEnvironment.CUDA_DEVICE_NAME_KEY)).append("]; ")
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.append("CC: [").append(dev.get(Nd4jEnvironment.CUDA_DEVICE_MAJOR_VERSION_KEY)).append(".")
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.append(dev.get(Nd4jEnvironment.CUDA_DEVICE_MINOR_VERSION_KEY))
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.append("]; Total/free memory: [").append(dev.get(Nd4jEnvironment.CUDA_TOTAL_MEMORY_KEY))
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.append("]").append("\n");
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}
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}
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sb.append("\nExecutor Properties:\n");
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for (Map.Entry<Object, Object> prop : props.entrySet()) {
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sb.append(prop.getKey().toString()).append("=").append(prop.getValue()).append("\n");
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}
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} catch (Exception e){
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sb.append("Could not get ND4J info\n");
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sb.append("Exception: ").append(e.getMessage()).append("\n");
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sb.append(ExceptionUtils.getStackTrace(e)).append("\n\n");
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}
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//hardware info
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appendHeader(sb, "Hardware Info");
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appendField(sb, "Available processors (cores)",
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Runtime.getRuntime().availableProcessors());
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oshi.SystemInfo sys = new oshi.SystemInfo();
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OperatingSystem os = sys.getOperatingSystem();
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String procName = sys.getHardware().getProcessor().getName();
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long totalMem = sys.getHardware().getMemory().getTotal();
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sb.append(f("Operating System", os.getManufacturer() + " " + os.getFamily() + " " + os.getVersion().getVersion()));
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sb.append(f("CPU", procName));
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sb.append(f("CPU Cores - Physical", sys.getHardware().getProcessor().getPhysicalProcessorCount()));
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sb.append(f("CPU Cores - Logical", sys.getHardware().getProcessor().getLogicalProcessorCount()));
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sb.append(fBytes("Total System Memory", totalMem));
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sb.append("\n");
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boolean hasGPUs = false;
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ServiceLoader<GPUInfoProvider> loader = ServiceLoader.load(GPUInfoProvider.class);
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Iterator<GPUInfoProvider> iter = loader.iterator();
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if(iter.hasNext()){
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List<GPUInfo> gpus = iter.next().getGPUs();
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sb.append(f("Number of GPUs Detected", gpus.size()));
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if(!gpus.isEmpty())
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hasGPUs = true;
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sb.append(String.format(fGpu, "Name", "CC", "Total Memory", "Used Memory", "Free Memory")).append("\n");
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for(GPUInfo gpuInfo : gpus){
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sb.append(gpuInfo).append("\n");
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}
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} else {
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sb.append("GPU Provider not found (are you missing nd4j-native?)");
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}
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appendHeader(sb, "CUDA Info");
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if(!isCUDA){
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sb.append("NOT USING CUDA Nd4j\n");
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if(hasGPUs)
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sb.append("GPUs detected, trying to list CUDA info anyways\n");
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}
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if(isCUDA || hasGPUs)
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appendCUDAInfo(sb, SystemUtils.IS_OS_WINDOWS);
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//OS info
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appendHeader(sb, "OS Info");
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appendProperty(sb, "OS" , "os.name");
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appendProperty(sb, "Version","os.version");
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appendProperty(sb, "Arch","os.arch");
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//memory settings
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appendHeader(sb, "Memory Settings");
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appendField(sb, "Free memory (bytes)",
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Runtime.getRuntime().freeMemory());
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long maxMemory = Runtime.getRuntime().maxMemory();
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appendField(sb, "Maximum memory (bytes)",
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(maxMemory == Long.MAX_VALUE ? "No Limit" : maxMemory));
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appendField(sb, "Total memory available to JVM (bytes)",
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Runtime.getRuntime().totalMemory());
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sb.append("\n");
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|
||||
long xmx = Runtime.getRuntime().maxMemory();
|
||||
long jvmTotal = Runtime.getRuntime().totalMemory();
|
||||
long javacppMaxPhys = Pointer.maxPhysicalBytes();
|
||||
long javacppMaxBytes = Pointer.maxBytes();
|
||||
long javacppCurrPhys = Pointer.physicalBytes();
|
||||
long javacppCurrBytes = Pointer.totalBytes();
|
||||
sb.append(fBytes("JVM Memory: XMX", xmx))
|
||||
.append(fBytes("JVM Memory: current", jvmTotal))
|
||||
.append(fBytes("JavaCPP Memory: Max Bytes", javacppMaxBytes))
|
||||
.append(fBytes("JavaCPP Memory: Max Physical", javacppMaxPhys))
|
||||
.append(fBytes("JavaCPP Memory: Current Bytes", javacppCurrBytes))
|
||||
.append(fBytes("JavaCPP Memory: Current Physical", javacppCurrPhys));
|
||||
boolean periodicGcEnabled = Nd4j.getMemoryManager().isPeriodicGcActive();
|
||||
long autoGcWindow = Nd4j.getMemoryManager().getAutoGcWindow();
|
||||
sb.append(f("Periodic GC Enabled", periodicGcEnabled));
|
||||
if(periodicGcEnabled){
|
||||
sb.append(f("Periodic GC Frequency", autoGcWindow + " ms"));
|
||||
}
|
||||
|
||||
// Workspaces info
|
||||
|
||||
appendHeader(sb, "Workspace Information");
|
||||
List<MemoryWorkspace> allWs = Nd4j.getWorkspaceManager().getAllWorkspacesForCurrentThread();
|
||||
sb.append(f("Workspaces: # for current thread", (allWs == null ? 0 : allWs.size())));
|
||||
//sb.append(f("Workspaces: # for all threads", allWs.size())); //TODO
|
||||
long totalWsSize = 0;
|
||||
if(allWs != null && allWs.size() > 0) {
|
||||
sb.append("Current thread workspaces:\n");
|
||||
//Name, open, size, currently allocated
|
||||
String wsFormat = " %-26s%-12s%-30s%-20s";
|
||||
sb.append(String.format(wsFormat, "Name", "State", "Size", "# Cycles")).append("\n");
|
||||
for (MemoryWorkspace ws : allWs) {
|
||||
totalWsSize += ws.getCurrentSize();
|
||||
long numCycles = ws.getGenerationId();
|
||||
sb.append(String.format(wsFormat, ws.getId(),
|
||||
(ws.isScopeActive() ? "OPEN" : "CLOSED"),
|
||||
fBytes(ws.getCurrentSize()),
|
||||
String.valueOf(numCycles))).append("\n");
|
||||
}
|
||||
}
|
||||
sb.append(fBytes("Workspaces total size", totalWsSize));
|
||||
|
||||
//JVM info
|
||||
appendHeader(sb, "JVM Info");
|
||||
|
||||
appendProperty(sb, "Runtime Name", "java.runtime.name");
|
||||
appendProperty(sb, "Java Version", "java.version");
|
||||
appendProperty(sb, "Runtime Version", "java.runtime.version");
|
||||
appendProperty(sb, "Vendor", "java.vm.vendor");
|
||||
appendProperty(sb, "Vendor Url", "java.vendor.url");
|
||||
|
||||
sb.append("\n");
|
||||
|
||||
appendProperty(sb, "VM Name", "java.vm.name");
|
||||
appendProperty(sb, "VM Version", "java.vm.version");
|
||||
appendProperty(sb, "VM Specification Name", "java.vm.specification.name");
|
||||
|
||||
sb.append("\n");
|
||||
|
||||
appendProperty(sb, "Library Path", "java.library.path");
|
||||
|
||||
|
||||
//classpath
|
||||
appendHeader(sb, "Classpath");
|
||||
ClassLoader cl = ClassLoader.getSystemClassLoader();
|
||||
|
||||
URL[] urls = null;
|
||||
try{
|
||||
urls = ((URLClassLoader)cl).getURLs();
|
||||
} catch (ClassCastException e){
|
||||
try {
|
||||
urls = ((URLClassLoader) SystemInfo.class.getClassLoader()).getURLs();
|
||||
} catch (ClassCastException e1){
|
||||
try{
|
||||
urls = ((URLClassLoader) (Thread.currentThread().getContextClassLoader())).getURLs();
|
||||
} catch (ClassCastException e2) {
|
||||
sb.append("Can't cast class loader to URLClassLoader\n");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if(urls != null) {
|
||||
for (URL url : urls) {
|
||||
sb.append(url.getFile()).append("\n");
|
||||
}
|
||||
} else {
|
||||
sb.append("Using System property java.class.path\n");
|
||||
String[] cps = System.getProperty("java.class.path").split(";");
|
||||
for(String c : cps){
|
||||
sb.append(c).append("\n");
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
//launch command
|
||||
appendHeader(sb, "Launch Command");
|
||||
|
||||
try{
|
||||
// only works on Oracle JVMs
|
||||
appendProperty(sb, "Launch Command", "sun.java.command");
|
||||
} catch (Exception e){
|
||||
appendField(sb, "Launch Command", "Not available on this JVM");
|
||||
}
|
||||
|
||||
List<String> inputArguments = ManagementFactory.getRuntimeMXBean().getInputArguments();
|
||||
appendField(sb, "JVM Arguments", inputArguments);
|
||||
|
||||
|
||||
//system properties
|
||||
appendHeader(sb, "System Properties");
|
||||
|
||||
Properties props = System.getProperties();
|
||||
for(Map.Entry<Object, Object> prop : props.entrySet()){
|
||||
if(prop.getKey().toString().equals("line.separator")) {
|
||||
sb.append(prop.getKey().toString()).append("=")
|
||||
.append(prop.getValue().toString().replace("\\", "\\\\")).append("\n");
|
||||
} else {
|
||||
sb.append(prop.getKey().toString()).append("=").append(prop.getValue()).append("\n");
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
//enviroment variables
|
||||
appendHeader(sb, "Environment Variables");
|
||||
|
||||
Map<String, String> env = System.getenv();
|
||||
|
||||
for(String key : env.keySet()){
|
||||
sb.append(key).append("=").append(env.get(key)).append("\n");
|
||||
}
|
||||
|
||||
return sb.toString();
|
||||
}
|
||||
|
||||
/**
|
||||
* Writes system info to the given file
|
||||
*/
|
||||
public static void writeSystemInfo(File file){
|
||||
try {
|
||||
file.createNewFile();
|
||||
FileUtils.writeStringToFile(file, getSystemInfo());
|
||||
} catch (IOException e) {
|
||||
throw new RuntimeException("IOException:" + e.getMessage(), e);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Prints system info
|
||||
*/
|
||||
public static void printSystemInfo(){
|
||||
System.out.println(getSystemInfo());
|
||||
}
|
||||
|
||||
public static Pair<String,String> inferVersion(){
|
||||
List<VersionInfo> vi = VersionCheck.getVersionInfos();
|
||||
|
||||
String dl4jVersion = null;
|
||||
String dl4jCudaArtifact = null;
|
||||
for(VersionInfo v : vi){
|
||||
if("org.deeplearning4j".equals(v.getGroupId()) && "deeplearning4j-core".equals(v.getArtifactId())){
|
||||
String version = v.getBuildVersion();
|
||||
if(version.contains("SNAPSHOT")){
|
||||
dl4jVersion = version + " (" + v.getCommitIdAbbrev() + ")";
|
||||
}
|
||||
dl4jVersion = version;
|
||||
} else if("org.deeplearning4j".equals(v.getGroupId()) && v.getArtifactId() != null && v.getArtifactId().contains("deeplearning4j-cuda")){
|
||||
dl4jCudaArtifact = v.getArtifactId();
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
return new Pair<>(dl4jVersion, dl4jCudaArtifact);
|
||||
}
|
||||
}
|
|
@ -0,0 +1,55 @@
|
|||
/*******************************************************************************
|
||||
* Copyright (c) 2015-2019 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.nd4j.nativeblas;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.nd4j.systeminfo.GPUInfo;
|
||||
import org.nd4j.systeminfo.GPUInfoProvider;
|
||||
|
||||
@Slf4j
|
||||
public class NativeOpsGPUInfoProvider implements GPUInfoProvider {
|
||||
|
||||
@Override
|
||||
public List<GPUInfo> getGPUs() {
|
||||
NativeOps nativeOps = NativeOpsHolder.getInstance().getDeviceNativeOps();
|
||||
|
||||
List<GPUInfo> gpus = new ArrayList<>();
|
||||
|
||||
|
||||
int nDevices = nativeOps.getAvailableDevices();
|
||||
if (nDevices > 0) {
|
||||
for (int i = 0; i < nDevices; i++) {
|
||||
try {
|
||||
String name = nativeOps.getDeviceName(i);
|
||||
long total = nativeOps.getDeviceTotalMemory(i);
|
||||
long free = nativeOps.getDeviceFreeMemory(i);
|
||||
int major = nativeOps.getDeviceMajor(i);
|
||||
int minor = nativeOps.getDeviceMinor(i);
|
||||
|
||||
gpus.add(new GPUInfo(name, total, free, major, minor));
|
||||
} catch (Exception e) {
|
||||
log.warn("Can't add GPU", e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return gpus;
|
||||
}
|
||||
|
||||
}
|
|
@ -16,17 +16,15 @@
|
|||
|
||||
package org.nd4j.nativeblas;
|
||||
|
||||
import java.util.Properties;
|
||||
import lombok.Getter;
|
||||
import org.bytedeco.javacpp.Loader;
|
||||
import org.bytedeco.javacpp.Pointer;
|
||||
import org.nd4j.config.ND4JEnvironmentVars;
|
||||
import org.nd4j.context.Nd4jContext;
|
||||
import org.nd4j.linalg.factory.Nd4j;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
|
||||
import java.util.Properties;
|
||||
|
||||
/**
|
||||
* @author raver119@gmail.com
|
||||
* @author saudet
|
||||
|
@ -74,5 +72,4 @@ public class NativeOpsHolder {
|
|||
public static NativeOpsHolder getInstance() {
|
||||
return INSTANCE;
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
@ -0,0 +1,17 @@
|
|||
################################################################################
|
||||
# Copyright (c) 2015-2019 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
|
||||
################################################################################
|
||||
|
||||
org.nd4j.nativeblas.NativeOpsGPUInfoProvider
|
|
@ -0,0 +1,27 @@
|
|||
/*******************************************************************************
|
||||
* Copyright (c) 2015-2019 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.nd4j.systeminfo;
|
||||
|
||||
import org.junit.Test;
|
||||
import org.nd4j.systeminfo.SystemInfo;
|
||||
|
||||
public class TestSystemInfo {
|
||||
@Test
|
||||
public void testSystemInfo(){
|
||||
SystemInfo.printSystemInfo();
|
||||
}
|
||||
}
|
Loading…
Reference in New Issue