cavis/libnd4j/include/ops/declarable/generic/random/poisson.cpp

/* ******************************************************************************
 *
 *
 * 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 George A. Shulinok <sgazeos@gmail.com>
//

#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_random_poisson)

#include <ops/declarable/headers/random.h>
#include <ops/declarable/helpers/random.h>

namespace sd {
    namespace ops {
        CUSTOM_OP_IMPL(random_poisson, 2, 1, false, 0, 0) {
            // gamma distribution
            auto rng = block.randomGenerator();
            auto shape = INPUT_VARIABLE(0);
            auto lambda = INPUT_VARIABLE(1);
            auto output = OUTPUT_VARIABLE(0);
            auto seed = 0;
            if (block.getIArguments()->size()) {
                seed = INT_ARG(0);
            }
            rng.setSeed(seed);
            helpers::fillRandomPoisson(block.launchContext(), rng, lambda, output);

            return Status::OK();
        }


        DECLARE_SHAPE_FN(random_poisson) {
            auto in = INPUT_VARIABLE(0);
            auto shape = in->template asVectorT<Nd4jLong>();
            auto lambdaShape = inputShape->at(1);
            auto dtype = block.numD() > 0? D_ARG(0) : ArrayOptions::dataType(lambdaShape);
            for (auto d = 0; d < shape::rank(lambdaShape); ++d ) {
                shape.emplace_back(shape::sizeAt(lambdaShape, d));
            }
            auto newShape = ConstantShapeHelper::getInstance().createShapeInfo(dtype, 'c', shape);
            return SHAPELIST(newShape);
        }

        DECLARE_TYPES(random_poisson) {
            getOpDescriptor()
                    ->setAllowedInputTypes(0, {ALL_INTS})
                    ->setAllowedInputTypes(1, {ALL_FLOATS})
                    ->setAllowedOutputTypes({ALL_FLOATS});
        }
    }
}

#endif