text: /*******************************************************************************
   * Copyright (c) 2015-2018 Skymind, Inc.
   * Copyright (c) 2019 Konduit K.K.
   *
   * 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
   ******************************************************************************/
  
  //
  // 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 argumens map:
           * TArgs[0] - min for rng
           * TArgs[1] - max for rng
           */
          CUSTOM_OP_IMPL(randomuniform, 1, 1, true, 0, 0) {
              // uniform distribution
              auto rng = block.randomGenerator();
              auto dtype = DataType::FLOAT32;
              if (block.getIArguments()->size())
                  dtype = (DataType)INT_ARG(0);
  
              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