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/* ******************************************************************************
*
*
* 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 Yurii Shyrma on 12.12.2017
//
#include <array/NDArrayFactory.h>
#include <execution/Threads.h>
#include <ops/declarable/helpers/gammaMathFunc.h>
#include <ops/declarable/helpers/zeta.h>
#if NOT_EXCLUDED(OP_polygamma)
namespace sd {
namespace ops {
namespace helpers {
//////////////////////////////////////////////////////////////////////////
// calculate factorial
template <typename T>
static SD_INLINE T getFactorial(const int n) {
if (n < 0) THROW_EXCEPTION("factorial is not defined for negative number !");
if (n == 0 || n == 1) return (T)1.f;
T result = (T)1.f;
for (int i = 2; i <= n; ++i) result *= i;
return result;
}
//////////////////////////////////////////////////////////////////////////
// implementation is based on serial representation written in terms of the Hurwitz zeta function as polygamma =
// (-1)^{n+1} * n! * zeta(n+1, x)
template <typename T>
static SD_INLINE T polyGammaScalar(sd::LaunchContext* context, const int n, const T x) {
int sign = (n + 1) % 2 ? -1 : 1;
T zeta = zetaScalar<T>(T(n + 1), x);
return T(sign) * getFactorial<T>(n) * zeta;
}
//////////////////////////////////////////////////////////////////////////
// calculate polygamma function for arrays
template <typename T>
static void polyGamma_(sd::LaunchContext* context, NDArray& n, NDArray& x, NDArray& output) {
auto func = PRAGMA_THREADS_FOR {
for (auto i = start; i < stop; i++) {
const T order = n.e<T>(i);
if (order !=
static_cast<int>(order)) // if order has fractional part then do not perform calculations and return NAN
output.p(i, std::numeric_limits<T>::quiet_NaN());
else if (order == 0) // polygamma function of zero order is digamma function
output.p(i, diGammaScalar<T>(x.e<T>(i)));
else
output.p(i, polyGammaScalar<T>(context, order, x.e<T>(i)));
}
};
samediff::Threads::parallel_for(func, 0, x.lengthOf());
}
void polyGamma(sd::LaunchContext* context, NDArray& n, NDArray& x, NDArray& output) {
BUILD_SINGLE_SELECTOR(x.dataType(), polyGamma_, (context, n, x, output), SD_FLOAT_TYPES);
}
BUILD_SINGLE_TEMPLATE( void polyGamma_,
(sd::LaunchContext * context, NDArray& n, NDArray& x, NDArray& output),
SD_FLOAT_TYPES);
} // namespace helpers
} // namespace ops
} // namespace sd
#endif