82 lines
3.1 KiB
Plaintext
82 lines
3.1 KiB
Plaintext
/*
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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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//
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// @author Yurii Shyrma (iuriish@yahoo.com)
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//
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#include<ops/declarable/helpers/gammaMathFunc.h>
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#include <array/NDArrayFactory.h>
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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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template<typename T>
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__global__ static void diGammaCuda(const void *vx, const Nd4jLong *xShapeInfo,
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void *vz, const Nd4jLong *zShapeInfo) {
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const auto x = reinterpret_cast<const T*>(vx);
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auto z = reinterpret_cast<T*>(vz);
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__shared__ Nd4jLong len;
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__shared__ bool sameOffset;
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if (threadIdx.x == 0) {
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len = shape::length(xShapeInfo);
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sameOffset = shape::haveSameShapeAndStrides(xShapeInfo, zShapeInfo);
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}
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__syncthreads();
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for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < len; i += gridDim.x * blockDim.x) {
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const auto xOffset = shape::getIndexOffset(i, xShapeInfo);
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const auto zOffset = sameOffset ? xOffset : shape::getIndexOffset(i, zShapeInfo);
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z[zOffset] = diGammaScalar<T>(x[xOffset]);
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}
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}
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///////////////////////////////////////////////////////////////////
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template<typename T>
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static void diGammaCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const cudaStream_t *stream, const void *vx, const Nd4jLong *xShapeInfo, void *vz, const Nd4jLong *zShapeInfo) {
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diGammaCuda<T><<<blocksPerGrid, threadsPerBlock, 1024, *stream>>>(vx, xShapeInfo, vz, zShapeInfo);
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}
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///////////////////////////////////////////////////////////////////
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void diGamma(sd::LaunchContext* context, const NDArray& x, NDArray& z) {
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int threadsPerBlock = MAX_NUM_THREADS / 2;
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int blocksPerGrid = (z.lengthOf() + threadsPerBlock - 1) / threadsPerBlock;
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NDArray::prepareSpecialUse({&z}, {&x});
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BUILD_SINGLE_SELECTOR(x.dataType(), diGammaCudaLauncher, (blocksPerGrid, threadsPerBlock, context->getCudaStream(), x.specialBuffer(), x.specialShapeInfo(), z.specialBuffer(), z.specialShapeInfo()), FLOAT_TYPES);
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NDArray::registerSpecialUse({&z}, {&x});
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}
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BUILD_SINGLE_TEMPLATE(template void diGammaCudaLauncher, (const int blocksPerGrid, const int threadsPerBlock, const cudaStream_t *stream, const void *vx, const Nd4jLong *xShapeInfo, void *vz, const Nd4jLong *zShapeInfo), FLOAT_TYPES);
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}
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}
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}
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