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deeplearning4j--deeplearning4j/libnd4j/include/ops/declarable/generic/nn/activations/cube.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_cube)
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/legacy_helpers.h>
namespace sd {
namespace ops {
CONFIGURABLE_OP_IMPL(cube, 1, 1, true, 0, 0) {
auto input = INPUT_VARIABLE(0);
auto output = OUTPUT_VARIABLE(0);
input->applyTransform(transform::Cube, output);
STORE_RESULT(output);
return Status::OK;
}
DECLARE_TYPES(cube) { getOpDescriptor()->setAllowedInputTypes(0, ANY)->setSameMode(true); }
CONFIGURABLE_OP_IMPL(cube_bp, 2, 1, true, 0, 0) {
auto input = INPUT_VARIABLE(0);
auto epsilon = INPUT_VARIABLE(1);
auto z = OUTPUT_VARIABLE(0);
helpers::cubeDerivative(block.launchContext(), input, epsilon, z);
return Status::OK;
}
DECLARE_TYPES(cube_bp) {
getOpDescriptor()
->setAllowedInputTypes(0, ANY)
->setAllowedInputTypes(1, {FLOAT32, DOUBLE, HALF})
->setAllowedOutputTypes(0, {FLOAT32, DOUBLE, HALF});
}
} // namespace ops
} // namespace sd
#endif