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/*
* ******************************************************************************
* *
* *
* * 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;
import lombok.NonNull;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.autodiff.util.SameDiffUtils;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.memory.MemoryWorkspace;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.shape.LongShapeDescriptor;
import org.nd4j.linalg.api.shape.Shape;
import org.nd4j.linalg.factory.Nd4j;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
@Slf4j
public abstract class BaseScalarOp extends BaseOp implements ScalarOp {
public BaseScalarOp() {
this.scalarValue = Nd4j.scalar(0.f);
}
public BaseScalarOp(INDArray x, INDArray y, INDArray z, Number num) {
super(x, y, z);
if (x.isCompressed())
Nd4j.getCompressor().decompressi(x);
try(MemoryWorkspace ws = Nd4j.getMemoryManager().scopeOutOfWorkspaces()) {
this.scalarValue = Nd4j.scalar(x.dataType(), num);
}
}
public BaseScalarOp(INDArray x, Number num) {
super(x);
if (x.isCompressed())
Nd4j.getCompressor().decompressi(x);
try(MemoryWorkspace ws = Nd4j.getMemoryManager().scopeOutOfWorkspaces()) {
this.scalarValue = Nd4j.scalar(x.dataType(), num);
}
}
public BaseScalarOp(INDArray x, INDArray z, Number set) {
super(x, null, z);
if (x.isCompressed())
Nd4j.getCompressor().decompressi(x);
try(MemoryWorkspace ws = Nd4j.getMemoryManager().scopeOutOfWorkspaces()) {
this.scalarValue = Nd4j.scalar(x.dataType(), set);
}
}
public BaseScalarOp(SameDiff sameDiff,SDVariable i_v,Number scalar) {
this(sameDiff,i_v,scalar,false,null);
}
public BaseScalarOp(SameDiff sameDiff,SDVariable i_v,Number scalar,boolean inPlace) {
this(sameDiff,i_v,scalar,inPlace,null);
}
public BaseScalarOp(SameDiff sameDiff,
@NonNull SDVariable i_v,
Number scalar,
boolean inPlace,
Object[] extraArgs) {
super(sameDiff,inPlace,extraArgs);
this.scalarValue = Nd4j.scalar(i_v.dataType(), scalar);
this.xVertexId = i_v.name();
sameDiff.addArgsFor(new String[]{xVertexId},this);
SameDiffUtils.validateDifferentialFunctionSameDiff(sameDiff, i_v, this);
}
public BaseScalarOp(SameDiff sameDiff,
SDVariable i_v,
Number scalar,
Object[] extraArgs) {
this(sameDiff,i_v,scalar,false,extraArgs);
}
@Override
public INDArray z() {
return z;
}
@Override
public List calculateOutputShape() {
return calculateOutputShape(null);
}
@Override
public List calculateOutputShape(OpContext oc) {
INDArray x = oc != null ? oc.getInputArray(0) : x();
val ret = new ArrayList(1);
long[] s;
if(x != null){
s = x.shape();
} else {
s = arg().getShape();
}
val aT = arg().dataType();
val sT = scalarValue.dataType();
ret.add(LongShapeDescriptor.fromShape(s, Shape.pickPairwiseDataType(aT, sT)));
return ret;
}
@Override
public Type opType() {
return Type.SCALAR;
}
@Override
public void setScalar(Number scalar) {
this.scalarValue = Nd4j.scalar(x.dataType(), scalar);
}
@Override
public void setScalar(INDArray scalar){
this.scalarValue = scalar;
}
@Override
public INDArray scalar() {
if(y() != null && y().isScalar())
return y();
return scalarValue;
}
@Override
public int[] getDimension() {
return dimensions;
}
@Override
public void setDimension(int... dimension) {
defineDimensions(dimension);
}
@Override
public boolean validateDataTypes(boolean experimentalMode) {
if (y() != null) {
if (y().isR() || x().isR())
Preconditions.checkArgument(z().isR(), "Op.Z must have floating point type, since one of operands is floating point:" +
" x.dataType=%s, y.dataType=%s, z.dataType=%s, op=%s", x.dataType(), y.dataType(), z.dataType(), getClass().getName());
if (!experimentalMode)
Preconditions.checkArgument(x.dataType() == y.dataType() || y.dataType() == DataType.BOOL, "Op.X must have same data type as Op.Y");
} else if (x().isR())
Preconditions.checkArgument(z().isR(), "Op.Z must have floating point type, since one of operands is floating point:" +
" x.dataType=%s, z.dataType=%s, op=%s", x.dataType(), z.dataType(), getClass().getName());
return true;
}
@Override
public Type getOpType() {
return Type.SCALAR;
}
@Override
public List calculateOutputDataTypes(List dataTypes) {
//All scalar ops: output type is same as input type
Preconditions.checkState(dataTypes != null && dataTypes.size() >= 1, "Expected 1 or more input datatype %s, got input %s", getClass(), dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
}