cavis/libnd4j/include/ops/declarable/helpers/cuda/diGamma.cu

79 lines
3.0 KiB
Plaintext

/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
* Copyright (c) 2019 Konduit K.K.
*
* 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.
*
* 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
******************************************************************************/
//
// @author Yurii Shyrma (iuriish@yahoo.com)
//
#include<ops/declarable/helpers/gammaMathFunc.h>
#include <NDArrayFactory.h>
namespace nd4j {
namespace ops {
namespace helpers {
///////////////////////////////////////////////////////////////////
template<typename T>
__global__ static void diGammaCuda(const void *vx, const Nd4jLong *xShapeInfo,
void *vz, const Nd4jLong *zShapeInfo) {
const auto x = reinterpret_cast<const T*>(vx);
auto z = reinterpret_cast<T*>(vz);
__shared__ Nd4jLong len;
__shared__ bool sameOffset;
if (threadIdx.x == 0) {
len = shape::length(xShapeInfo);
sameOffset = shape::haveSameShapeAndStrides(xShapeInfo, zShapeInfo);
}
__syncthreads();
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < len; i += gridDim.x * blockDim.x) {
const auto xOffset = shape::getIndexOffset(i, xShapeInfo);
const auto zOffset = sameOffset ? xOffset : shape::getIndexOffset(i, zShapeInfo);
z[zOffset] = diGammaScalar<T>(x[xOffset]);
}
}
///////////////////////////////////////////////////////////////////
template<typename T>
static void diGammaCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const cudaStream_t *stream, const void *vx, const Nd4jLong *xShapeInfo, void *vz, const Nd4jLong *zShapeInfo) {
diGammaCuda<T><<<blocksPerGrid, threadsPerBlock, 1024, *stream>>>(vx, xShapeInfo, vz, zShapeInfo);
}
///////////////////////////////////////////////////////////////////
void diGamma(nd4j::LaunchContext* context, const NDArray& x, NDArray& z) {
int threadsPerBlock = MAX_NUM_THREADS / 2;
int blocksPerGrid = (z.lengthOf() + threadsPerBlock - 1) / threadsPerBlock;
NDArray::prepareSpecialUse({&z}, {&x});
BUILD_SINGLE_SELECTOR(x.dataType(), diGammaCudaLauncher, (blocksPerGrid, threadsPerBlock, context->getCudaStream(), x.getSpecialBuffer(), x.getSpecialShapeInfo(), z.getSpecialBuffer(), z.getSpecialShapeInfo()), FLOAT_TYPES);
NDArray::registerSpecialUse({&z}, {&x});
}
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);
}
}
}