deeplearning4j/deeplearning4j

/*
 *  ******************************************************************************
 *  *
 *  *
 *  * 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)
//

#include <array/NDArray.h>
#include <execution/Threads.h>
#include <helpers/ConstantTadHelper.h>
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/headers/updaters.h>
#if NOT_EXCLUDED(OP_ams_grad_updater)
namespace sd {
namespace ops {

CONFIGURABLE_OP_IMPL(ams_grad_updater, 4, 4, true, 0, 0) {
  const auto gradient = INPUT_VARIABLE(0);
  const auto initStateV = INPUT_VARIABLE(1);
  const auto initStateM = INPUT_VARIABLE(2);
  const auto initStateH = INPUT_VARIABLE(3);

  auto update = OUTPUT_VARIABLE(0);
  auto stateV = OUTPUT_VARIABLE(1);
  auto stateM = OUTPUT_VARIABLE(2);
  auto stateH = OUTPUT_VARIABLE(3);

  // todo maybe we need an error like on Java side
  if (gradient->isEmpty() || initStateV->isEmpty() || initStateM->isEmpty() || initStateH->isEmpty())
    return sd::Status::OK;

  REQUIRE_TRUE(gradient->isSameShape(initStateV), 0,
               "AMSGRAD UPDATER OP: input state Msg must have the same shape as gradient,"
               "  expected shape %s, but got %s!",
               ShapeUtils::shapeAsString(gradient->shapeInfo()).c_str(),
               ShapeUtils::shapeAsString(initStateV->shapeInfo()).c_str());
  REQUIRE_TRUE(gradient->isSameShape(initStateM), 0,
               "AMSGRAD UPDATER OP: input state Msdx 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());
  REQUIRE_TRUE(gradient->isSameShape(initStateH), 0,
               "AMSGRAD UPDATER OP: input state Msdx must have the same shape as gradient!,"
               "  expected shape %s, but got %s!",
               ShapeUtils::shapeAsString(gradient->shapeInfo()).c_str(),
               ShapeUtils::shapeAsString(initStateH->shapeInfo()).c_str());

  bool bParamsSupply = 8 == block.width() || 4 == block.getTArguments()->size();

  auto iteration = block.getIArguments()->size() > 0 ? INT_ARG(0) : 0;

  REQUIRE_TRUE(bParamsSupply, 0, "AMSGRAD UPDATER OP: learning rate, beta 1, beta 2 and epsilon were not provided!");

  double dLr, dBeta1, dBeta2, dEpsilon;

  if (block.width() > 4) {
    const auto lr = INPUT_VARIABLE(4);
    const auto beta1 = INPUT_VARIABLE(5);
    const auto beta2 = INPUT_VARIABLE(6);
    const auto epsilon = INPUT_VARIABLE(7);

    REQUIRE_TRUE(lr->isScalar(), 0, "AMSGRAD UPDATER OP: Learning rate has to be a scalar, but instead got rank %i!",
                 lr->rankOf());
    REQUIRE_TRUE(beta1->isScalar(), 0, "AMSGRAD UPDATER OP: beta 1 has to be a scalar, but instead got rank %i!",
                 beta1->rankOf());
    REQUIRE_TRUE(beta2->isScalar(), 0, "AMSGRAD UPDATER OP: beta 2 has to be a scalar, but instead got rank %i!",
                 beta2->rankOf());
    REQUIRE_TRUE(epsilon->isScalar(), 0, "AMSGRAD 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::updaterAmsGrad(block.launchContext(), *gradient, *initStateV, *initStateM, *initStateH, *update, *stateV,
                          *stateM, *stateH, dLr, dBeta1, dBeta2, dEpsilon, iteration);
  return sd::Status::OK;
}

DECLARE_TYPES(ams_grad_updater) { getOpDescriptor()->setAllowedInputTypes({ALL_FLOATS})->setSameMode(true); }

}  // namespace ops
}  // namespace sd

#endif