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deeplearning4j--deeplearning4j/libnd4j/include/ops/declarable/generic/tests/testcustom.cpp
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2026-07-13 12:47:05 +08:00

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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
******************************************************************************/
//
// @author raver119@gmail.com
//
#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_testcustom)
#include <ops/declarable/headers/tests.h>
namespace sd {
namespace ops {
//////////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(testcustom, 1, 1, false, 0, -1) {
auto z = this->getZ(block);
STORE_RESULT(*z);
return Status::OK;
}
DECLARE_SHAPE_FN(testcustom) {
// this test op will just return back original shape doubled
LongType *shapeOf;
ALLOCATE(shapeOf, block.getWorkspace(), shape::rank(inputShape->at(0)), sd::LongType);
for (int e = 0; e < shape::rank(inputShape->at(0)); e++) shapeOf[e] = inputShape->at(0)[e + 1] * 2;
auto newShape = ConstantShapeHelper::getInstance().createShapeInfo(block.dataType(), 'c',
shape::rank(inputShape->at(0)), shapeOf, -1);
RELEASE(shapeOf, block.getWorkspace());
return SHAPELIST(newShape);
}
DECLARE_TYPES(testcustom) { getOpDescriptor()->setAllowedInputTypes(ANY)->setSameMode(true); }
} // namespace ops
} // namespace sd
#endif