cavis/libnd4j/include/ops/declarable/generic/random/uniform.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
 *  *****************************************************************************
 */

//
// Created by raver119 on 29/10/17.
//

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

#include <ops/declarable/CustomOperations.h>
#include <helpers/RandomLauncher.h>
#include <ops/declarable/helpers/random.h>

namespace sd {
    namespace ops {
        ///////////////////////
        /**
         * uniform distribution
         * takes 1 ndarray
         *
         * T arguments map:
         * TArgs[0] - min for rng
         * TArgs[1] - max for rng
         */
        CUSTOM_OP_IMPL(randomuniform, -1, 1, true, 0, -2) {
            // uniform distribution
            auto rng = block.randomGenerator();
            auto dtype = DataType::FLOAT32;
            if (block.getIArguments()->size())
                dtype = (DataType)INT_ARG(0);

            if(block.getIArguments()->size() > 1) {
                auto seed = INT_ARG(1);
                rng.setStates(seed,seed ^ 0xdeadbeef);
                nd4j_debug("randomuniform: Setting seed %d\n",seed);
                //rng.setSeed(seed);
            }

            auto min = block.width() > 1 ? INPUT_VARIABLE(1) : (NDArray*) nullptr;
            auto max = block.width() > 2 ? INPUT_VARIABLE(2) : (NDArray*) nullptr;
            bool disposable = false;

            if (min == nullptr && max == nullptr && block.numT() >= 2) {
                min = NDArrayFactory::create_(dtype, block.launchContext());
                max = NDArrayFactory::create_(dtype, block.launchContext());
                min->p(0, T_ARG(0));
                max->p(0, T_ARG(1));
                disposable = true;
            }

            auto output = OUTPUT_VARIABLE(0);
            REQUIRE_TRUE(output->dataType() == dtype, 0, "RandomUniform: data type of output should be equals to given.");

            helpers::fillRandomUniform(block.launchContext(), rng, min, max, output);

            if (disposable) {
                delete min;
                delete max;
            }
            return Status::OK();
        }


        DECLARE_SHAPE_FN(randomuniform) {
            auto in = INPUT_VARIABLE(0);
            //auto min = INPUT_VARIABLE(1);
            auto shape = in->template asVectorT<Nd4jLong>();
            auto dtype = DataType::FLOAT32; //ArrayOptions::dataType(inputShape->at(1)); // output type is by given min

            if (block.getIArguments()->size())
                dtype = (DataType)INT_ARG(0);
            if (block.width() > 1)
                REQUIRE_TRUE(dtype == INPUT_VARIABLE(1)->dataType(), 0, "RandomUniform: data type of output and min/max args should be the same");

            auto newShape = ConstantShapeHelper::getInstance().createShapeInfo(dtype, 'c', shape);
            return SHAPELIST(newShape);
        }

        DECLARE_TYPES(randomuniform) {
            getOpDescriptor()
                    ->setAllowedInputTypes(0, {ALL_INTS})
                    ->setAllowedInputTypes(1, {ALL_INTS, ALL_FLOATS})
                    ->setAllowedInputTypes(2, {ALL_INTS, ALL_FLOATS})
                    ->setAllowedOutputTypes({ALL_FLOATS, ALL_INTS});
        }
    }
}

#endif