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

62 lines
2.2 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@gmail.com
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_apply_sgd)
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/gradient.h>
namespace nd4j {
namespace ops {
CONFIGURABLE_OP_IMPL(apply_sgd, 2, 1, true, -2, 0) {
auto parameters = INPUT_VARIABLE(0);
auto gradients = INPUT_VARIABLE(1);
double lr = 0.0;
REQUIRE_TRUE(parameters->isSameShape(gradients), 0, "ApplySGD: parameters and gradients should have the same shape, but got parameters = %s and gradients = %s !", ShapeUtils::shapeAsString(parameters).c_str(), ShapeUtils::shapeAsString(gradients).c_str());
if (block.width() == 3) {
auto tarr = INPUT_VARIABLE(2);
lr = tarr->e<double>(0);
} else if (block.getTArguments()->size() == 1) {
lr = T_ARG(0);
} else {
REQUIRE_TRUE(false, 0, "ApplyGradients op should have LR announced either es T argument or additional NDArray!");
}
auto Z = OUTPUT_VARIABLE(0);
helpers::applyGradientDescent(block.launchContext(), parameters, gradients, lr, Z);
return Status::OK();
}
DECLARE_SYN(ApplyGradientDescent, apply_sgd);
}
DECLARE_TYPES(apply_sgd) {
getOpDescriptor()
->setAllowedInputTypes({ALL_FLOATS})
->setAllowedOutputTypes({ALL_FLOATS});
}
}
#endif