cavis/libnd4j/include/ops/declarable/generic/loss/l2_loss.cpp

52 lines
1.7 KiB
C++

/*******************************************************************************
* 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
******************************************************************************/
//
// Created by GS <sgazeos@gmail.com> 31.01.2018
//
#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_l2_loss)
#include <ops/declarable/CustomOperations.h>
namespace sd {
namespace ops {
CUSTOM_OP_IMPL(l2_loss, 1, 1, false, 0, 0) {
auto input = INPUT_VARIABLE(0);
auto output = OUTPUT_VARIABLE(0);
REQUIRE_TRUE(output->isScalar(), 0, "Rank output should be scalar");
// FIXME: output should be used directly here, to avoid sum
input->reduceNumber(reduce::SquaredNorm, *output);
(*output) /= 2.;
return Status::OK();
}
DECLARE_SHAPE_FN(l2_loss) {
return SHAPELIST(ConstantShapeHelper::getInstance().scalarShapeInfo(ArrayOptions::dataType(inputShape->at(0))));
}
DECLARE_TYPES(l2_loss) {
getOpDescriptor()
->setAllowedInputTypes(sd::DataType::ANY)
->setAllowedOutputTypes({ALL_FLOATS});
}
}
}
#endif