96 lines
2.9 KiB
C++
96 lines
2.9 KiB
C++
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/*******************************************************************************
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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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// Created by Yurii Shyrma on 12.12.2017
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//
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#include<ops/declarable/helpers/polyGamma.h>
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#include<ops/declarable/helpers/zeta.h>
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#include <NDArrayFactory.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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//////////////////////////////////////////////////////////////////////////
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// calculate factorial
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template <typename T>
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static FORCEINLINE T getFactorial(const int n) {
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if (n < 0)
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throw std::runtime_error("factorial is not defined for negative number !");
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if(n==0 || n==1)
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return (T)1.f;
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T result = (T)1.f;
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PRAGMA_OMP_PARALLEL_FOR_SIMD_REDUCTION(prodT : result)
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for(int i = 2; i <= n; ++i)
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result *= i;
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return result;
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}
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//////////////////////////////////////////////////////////////////////////
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// implementation is based on serial representation written in terms of the Hurwitz zeta function as polygamma = (-1)^{n+1} * n! * zeta(n+1, x)
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template <typename T>
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static FORCEINLINE T polyGammaScalar(nd4j::LaunchContext * context, const int n, const T x) {
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// if (n < 0)
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// throw("polyGamma function: n must be >= 0 !");
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// if (x <= (T)0.)
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// throw("polyGamma function: x must be > 0 !");
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// TODO case for n = 0 (digamma)
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int sign = (n + 1) % 2 ? -1 : 1;
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// T factorial = (T)std::tgamma(n + 1);
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return sign * getFactorial<T>(n) * zetaScalar<T>((T)(n + 1), x);
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}
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//////////////////////////////////////////////////////////////////////////
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// calculate polygamma function for arrays
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template <typename T>
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static void polyGamma_(nd4j::LaunchContext * context, const NDArray& n, const NDArray& x, NDArray& output) {
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NDArray& result = output;
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int xLen = x.lengthOf();
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PRAGMA_OMP_PARALLEL_FOR_IF(xLen > Environment::getInstance()->elementwiseThreshold())
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for(int i = 0; i < x.lengthOf(); ++i)
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result.p(i, polyGammaScalar<T>(context, n.e<int>(i), x.e<T>(i)));
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// return result;
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}
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void polyGamma(nd4j::LaunchContext * context, const NDArray& n, const NDArray& x, NDArray& output) {
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BUILD_SINGLE_SELECTOR(x.dataType(), polyGamma_, (context, n, x, output), FLOAT_TYPES);
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}
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BUILD_SINGLE_TEMPLATE(template void polyGamma_, (nd4j::LaunchContext * context, const NDArray& n, const NDArray& x, NDArray& output), FLOAT_TYPES);
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}
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}
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}
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