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org.nd4j.linalg.api.ops.BaseReduceBoolOp Maven / Gradle / Ivy
/*******************************************************************************
* 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.nd4j.linalg.api.ops;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.shape.LongShapeDescriptor;
import org.nd4j.linalg.api.shape.Shape;
import java.util.Collections;
import java.util.List;
public abstract class BaseReduceBoolOp extends BaseReduceOp implements ReduceBoolOp {
public BaseReduceBoolOp(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions) {
super(sameDiff, i_v, i_v2, dimensions);
}
protected BaseReduceBoolOp(SameDiff sameDiff, SDVariable input, int[] dimensions, boolean keepDims) {
super(sameDiff, input, dimensions, keepDims);
}
protected BaseReduceBoolOp(SameDiff sameDiff, SDVariable input, int... dimensions) {
super(sameDiff, input, dimensions);
}
public BaseReduceBoolOp(INDArray x, INDArray z, boolean keepDims, int[] dimensions) {
super(x, null, z, keepDims, dimensions);
}
public BaseReduceBoolOp(INDArray x, int... dimensions) {
this(x, null, false, dimensions);
}
public BaseReduceBoolOp(INDArray x, INDArray z, int... dimensions) {
this(x, z, false, dimensions);
}
protected BaseReduceBoolOp() {
super();
}
@Override
public Type opType() {
return Type.REDUCE_BOOL;
}
@Override
public Type getOpType() {
return opType();
}
@Override
public DataType resultType() {
return DataType.BOOL;
}
@Override
public DataType resultType(OpContext oc) {
return DataType.BOOL;
}
@Override
public boolean validateDataTypes(OpContext oc) {
INDArray x = oc != null ? oc.getInputArray(0) : x();
INDArray y = oc != null ? oc.getInputArray(1) : y();
if (y != null)
Preconditions.checkArgument(x.dataType() == y.dataType(),"Op.X type must be the same as Op.Y:" +
" x.dataType=%s, y.dataType=%s, op=%s", x.dataType(), y.dataType(), getClass().getName());
INDArray z = oc != null ? oc.getOutputArray(0) : z();
if (z != null)
Preconditions.checkArgument(z.isB(), "Op.Z type must be bool: got type %s for op %s", z.dataType(), getClass());
return true;
}
@Override
public List calculateOutputShape() {
return calculateOutputShape(null);
}
@Override
public List calculateOutputShape(OpContext oc) {
INDArray x = oc != null ? oc.getInputArray(0) : x();
if(x == null)
return Collections.emptyList();
//Calculate reduction shape. Note that reduction on scalar - returns a scalar
long[] reducedShape = x.rank() == 0 ? x.shape() : Shape.getReducedShape(x.shape(),dimensions, isKeepDims());
return Collections.singletonList(LongShapeDescriptor.fromShape(reducedShape, DataType.BOOL));
}
@Override
public List calculateOutputDataTypes(List dataTypes){
//All reduce bool: always bool output type. 2nd input is axis arg
Preconditions.checkState(dataTypes != null && (dataTypes.size() == 1 || dataTypes.size() == 2),
"Expected 1 or input datatype for %s, got input %s", getClass(), dataTypes);
Preconditions.checkState(dataTypes.size() == 1 || dataTypes.get(1).isIntType(), "When executing reductions" +
"with 2 inputs, second input (axis) must be an integer datatype for %s, got %s", getClass(), dataTypes);
return Collections.singletonList(DataType.BOOL);
}
public abstract boolean emptyValue();
}
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