97 lines
4.3 KiB
C++
97 lines
4.3 KiB
C++
|
/*
|
||
|
|
* ******************************************************************************
|
||
|
|
* *
|
||
|
|
* *
|
||
|
|
* * 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 Oleh Semeniv (oleg.semeniv@gmail.com)
|
||
|
|
// @author Abdelrauf(rauf@konduit.ai)
|
||
|
|
|
||
|
|
#include <ops/declarable/headers/updaters.h>
|
||
|
|
#include <ops/declarable/CustomOperations.h>
|
||
|
|
#include <helpers/ConstantTadHelper.h>
|
||
|
|
#include <execution/Threads.h>
|
||
|
|
#include <array/NDArray.h>
|
||
|
|
|
||
|
|
namespace sd {
|
||
|
|
namespace ops {
|
||
|
|
|
||
|
|
CONFIGURABLE_OP_IMPL(adabelief_updater, 3, 3, true, 0, 0) {
|
||
|
|
|
||
|
|
const auto gradient = INPUT_VARIABLE(0);
|
||
|
|
const auto initStateU = INPUT_VARIABLE(1);
|
||
|
|
const auto initStateM = INPUT_VARIABLE(2);
|
||
|
|
|
||
|
|
auto update = OUTPUT_VARIABLE(0);
|
||
|
|
auto stateU = OUTPUT_VARIABLE(1);
|
||
|
|
auto stateM = OUTPUT_VARIABLE(2);
|
||
|
|
|
||
|
|
// todo maybe we need an error like on Java side
|
||
|
|
if (gradient->isEmpty() || initStateU->isEmpty() || initStateM->isEmpty())
|
||
|
|
return Status::OK();
|
||
|
|
|
||
|
|
REQUIRE_TRUE(gradient->isSameShape(initStateU), 0, "ADABELIEF UPDATER OP: input state V must have the same shape as gradient,"
|
||
|
|
" expected shape %s, but got %s!", ShapeUtils::shapeAsString(gradient->shapeInfo()).c_str(),
|
||
|
|
ShapeUtils::shapeAsString(initStateU->shapeInfo()).c_str());
|
||
|
|
REQUIRE_TRUE(gradient->isSameShape(initStateM), 0, "ADABELIEF UPDATER OP: input state M must have the same shape as gradient,"
|
||
|
|
" expected shape %s, but got %s!", ShapeUtils::shapeAsString(gradient->shapeInfo()).c_str(),
|
||
|
|
ShapeUtils::shapeAsString(initStateM->shapeInfo()).c_str());
|
||
|
|
|
||
|
|
bool bParamsSupply = 7 == block.width() || 4 == block.getTArguments()->size();
|
||
|
|
|
||
|
|
auto iteration = block.getIArguments()->size() > 0 ? INT_ARG(0) : 0;
|
||
|
|
|
||
|
|
REQUIRE_TRUE(bParamsSupply, 0, "ADABELIEF UPDATER OP: learning rate, beta 1, beta 2 and epsilon were not provided!");
|
||
|
|
|
||
|
|
double dLr, dBeta1, dBeta2, dEpsilon;
|
||
|
|
|
||
|
|
if (block.width() > 3) {
|
||
|
|
const auto lr = INPUT_VARIABLE(3);
|
||
|
|
const auto beta1 = INPUT_VARIABLE(4);
|
||
|
|
const auto beta2 = INPUT_VARIABLE(5);
|
||
|
|
const auto epsilon = INPUT_VARIABLE(6);
|
||
|
|
|
||
|
|
REQUIRE_TRUE(lr->isScalar(), 0, "ADABELIEF UPDATER OP: Learning rate has to be a scalar, but instead got rank %i!", lr->rankOf());
|
||
|
|
REQUIRE_TRUE(beta1->isScalar(), 0, "ADABELIEF UPDATER OP: beta 1 has to be a scalar, but instead got rank %i!", beta1->rankOf());
|
||
|
|
REQUIRE_TRUE(beta2->isScalar(), 0, "ADABELIEF UPDATER OP: beta 2 has to be a scalar, but instead got rank %i!", beta2->rankOf());
|
||
|
|
REQUIRE_TRUE(epsilon->isScalar(), 0, "ADABELIEF UPDATER OP: Epsilon has to be a scalar, but instead got rank %i!", epsilon->rankOf());
|
||
|
|
|
||
|
|
dLr = lr->e<double>(0);
|
||
|
|
dBeta1 = beta1->e<double>(0);
|
||
|
|
dBeta2 = beta2->e<double>(0);
|
||
|
|
dEpsilon = epsilon->e<double>(0);
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
dLr = T_ARG(0);
|
||
|
|
dBeta1 = T_ARG(1);
|
||
|
|
dBeta2 = T_ARG(2);
|
||
|
|
dEpsilon = T_ARG(3);
|
||
|
|
}
|
||
|
|
|
||
|
|
helpers::updaterAdaBelief(block.launchContext(), *gradient, *initStateU, *initStateM, *update, *stateU, *stateM, dLr, dBeta1, dBeta2, dEpsilon, iteration);
|
||
|
|
return Status::OK();
|
||
|
|
}
|
||
|
|
|
||
|
|
DECLARE_TYPES(adabelief_updater) {
|
||
|
|
getOpDescriptor()->setAllowedInputTypes({ ALL_FLOATS })
|
||
|
|
->setSameMode(true);
|
||
|
|
}
|
||
|
|
|
||
|
|
}
|
||
|
|
}
|