78 lines
2.7 KiB
C++
78 lines
2.7 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author raver119@gmail.com
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//
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#include <op_boilerplate.h>
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#if NOT_EXCLUDED(OP_random_exponential)
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#include <ops/declarable/headers/random.h>
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#include <helpers/RandomLauncher.h>
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namespace nd4j {
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namespace ops {
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CUSTOM_OP_IMPL(random_exponential, 1, 1, true, 1, 0) {
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// uniform distribution
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auto rng = block.randomGenerator();
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// FIXME: to be implemented
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/*
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if (rng == nullptr)
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return Status::THROW("RNG is null, aborting...");
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auto x = INPUT_VARIABLE(0);
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auto z = OUTPUT_VARIABLE(0);
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if (block.width() == 1)
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functions::random::RandomFunction<T>::template execTransform<randomOps::ExponentialDistribution<T>>(block.getRNG(), z->getBuffer(), z->getShapeInfo(), block.getTArguments()->data());
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else {
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auto y = INPUT_VARIABLE(1);
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REQUIRE_TRUE(y->isSameShape(z), 0, "ExponentialDistribution: Y shape should be equal to Z shape");
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functions::random::RandomFunction<T>::template execTransform<randomOps::ExponentialDistribution<T>>(block.getRNG(), y->getBuffer(), y->getShapeInfo(), z->getBuffer(), z->getShapeInfo(), block.getTArguments()->data());
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}
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STORE_RESULT(*z);
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*/
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auto z = OUTPUT_VARIABLE(0);
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auto lambda = T_ARG(0);
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RandomLauncher::fillExponential(block.launchContext(), rng, z, lambda);
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return Status::OK();
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}
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DECLARE_SHAPE_FN(random_exponential) {
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auto in = INPUT_VARIABLE(0);
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auto shape = in->template asVectorT<Nd4jLong>();
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auto newShape = ConstantShapeHelper::getInstance()->createShapeInfo(block.dataType(), 'c', shape);
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return SHAPELIST(newShape);
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}
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DECLARE_TYPES(random_exponential) {
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getOpDescriptor()
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->setAllowedInputTypes(nd4j::DataType::ANY)
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->setAllowedOutputTypes({ALL_FLOATS});
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}
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}
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}
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#endif |