cavis/libnd4j/include/ops/declarable/generic/nn/lrn.cpp

82 lines
2.9 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
******************************************************************************/
//
// @author raver119 on 29/10/17
// @author GS <sgazeos@gmail.com> 2/16/18
// @author Yurii Shyrma (iuriish@yahoo.com) -> back prop author
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_lrn)
#include <ops/declarable/helpers/lrn.h>
#include <ops/declarable/CustomOperations.h>
namespace nd4j {
namespace ops {
DECLARE_TYPES(lrn) {
getOpDescriptor()
->setAllowedInputTypes(nd4j::DataType::ANY)
->setAllowedOutputTypes({ALL_FLOATS});
}
CONFIGURABLE_OP_IMPL(lrn, 1, 1, true, 3, 1) {
auto input = INPUT_VARIABLE(0);
auto output = OUTPUT_VARIABLE(0);
REQUIRE_TRUE(input->rankOf() == 4, 0, "lrn: Input rank of 4 expected, but got %i instead", input->rankOf());
// FIXME: double?
double alpha = T_ARG(1);
double beta = T_ARG(2);
double bias = T_ARG(0);
int depth = INT_ARG(0);
return helpers::lrnFunctor(block, input, output, depth, bias, alpha, beta);
}
DECLARE_TYPES(lrn_bp) {
getOpDescriptor()
->setAllowedInputTypes(nd4j::DataType::ANY)
->setAllowedOutputTypes({ALL_FLOATS});
}
CONFIGURABLE_OP_IMPL(lrn_bp, 2, 1, true, 3, 1) {
auto input = INPUT_VARIABLE(0);
auto gradO = INPUT_VARIABLE(1);
auto gradI = OUTPUT_VARIABLE(0);
REQUIRE_TRUE(input->rankOf() == 4, 0, "lrn_bp: Input rank of 4 expected, but got %i instead", input->rankOf());
REQUIRE_TRUE(input->isSameShape(gradO), 0, "lrn_bp: Both input and grad_output should have the same shape, but got %s and %s correspondingly !", ShapeUtils::shapeAsString(input).c_str(), ShapeUtils::shapeAsString(gradO).c_str());
// FIXME: double/float?
float bias = T_ARG(0);
float alpha = T_ARG(1);
float beta = T_ARG(2);
int depth = INT_ARG(0);
helpers::lrnBP(*input, *gradO, *gradI, depth, bias, alpha, beta);
return Status::OK();
}
DECLARE_SYN(local_response_normalization, lrn);
}
}
#endif