chore: import upstream snapshot with attribution
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/* ******************************************************************************
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*
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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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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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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 <array/NDArrayFactory.h>
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#include <execution/Threads.h>
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#include <ops/declarable/helpers/gammaMathFunc.h>
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#include <ops/declarable/helpers/zeta.h>
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#if NOT_EXCLUDED(OP_polygamma)
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namespace sd {
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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 SD_INLINE T getFactorial(const int n) {
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if (n < 0) THROW_EXCEPTION("factorial is not defined for negative number !");
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if (n == 0 || n == 1) return (T)1.f;
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T result = (T)1.f;
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for (int i = 2; i <= n; ++i) 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 =
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// (-1)^{n+1} * n! * zeta(n+1, x)
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template <typename T>
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static SD_INLINE T polyGammaScalar(sd::LaunchContext* context, const int n, const T x) {
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int sign = (n + 1) % 2 ? -1 : 1;
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T zeta = zetaScalar<T>(T(n + 1), x);
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return T(sign) * getFactorial<T>(n) * zeta;
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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_(sd::LaunchContext* context, NDArray& n, NDArray& x, NDArray& output) {
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auto func = PRAGMA_THREADS_FOR {
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for (auto i = start; i < stop; i++) {
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const T order = n.e<T>(i);
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if (order !=
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static_cast<int>(order)) // if order has fractional part then do not perform calculations and return NAN
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output.p(i, std::numeric_limits<T>::quiet_NaN());
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else if (order == 0) // polygamma function of zero order is digamma function
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output.p(i, diGammaScalar<T>(x.e<T>(i)));
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else
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output.p(i, polyGammaScalar<T>(context, order, x.e<T>(i)));
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}
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};
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samediff::Threads::parallel_for(func, 0, x.lengthOf());
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}
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void polyGamma(sd::LaunchContext* context, NDArray& n, NDArray& x, NDArray& output) {
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BUILD_SINGLE_SELECTOR(x.dataType(), polyGamma_, (context, n, x, output), SD_FLOAT_TYPES);
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}
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BUILD_SINGLE_TEMPLATE( void polyGamma_,
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(sd::LaunchContext * context, NDArray& n, NDArray& x, NDArray& output),
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SD_FLOAT_TYPES);
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} // namespace helpers
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} // namespace ops
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} // namespace sd
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#endif
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