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

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2019-06-06 14:21:15 +02:00
/*******************************************************************************
* 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
******************************************************************************/
//
// @author raver119@gmail.com
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_split_v)
#include <ops/declarable/headers/parity_ops.h>
namespace nd4j {
namespace ops {
CUSTOM_OP_IMPL(split_v, 2, -1, false, 0, -2) {
auto input = INPUT_VARIABLE(0);
auto sizes = INPUT_VARIABLE(1);
int axis = 0;
if (block.getIArguments()->size() > 0) {
axis = INT_ARG(0);
} else if (block.width() > 2){
auto _a = INPUT_VARIABLE(2);
axis = _a->e<int>(0);
}
if (axis < 0)
axis += input->rankOf();
std::vector<int> dims = ShapeUtils::evalDimsToExclude(input->rankOf(), {axis});
int pos = 0;
std::vector<Nd4jLong> indices(2 * input->rankOf());
for (Nd4jLong e = 0; e < sizes->lengthOf(); e++) {
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int c_size = sizes->e<int>(e);
for (int d = 0; d < input->rankOf(); d++) {
if (d == axis)
indices[2*d + 1] = (indices[2*d] = pos) + c_size;
else
indices[2*d] = indices[2*d + 1] = 0;
}
auto output = OUTPUT_VARIABLE(e);
REQUIRE_TRUE(output->dataType() == input->dataType(), 0, "SplitV: all outputs must have same data type as input");
auto sub = (*input)(indices);
output->assign(sub);
pos += c_size;
}
//delete tads;
return Status::OK();
}
DECLARE_TYPES(split_v) {
getOpDescriptor()
->setAllowedInputTypes(0, {ALL_INTS, ALL_FLOATS})
->setAllowedInputTypes(1, {ALL_INTS})
->setAllowedInputTypes(2, {ALL_INTS})
->setAllowedOutputTypes({ALL_INTS, ALL_FLOATS});
}
DECLARE_SHAPE_FN(split_v) {
auto input = inputShape->at(0);
//auto sizes = inputShape->at(1);
auto shapeList = SHAPELIST();
int rank = shape::rank(input);
// 0 is just default axis
int axis = 0;
if (block.getIArguments()->size() > 0)
axis = INT_ARG(0);
else if (block.width() > 2) {
auto _a = INPUT_VARIABLE(2);
axis = _a->e<int>(0);
}
if (axis < 0)
axis += shape::rank(input);
// this op assumes we have sizes defined
auto sizes = INPUT_VARIABLE(1);
auto length = sizes->lengthOf();
int pos = 0;
for (Nd4jLong e = 0; e < length; e++) {
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int c_size = sizes->e<int>(e);
std::vector<Nd4jLong> shape(rank);
for (int d = 0; d < rank; d++) {
if (d != axis)
shape[d] = shape::sizeAt(input, d);
else
shape[d] = c_size;
}
auto newShape = ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(input), shape::order(input), shape);
shapeList->push_back(newShape);
}
return shapeList;
}
}
}
#endif