org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner Maven / Gradle / Ivy
/*
* ******************************************************************************
* *
* *
* * 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.
* *
* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
* * 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.linalg.api.ops.executioner;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.bytedeco.javacpp.Pointer;
import org.nd4j.autodiff.functions.DifferentialFunction;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataBuffer;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.environment.Nd4jEnvironment;
import org.nd4j.linalg.api.memory.MemoryWorkspace;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ndarray.INDArrayStatistics;
import org.nd4j.linalg.api.ops.*;
import org.nd4j.linalg.api.ops.aggregates.Aggregate;
import org.nd4j.linalg.api.ops.aggregates.Batch;
import org.nd4j.linalg.api.ops.compression.DecodeBitmap;
import org.nd4j.linalg.api.ops.compression.DecodeThreshold;
import org.nd4j.linalg.api.ops.compression.EncodeBitmap;
import org.nd4j.linalg.api.ops.compression.EncodeThreshold;
import org.nd4j.linalg.api.ops.impl.scatter.ScatterUpdate;
import org.nd4j.linalg.api.ops.impl.summarystats.Variance;
import org.nd4j.linalg.api.rng.Random;
import org.nd4j.linalg.api.shape.LongShapeDescriptor;
import org.nd4j.linalg.api.shape.Shape;
import org.nd4j.linalg.api.shape.TadPack;
import org.nd4j.linalg.cache.TADManager;
import org.nd4j.linalg.exception.ND4JIllegalStateException;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.common.primitives.AtomicBoolean;
import org.nd4j.common.primitives.Optional;
import org.nd4j.linalg.profiler.OpProfiler;
import org.nd4j.linalg.profiler.ProfilerConfig;
import org.nd4j.common.util.ArrayUtil;
import java.util.*;
@Slf4j
public abstract class DefaultOpExecutioner implements OpExecutioner {
private static final String SCOPE_PANIC_MSG = "For more details, see the ND4J User Guide: https://deeplearning4j.konduit.ai/nd4j/overview#workspaces-scope-panic";
protected ProfilingMode profilingMode = ProfilingMode.SCOPE_PANIC;
protected AtomicBoolean verbose = new AtomicBoolean(false);
protected AtomicBoolean debug = new AtomicBoolean(false);
public DefaultOpExecutioner() {}
protected void checkForCompression(Op op) {
// check for INT datatype arrays
interceptIntDataType(op);
if (op.x() != null && op.x().isCompressed())
Nd4j.getCompressor().decompressi(op.x());
if (op.y() != null && op.y().isCompressed())
Nd4j.getCompressor().decompressi(op.y());
if (op.z() != null && op.z().isCompressed())
Nd4j.getCompressor().decompressi(op.z());
}
@Override
public String getLastOp() {
return "UNKNOWN";
}
/**
* This method checks if any Op operand has data opType of INT, and throws exception if any.
*
* @param op
*/
protected void interceptIntDataType(Op op) {
// FIXME: Remove this method, after we'll add support for dtype operations
/*
if (op.x() != null && op.x().data().dataType() == DataType.INT)
throw new ND4JIllegalStateException(
"Op.X contains INT data. Operations on INT dataType are not supported yet");
if (op.z() != null && op.z().data().dataType() == DataType.INT)
throw new ND4JIllegalStateException(
"Op.Z contains INT data. Operations on INT dataType are not supported yet");
if (op.y() != null && op.y().data().dataType() == DataType.INT)
throw new ND4JIllegalStateException(
"Op.Y contains INT data. Operations on INT dataType are not supported yet.");
*/
}
@Override
public abstract INDArray exec(Op op);
@Override
public abstract INDArray exec(Op op, OpContext opContext);
@Override
public Op execAndReturn(Op op) {
if (op instanceof TransformOp) {
return execAndReturn((TransformOp) op);
}
if (op instanceof ScalarOp) {
return execAndReturn((ScalarOp) op);
}
if (op instanceof ReduceOp) {
exec((ReduceOp) op);
return op;
}
if (op instanceof IndexAccumulation) {
exec((IndexAccumulation) op);
return op;
}
throw new IllegalArgumentException("Illegal opType of op: " + op.getClass());
}
@Override
public TransformOp execAndReturn(TransformOp op) {
exec(op);
return op;
}
@Override
public ReduceOp execAndReturn(ReduceOp op) {
exec(op);
return op;
}
@Override
public Variance execAndReturn(Variance op) {
exec(op);
return op;
}
@Override
public ScalarOp execAndReturn(ScalarOp op) {
exec(op);
return op;
}
@Override
public IndexAccumulation execAndReturn(IndexAccumulation op) {
exec(op);
return op;
}
@Override
public BroadcastOp execAndReturn(BroadcastOp op) {
exec(op);
return op;
}
@Override
public INDArray[] exec(CustomOp op) {
return execAndReturn(op).outputArguments().toArray(new INDArray[0]);
}
@Override
public abstract INDArray exec(ReduceOp op);
@Override
public abstract INDArray exec(Variance accumulation);
@Override
public abstract INDArray exec(IndexAccumulation op);
@Override
public abstract INDArray exec(BroadcastOp broadcast);
@Override
public void exec(MetaOp op) {
throw new UnsupportedOperationException("MetaOp execution isn't supported for this OpExecutioner yet");
}
@Override
public void exec(GridOp op) {
throw new UnsupportedOperationException("GridOp execution isn't supported for this OpExecutioner yet");
}
@Override
public void exec(Batch batch) {
throw new UnsupportedOperationException();
}
@Override
public void exec(Aggregate op) {
throw new UnsupportedOperationException();
}
@Override
public abstract INDArray exec(ScalarOp op);
@Override
public void exec(List batch) {
throw new UnsupportedOperationException();
}
/**
* This method executes specified RandomOp using default RNG available via Nd4j.getRandom()
*
* @param op
*/
@Override
public INDArray exec(RandomOp op) {
return exec(op, Nd4j.getRandom());
}
/**
* This method executes specific RandomOp against specified RNG
*
* @param op
* @param rng
*/
@Override
public abstract INDArray exec(RandomOp op, Random rng);
@Deprecated
@Override
public void setProfilingMode(ProfilingMode mode) {
profilingMode = mode;
ProfilerConfig config = null;
switch (profilingMode) {
case ALL:
config = ProfilerConfig.builder().checkWorkspaces(true).checkElapsedTime(true).stackTrace(true).build();
break;
case METHODS:
config = ProfilerConfig.builder().stackTrace(true).build();
break;
case OPERATIONS:
config = ProfilerConfig.builder().stackTrace(true).checkElapsedTime(true).build();
break;
case SCOPE_PANIC:
config = ProfilerConfig.builder().checkWorkspaces(true).build();
break;
case ANY_PANIC:
config = ProfilerConfig.builder().checkForINF(true).checkForNAN(true).build();
break;
case INF_PANIC:
config = ProfilerConfig.builder().checkForINF(true).build();
break;
case NAN_PANIC:
config = ProfilerConfig.builder().checkForNAN(true).build();
break;
default:
config = ProfilerConfig.builder().build();
break;
}
OpProfiler.getInstance().setConfig(config);
}
@Override
public void setProfilingConfig(ProfilerConfig config) {
OpProfiler.getInstance().setConfig(config);
}
@Deprecated
@Override
public ProfilingMode getProfilingMode() {
return profilingMode;
}
protected void checkWorkspace(String opName, INDArray array) {
if (array.isAttached()) {
val ws = array.data().getParentWorkspace();
if (ws.getWorkspaceType() != MemoryWorkspace.Type.CIRCULAR) {
if (!ws.isScopeActive()) {
throw new ND4JIllegalStateException("Op [" + opName + "] X argument uses leaked workspace pointer from workspace ["
+ ws.getId() + "]: Workspace the array was defined in is no longer open.\nAll open workspaces: " + allOpenWorkspaces() + "\n" + SCOPE_PANIC_MSG);
}
if (ws.getGenerationId() != array.data().getGenerationId())
throw new ND4JIllegalStateException("Op [" + opName + "] X argument uses outdated workspace pointer from workspace ["
+ ws.getId() + "]: Workspace array was defined in has been closed and reopened at least once since array creation. Array WS iteration: " +
array.data().getGenerationId() + ". Workspace current iteration: " +
ws.getGenerationId() + "\nAll open workspaces: " + allOpenWorkspaces() + "\n" + SCOPE_PANIC_MSG);
}
}
}
protected void checkForWorkspaces(CustomOp op, OpContext oc) {
List inArgs = oc != null ? oc.getInputArrays() : op.inputArguments();
List outArgs = oc != null ? oc.getOutputArrays() : op.outputArguments();
int count = 0;
for (val input: inArgs) {
checkWorkspace(op.opName(), input);
count++;
}
for (val output: outArgs)
checkWorkspace(op.opName(), output);
}
protected void checkForWorkspaces(Op op, OpContext oc) {
val x = oc != null ? oc.getInputArray(0) : op.x();
if (x != null)
checkWorkspace(op.opName(), x);
val y = oc != null && oc.getInputArrays().size() > 1 ? oc.getInputArray(1) : op.y();
if (y != null)
checkWorkspace(op.opName(), y);
val z = oc != null ? oc.getOutputArray(0) : op.z();
if (z != null)
checkWorkspace(op.opName(), z);
}
public static List allOpenWorkspaces(){
List l = Nd4j.getWorkspaceManager().getAllWorkspacesForCurrentThread();
List workspaces = new ArrayList<>(l.size());
for( MemoryWorkspace ws : l){
if(ws.isScopeActive()) {
workspaces.add(ws.getId());
}
}
return workspaces;
}
@Deprecated
public long profilingHookIn(Op op, DataBuffer... tadBuffers) {
switch (profilingMode) {
case ALL:
OpProfiler.getInstance().processOpCall(op, tadBuffers);
break;
case METHODS:
break;
case OPERATIONS:
OpProfiler.getInstance().processOpCall(op, tadBuffers);
break;
case SCOPE_PANIC:
checkForWorkspaces(op, null);
return 0L;
case DISABLED:
default:
return 0L;
}
return System.nanoTime();
}
@Deprecated
public long profilingHookIn(CustomOp op, OpContext oc) {
switch (profilingMode) {
case ALL:
OpProfiler.getInstance().processOpCall(op);
break;
case METHODS:
break;
case OPERATIONS:
OpProfiler.getInstance().processOpCall(op);
break;
case SCOPE_PANIC:
checkForWorkspaces(op, oc);
return 0L;
case DISABLED:
default:
return 0L;
}
return System.nanoTime();
}
@Deprecated
public void profilingHookOut(Op op, OpContext oc, long timeStart) {
switch (profilingMode) {
case ALL:
OpProfiler.getInstance().processStackCall(op, timeStart);
OpProfiler.getInstance().timeOpCall(op, timeStart);
break;
case METHODS:
OpProfiler.getInstance().processStackCall(op, timeStart);
break;
case OPERATIONS:
OpProfiler.getInstance().timeOpCall(op, timeStart);
break;
case NAN_PANIC:
OpExecutionerUtil.checkForNaN(op, oc);
break;
case INF_PANIC:
OpExecutionerUtil.checkForInf(op, oc);
break;
case ANY_PANIC:
OpExecutionerUtil.checkForNaN(op, oc);
OpExecutionerUtil.checkForInf(op, oc);
break;
case DISABLED:
default:
break;
}
if (Nd4j.getExecutioner().isVerbose()) {
if (op.z() != null)
log.info("Op name: {}; Z shapeInfo: {}; Z values: {}", op.opName(), op.z().shapeInfoJava(), firstX(op.z(), 10));
}
}
@Deprecated
public void profilingHookOut(CustomOp op, OpContext oc, long timeStart) {
switch (profilingMode) {
case ALL:
OpProfiler.getInstance().processStackCall(op, timeStart);
OpProfiler.getInstance().timeOpCall(op, timeStart);
break;
case METHODS:
OpProfiler.getInstance().processStackCall(op, timeStart);
break;
case OPERATIONS:
OpProfiler.getInstance().timeOpCall(op, timeStart);
break;
case NAN_PANIC:
OpExecutionerUtil.checkForNaN(op, oc);
break;
case INF_PANIC:
OpExecutionerUtil.checkForInf(op, oc);
break;
case ANY_PANIC:
OpExecutionerUtil.checkForNaN(op, oc);
OpExecutionerUtil.checkForInf(op, oc);
break;
case DISABLED:
default:
break;
}
}
public long profilingConfigurableHookIn(CustomOp op, OpContext oc) {
List inArgs = oc != null ? oc.getInputArrays() : op.inputArguments();
List outArgs = oc != null ? oc.getOutputArrays() : op.outputArguments();
for (val arr: inArgs)
if (arr.wasClosed())
throw new IllegalStateException("One of Input arguments was closed before call");
for (val arr: outArgs)
if (arr.wasClosed())
throw new IllegalStateException("One of Output arguments was closed before call");
if (OpProfiler.getInstance().getConfig() == null)
return System.nanoTime();
if (OpProfiler.getInstance().getConfig().isStackTrace() ||
OpProfiler.getInstance().getConfig().isCheckElapsedTime()) {
OpProfiler.getInstance().processOpCall(op);
}
if (OpProfiler.getInstance().getConfig().isCheckWorkspaces()) {
checkForWorkspaces(op, oc);
}
return System.nanoTime();
}
public long profilingConfigurableHookIn(Op op, DataBuffer... tadBuffers) {
if (op.x() != null)
if (op.x().wasClosed())
throw new IllegalStateException("Op.X argument was closed before call");
if (op.y() != null)
if (op.y().wasClosed())
throw new IllegalStateException("Op.Y argument was closed before call");
if (op.z() != null)
if (op.z().wasClosed())
throw new IllegalStateException("Op.Z argument was closed before call");
if (OpProfiler.getInstance().getConfig() == null)
return System.nanoTime();
if (OpProfiler.getInstance().getConfig().isStackTrace() ||
OpProfiler.getInstance().getConfig().isCheckElapsedTime()) {
OpProfiler.getInstance().processOpCall(op);
}
if (OpProfiler.getInstance().getConfig().isNotOptimalTAD()) {
OpProfiler.getInstance().processOpCall(op, tadBuffers);
}
if (OpProfiler.getInstance().getConfig().isCheckWorkspaces()) {
checkForWorkspaces(op, null);
}
return System.nanoTime();
}
public void profilingConfigurableHookOut(Op op, OpContext oc, long timeStart) {
if (OpProfiler.getInstance().getConfig() == null)
return;
if (OpProfiler.getInstance().getConfig().isStackTrace()) {
OpProfiler.getInstance().processStackCall(op, timeStart);
}
if (OpProfiler.getInstance().getConfig().isCheckElapsedTime()) {
OpProfiler.getInstance().timeOpCall(op, timeStart);
}
if (OpProfiler.getInstance().getConfig().isCheckForNAN()) {
OpExecutionerUtil.checkForNaN(op, oc);
}
if (OpProfiler.getInstance().getConfig().isCheckForINF()) {
OpExecutionerUtil.checkForInf(op, oc);
}
if (OpProfiler.getInstance().getConfig().isNativeStatistics()) {
if (op.z() != null) {
INDArrayStatistics stat = inspectArray(op.z());
OpProfiler.getInstance().setStatistics(stat);
log.info("Op name: {}; Z shapeInfo: {}; Statistics: min:{} max:{} mean:{} stdev:{} pos:{}, neg:{} zero:{} inf:{} nan:{}",
op.opName(), op.z().shapeInfoJava(), stat.getMinValue(), stat.getMaxValue(), stat.getMeanValue(),
stat.getStdDevValue(), stat.getCountPositive(), stat.getCountNegative(),
stat.getCountZero(), stat.getCountInf(), stat.getCountNaN());
}
}
if (Nd4j.getExecutioner().isVerbose()) {
if (op.z() != null)
log.info("Op name: {}; Z shapeInfo: {}; Z values: {}", op.opName(), op.z().shapeInfoJava(), firstX(op.z(), 10));
}
}
public void profilingConfigurableHookOut(CustomOp op, OpContext oc, long timeStart) {
if (OpProfiler.getInstance().getConfig() == null)
return;
if (OpProfiler.getInstance().getConfig().isStackTrace()) {
OpProfiler.getInstance().processStackCall(op, timeStart);
}
if (OpProfiler.getInstance().getConfig().isCheckElapsedTime()) {
OpProfiler.getInstance().timeOpCall(op, timeStart);
}
if (OpProfiler.getInstance().getConfig().isCheckForNAN()) {
OpExecutionerUtil.checkForNaN(op, oc);
}
if (OpProfiler.getInstance().getConfig().isCheckForINF()) {
OpExecutionerUtil.checkForInf(op, oc);
}
}
/**
* Validate the data types
* for the given operation
* @param expectedType
* @param op
*/
public static void validateDataType(DataType expectedType, Op op) {
if (op.x() != null && !Shape.isEmpty(op.x().shapeInfoJava()) && op.x().data().dataType() == DataType.COMPRESSED) {
Nd4j.getCompressor().decompressi(op.x());
}
if (op.y() != null && !Shape.isEmpty(op.y().shapeInfoJava()) && op.y().data().dataType() == DataType.COMPRESSED) {
Nd4j.getCompressor().decompressi(op.y());
}
if (op.z() != null && !Shape.isEmpty(op.z().shapeInfoJava()) && op.z().data().dataType() == DataType.COMPRESSED) {
Nd4j.getCompressor().decompressi(op.z());
}
/*
if (op.x() != null && !Shape.isEmpty(op.x().shapeInfoJava())
&& op.x().data().dataType() != expectedType
&& op.x().data().dataType() != DataType.COMPRESSED) {
throw new ND4JIllegalStateException("op.X dataType is [" + op.x().data().dataType()
+ "] instead of expected [" + expectedType + "] - x.shape = " + Arrays.toString(op.x().shape())
+ (op.y() != null ? ", y.shape=" + Arrays.toString(op.y().shape()) : "")
+ ", z.shape=" + Arrays.toString(op.z().shape()) + " - op: " + op.getClass().getName());
}
*/
/*
if (op.z() != null && !Shape.isEmpty(op.z().shapeInfoJava())
&& op.z().data().dataType() != expectedType
&& op.z().data().dataType() != DataType.COMPRESSED)
throw new ND4JIllegalStateException("op.Z dataType is [" + op.z().data().dataType()
+ "] instead of expected [" + expectedType + "]");
*/
if (op.y() != null && !Shape.isEmpty(op.y().shapeInfoJava())
&& op.y().data().dataType() != expectedType) {
throw new ND4JIllegalStateException("op.Y dataType is [" + op.y().data().dataType()
+ "] instead of expected [" + expectedType + "] - x.shape = " + Arrays.toString(op.x().shape())
+ (op.y() != null ? ", y.shape=" + Arrays.toString(op.y().shape()) : "")
+ ", z.shape=" + Arrays.toString(op.z().shape()) + " - op: " + op.getClass().getName());
}
if (Nd4j.getExecutioner().isVerbose()) {
log.info("Reporting [{}]", op.opName());
if (op.x() != null)
log.info("X shapeInfo: {}; X values: {}", op.x().shapeInfoJava(), firstX(op.x(), 10));
if (op.y() != null)
log.info("Y shapeInfo: {}; Y values: {}", op.y().shapeInfoJava(), firstX(op.y(), 10));
}
}
protected static String firstX(INDArray array, int x) {
val builder = new StringBuilder("[");
val limit = (int) Math.min(x, array.length());
for (int e = 0; e < limit; e++) {
builder.append(array.getDouble(e));
if (e < limit - 1)
builder.append(", ");
}
builder.append("]");
return builder.toString();
}
public static void validateDataType(DataType expectedType, Object op, INDArray... operands) {
if (operands == null || operands.length == 0)
return;
int cnt = 0;
for (INDArray operand : operands) {
if (operand == null)
continue;
if (operand.data().dataType() != expectedType) {
throw new ND4JIllegalStateException("INDArray [" + cnt + "] dataType is [" + operand.data().dataType()
+ "] instead of expected [" + expectedType + "]" + (op != null ? " op: " + op.getClass().getName() : ""));
}
cnt++;
}
}
@Override
public TADManager getTADManager() {
throw new UnsupportedOperationException();
}
/**
* This method return set of key/value and key/key/value objects, describing current environment
*
* @return
*/
@Override
public Properties getEnvironmentInformation() {
Properties environment = new Properties();
environment.put(Nd4jEnvironment.CPU_CORES_KEY, Runtime.getRuntime().availableProcessors());
environment.put(Nd4jEnvironment.HOST_TOTAL_MEMORY_KEY, Runtime.getRuntime().maxMemory());
environment.put(Nd4jEnvironment.OS_KEY, System.getProperty("os.name"));
return environment;
}
@Override
public void printEnvironmentInformation() {
Properties env = getEnvironmentInformation();
double memory = ((Long) env.get("memory.available")) / (double) 1024 / 1024 / 1024;
String fm = String.format("%.1f", memory);
log.info("Backend used: [{}]; OS: [{}]", env.get("backend"), env.get("os"));
log.info("Cores: [{}]; Memory: [{}GB];", env.get("cores"), fm);
log.info("Blas vendor: [{}]", env.get("blas.vendor"));
}
@Override
public void push() {
// no-op
}
@Override
public void commit() {
// no-op
}
@Override
public INDArray thresholdEncode(INDArray input, double threshold) {
return thresholdEncode(input, threshold, Integer.MAX_VALUE);
}
private long _length(long[] shape) {
// scalar case
if (shape.length == 0)
return 1;
else if (shape.length == 1)
return shape[0];
else {
long length = 1;
for (int e = 0; e < shape.length; e++)
length *= shape[e];
return length;
}
}
@Override
public INDArray thresholdEncode(INDArray input, double threshold, Integer boundary) {
val op_shape = new EncodeThreshold(input, (float) threshold, boundary);
val shapes = Nd4j.getExecutioner().calculateOutputShape(op_shape);
if (_length(shapes.get(1).getShape()) < 2)
return null;
val result = Nd4j.create(DataType.INT32, shapes.get(1).getShape());
op_shape.addOutputArgument(input, result);
Nd4j.exec(op_shape);
return result.getInt(0) > 0 ? result : null;
}
@Override
public INDArray thresholdDecode(INDArray encoded, INDArray target) {
Nd4j.exec(new DecodeThreshold(encoded, target));
return target;
}
@Override
public long bitmapEncode(INDArray indArray, INDArray target, double threshold) {
val results = Nd4j.exec(new EncodeBitmap(indArray, target, Nd4j.scalar(0), (float) threshold));
// return number of elements taht were compressed
return results[2].getInt(0);
}
@Override
public INDArray bitmapEncode(INDArray indArray, double threshold) {
val array = Nd4j.create(DataType.INT32, indArray.length() / 16 + 5);
bitmapEncode(indArray, array, threshold);
return array;
}
@Override
public INDArray bitmapDecode(INDArray encoded, INDArray target) {
Nd4j.exec(new DecodeBitmap(encoded, target));
return target;
}
@Override
public Map getCustomOperations() {
throw new UnsupportedOperationException();
}
@Override
public CustomOp execAndReturn(CustomOp op) {
exec(op);
return op;
}
@Override
public List calculateOutputShape(CustomOp op) {
throw new UnsupportedOperationException();
}
@Override
public List calculateOutputShape(CustomOp op, OpContext opContext) {
throw new UnsupportedOperationException();
}
@Override
public INDArray[] allocateOutputArrays(CustomOp op){
List shapes = calculateOutputShape(op);
INDArray[] out = new INDArray[shapes.size()];
for(int i=0; i executeGraph(long id, Map map, Map reverseMap) {
throw new UnsupportedOperationException("Not yet implemented");
}
@Override
public void forgetGraph(long id) {
throw new UnsupportedOperationException("Not yet implemented");
}
/**
* This method allows to set desired number of elements per thread, for performance optimization purposes.
* I.e. if array contains 2048 elements, and threshold is set to 1024, 2 threads will be used for given op execution.
*
* Default value: 1024
*
* @param threshold
*/
@Override
public void setElementsThreshold(int threshold) {
// no-op
}
/**
* This method allows to set desired number of sub-arrays per thread, for performance optimization purposes.
* I.e. if matrix has shape of 64 x 128, and threshold is set to 8, each thread will be processing 8 sub-arrays (sure, if you have 8 core cpu).
* If your cpu has, say, 4, cores, only 4 threads will be spawned, and each will process 16 sub-arrays
*
* Default value: 8
*
* @param threshold
*/
@Override
public void setTadThreshold(int threshold) {
// no-op
}
@Override
public boolean isVerbose() {
return verbose.get();
}
@Override
public boolean isDebug() {
return debug.get();
}
@Override
public ExecutionerType type() {
throw new UnsupportedOperationException();
}
@Override
public String getString(DataBuffer buffer, long index) {
throw new UnsupportedOperationException();
}
@Override
public void scatterUpdate(ScatterUpdate.UpdateOp op, INDArray array, INDArray indices, INDArray updates, int[] axis) {
throw new UnsupportedOperationException();
}
/**
* Get the information about the op in a String representation, for throwing more useful exceptions (mainly for debugging)
* @param op
* @param dimensions Use optional here for 3 states: null = "not an exec(Op, int... dim) call". empty = "exec(Op, null)".
* Otherwise present = "exec(Op,int[])" call
* @return
*/
public String opInfoString(Op op, Optional dimensions){
if(op == null)
return "";
StringBuilder sb = new StringBuilder();
sb.append("Class: ").append(op.getClass().getName()).append("; opNum: ").append(op.opNum())
.append("; opName: ").append(op.opName());
if(op instanceof DifferentialFunction){
sb.append("; opType: ").append(((DifferentialFunction)op).opType());
}
if(dimensions != null){
sb.append("; dimensions: ");
if(dimensions.isPresent()){
sb.append(Arrays.toString(dimensions.get()));
} else {
sb.append("");
}
}
INDArray x = op.x();
INDArray y = op.y();
INDArray z = op.z();
Object[] extraArgs = op.extraArgs();
sb.append("\n");
sb.append("x: ").append(arrayInfo(x)).append("; ");
sb.append("y: ").append(arrayInfo(y)).append("; ");
sb.append("z: ").append(arrayInfo(z)).append("; ");
if(x == y && x != null)
sb.append("(x == y)");
if(x == z && x != null)
sb.append("(x == z)");
if(y == z && y != null)
sb.append("(y == z)");
sb.append("\n");
sb.append("; extraArgs: ").append(Preconditions.formatArray(extraArgs));
return sb.toString();
}
public String arrayInfo(INDArray arr){
if(arr == null)
return "";
if(arr.isEmpty())
return "(empty NDArray)";
return arr.shapeInfoToString().replaceAll("\n","");
}
@Override
public boolean isExperimentalMode() {
return false;
}
@Override
public OpContext buildContext() {
throw new UnsupportedOperationException("OpContext is available only on native backends");
}
@Override
public INDArray[] exec(CustomOp op, OpContext context) {
throw new UnsupportedOperationException();
}
@Override
public INDArrayStatistics inspectArray(INDArray array) {
throw new UnsupportedOperationException();
}
@Override
public DataBuffer createShapeInfo(long[] shape, long[] stride, long elementWiseStride, char order, DataType dtype, boolean empty) {
throw new UnsupportedOperationException();
}
@Override
public DataBuffer createShapeInfo(long[] shape, long[] stride, long elementWiseStride, char order, DataType dtype, long extras) {
throw new UnsupportedOperationException();
}
@Override
public TadPack tadShapeInfoAndOffsets(INDArray array, int[] dimension) {
throw new UnsupportedOperationException();
}
@Override
public DataBuffer createConstantBuffer(long[] values, DataType desiredType) {
throw new UnsupportedOperationException();
}
@Override
public DataBuffer createConstantBuffer(int[] values, DataType desiredType) {
return createConstantBuffer(ArrayUtil.toLongArray(values), desiredType);
}
@Override
public DataBuffer createConstantBuffer(float[] values, DataType desiredType) {
return createConstantBuffer(ArrayUtil.toDoubles(values), desiredType);
}
@Override
public DataBuffer createConstantBuffer(double[] values, DataType desiredType) {
throw new UnsupportedOperationException();
}
@Override
public int useCount(DataBuffer buffer){
throw new UnsupportedOperationException();
}
public void setX(INDArray x, Op op, OpContext oc){
if(oc != null)
oc.setInputArray(0, x);
else
op.setX(x);
}
public INDArray getX(Op op, OpContext oc){
if( oc != null )
return oc.getInputArray(0);
return op.x();
}
public void setY(INDArray y, Op op, OpContext oc){
if(oc != null)
oc.setInputArray(1, y);
else
op.setY(y);
}
public INDArray getY(Op op, OpContext oc){
if( oc != null )
return oc.getInputArray(1);
return op.y();
}
public void setZ(INDArray z, Op op, OpContext oc){
if(oc != null)
oc.setOutputArray(0, z);
else
op.setZ(z);
}
public INDArray getZ(Op op, OpContext oc){
if( oc != null )
return oc.getOutputArray(0);
return op.z();
}
}