cavis/libnd4j/include/ops/declarable/generic/parity_ops/sequence_mask.cpp

109 lines
4.0 KiB
C++

/* ******************************************************************************
*
*
* 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
******************************************************************************/
//
// Created to use with batched tensor by GS <sgazeos@gmail.com> 3/27/2018
//
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/sequence_mask.h>
namespace sd {
namespace ops {
CUSTOM_OP_IMPL(sequence_mask, 1, 1, false, 0, 0) {
auto input = INPUT_VARIABLE(0);
auto output = OUTPUT_NULLIFIED(0);
const int inRank = input->rankOf();
//REQUIRE_TRUE(inRank >= 1, 0, "sequence_mask: input array must have rank >= 1, but %i given!", inRank);
Nd4jLong maxInd = input->argMax();
float max = input->e<float>(maxInd);
if (block.getIArguments()->size() > 0) {
maxInd = INT_ARG(0);
if (maxInd < max)
maxInd = static_cast<Nd4jLong>(max);
}
else if (block.width() > 1) {
auto maxlen = INPUT_VARIABLE(1);
//REQUIRE_TRUE(maxlen->lengthOf() == 1, "sequence_mask: 2nd input (max length) should be a scalar array.");
float tmaxlen = maxlen->e<float>(0);
if (tmaxlen > max)
maxInd = static_cast<Nd4jLong>(tmaxlen);
}
else
maxInd = static_cast<Nd4jLong>(max);
helpers::sequenceMask(block.launchContext(), input, output, maxInd);
return Status::OK();
}
DECLARE_SHAPE_FN(sequence_mask) {
Nd4jLong* outShapeInfo = nullptr;
auto in = inputShape->at(0);
int outRank = shape::rank(in) + 1;
auto input = INPUT_VARIABLE(0);
auto dtype = DataType::BOOL;
auto argMaxInd = input->argMax();
Nd4jLong max = input->e<Nd4jLong>(argMaxInd);
Nd4jLong maxInd = max;
if (block.numD() > 0)
dtype = D_ARG(0);
if (block.width() > 1) {
auto maxlen = INPUT_VARIABLE(1);
Nd4jLong tmaxlen = maxlen->e<Nd4jLong>(0);
if (tmaxlen > max)
maxInd = static_cast<Nd4jLong>(tmaxlen);
if (block.numI() > 0) {
dtype = (DataType) INT_ARG(0);
}
}
else {
if (block.numI() > 0) {
maxInd = INT_ARG(0);
}
if (maxInd < max)
maxInd = max;
if (block.numI() > 1)
dtype = (DataType)INT_ARG(1); // to work with legacy code
}
int lastDimension = maxInd;
ALLOCATE(outShapeInfo, block.getWorkspace(), shape::shapeInfoLength(outRank), Nd4jLong);
outShapeInfo[0] = outRank;
for(int i = 0; i < outRank - 1; ++i)
outShapeInfo[i + 1] = shape::sizeAt(in, i);
outShapeInfo[outRank] = lastDimension;
ShapeUtils::updateStridesAndType(outShapeInfo, dtype, shape::order(in));
return SHAPELIST(CONSTANT(outShapeInfo));
}
DECLARE_TYPES(sequence_mask) {
getOpDescriptor()
->setAllowedInputTypes({ALL_INTS})
->setAllowedOutputTypes(sd::DataType::ANY);
}
}
}