222 lines
9.1 KiB
Plaintext
222 lines
9.1 KiB
Plaintext
/*******************************************************************************
|
|
* Copyright (c) 2015-2018 Skymind, Inc.
|
|
*
|
|
* 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 raver119@gmail.com
|
|
// @author Yurii Shyrma (iuriish@yahoo.com)
|
|
//
|
|
|
|
#include <ops/declarable/helpers/adjust_hue.h>
|
|
#include <helpers/ConstantTadHelper.h>
|
|
#include <PointersManager.h>
|
|
|
|
namespace nd4j {
|
|
namespace ops {
|
|
namespace helpers {
|
|
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
template <typename T>
|
|
static void _CUDA_G adjustHueCuda(const void* vx, const Nd4jLong* xShapeInfo, const Nd4jLong* xTadOffsets,
|
|
void* vz, const Nd4jLong *zShapeInfo, const Nd4jLong* zTadOffsets,
|
|
const Nd4jLong numOfTads, const T delta, const int dimC) {
|
|
|
|
const T* x = reinterpret_cast<const T*>(vx);
|
|
T* z = reinterpret_cast<T*>(vz);
|
|
|
|
__shared__ int rank;
|
|
__shared__ Nd4jLong xDimCstride, zDimCstride;
|
|
|
|
if (threadIdx.x == 0) {
|
|
rank = shape::rank(xShapeInfo);
|
|
xDimCstride = shape::stride(xShapeInfo)[dimC];
|
|
zDimCstride = shape::stride(zShapeInfo)[dimC];
|
|
}
|
|
__syncthreads();
|
|
|
|
const auto tid = blockIdx.x * blockDim.x + threadIdx.x;
|
|
|
|
for (Nd4jLong i = tid; i < numOfTads; i += gridDim.x * blockDim.x) {
|
|
|
|
const T* xTad = x + xTadOffsets[i];
|
|
T* zTad = z + zTadOffsets[i];
|
|
|
|
T h, s, v;
|
|
|
|
rgbToHsv<T>(xTad[0], xTad[xDimCstride], xTad[2 * xDimCstride], h, s, v);
|
|
|
|
h += delta ;
|
|
if(h > 1)
|
|
h -= 1;
|
|
else if(h < 0)
|
|
h += 1;
|
|
|
|
hsvToRgb<T>(h, s, v, zTad[0], zTad[zDimCstride], zTad[2 * zDimCstride]);
|
|
}
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
template<typename T>
|
|
static _CUDA_H void adjustHueCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const cudaStream_t *stream,
|
|
const void* vx, const Nd4jLong* xShapeInfo, const Nd4jLong* xTadOffsets,
|
|
void* vz, const Nd4jLong* zShapeInfo, const Nd4jLong* zTadOffsets,
|
|
const Nd4jLong numOfTads, const NDArray* deltaScalarArr, const int dimC) {
|
|
|
|
adjustHueCuda<T><<<blocksPerGrid, threadsPerBlock, 256, *stream>>>(vx, xShapeInfo, xTadOffsets, vz, zShapeInfo, zTadOffsets, numOfTads, deltaScalarArr->e<T>(0), dimC);
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////////
|
|
void adjustHue(nd4j::LaunchContext* context, const NDArray *input, const NDArray* deltaScalarArr, NDArray *output, const int dimC) {
|
|
|
|
auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(input->getShapeInfo(), {dimC});
|
|
auto packZ = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(output->getShapeInfo(), {dimC});
|
|
|
|
const Nd4jLong numOfTads = packX.numberOfTads();
|
|
|
|
const int threadsPerBlock = MAX_NUM_THREADS / 2;
|
|
const int blocksPerGrid = (numOfTads + threadsPerBlock - 1) / threadsPerBlock;
|
|
|
|
PointersManager manager(context, "adjustHue");
|
|
|
|
NDArray::prepareSpecialUse({output}, {input, deltaScalarArr});
|
|
BUILD_SINGLE_SELECTOR(input->dataType(), adjustHueCudaLauncher, (blocksPerGrid, threadsPerBlock, context->getCudaStream(), input->getSpecialBuffer(), input->getSpecialShapeInfo(), packX.platformOffsets(), output->specialBuffer(), output->specialShapeInfo(), packZ.platformOffsets(), numOfTads, deltaScalarArr, dimC), FLOAT_TYPES);
|
|
NDArray::registerSpecialUse({output}, {input, deltaScalarArr});
|
|
|
|
manager.synchronize();
|
|
}
|
|
|
|
|
|
/*
|
|
template <typename T>
|
|
static void _CUDA_G adjustHueSingleNHWCKernel(void *xBuffer, Nd4jLong *xShapeInfo, void *zBuffer, Nd4jLong *zShapeInfo, Nd4jLong tuples, float delta) {
|
|
int numChannels = 3;
|
|
auto tid = threadIdx.x + blockIdx.x * blockDim.x;
|
|
|
|
auto bIn = reinterpret_cast<T*>(xBuffer);
|
|
auto bOut = reinterpret_cast<T*>(zBuffer);
|
|
static const int kChannelRange = 6;
|
|
|
|
for (Nd4jLong e = tid; e < tuples; e += blockDim.x * gridDim.x) {
|
|
auto i = bIn + e * numChannels;
|
|
auto o = bOut + e * numChannels;
|
|
|
|
T h, v_min, v_max;
|
|
helpers::rgb_to_hv(i[0], i[1], i[2], &h, &v_min, &v_max);
|
|
|
|
h += delta * kChannelRange;
|
|
while (h < (T) 0.)
|
|
h += (T) kChannelRange;
|
|
|
|
while (h >= (T) kChannelRange)
|
|
h -= (T) kChannelRange;
|
|
|
|
helpers::hv_to_rgb(h, v_min, v_max, o, o + 1, o + 2);
|
|
}
|
|
}
|
|
|
|
template <typename T>
|
|
static void _CUDA_G adjustHueSingleNCHWKernel(void *xBuffer, Nd4jLong *xTadShapeInfo, Nd4jLong *xOffsets, void *zBuffer, Nd4jLong *zTadShapeInfo, Nd4jLong *zOffsets, Nd4jLong tadLength, Nd4jLong tuples, float delta) {
|
|
int numChannels = 3;
|
|
auto tid = threadIdx.x + blockIdx.x * blockDim.x;
|
|
static const int kChannelRange = 6;
|
|
|
|
auto bufferR = reinterpret_cast<T *>(xBuffer) + xOffsets[0];
|
|
auto bufferG = reinterpret_cast<T *>(xBuffer) + xOffsets[1];
|
|
auto bufferB = reinterpret_cast<T *>(xBuffer) + xOffsets[2];
|
|
|
|
auto outputR = reinterpret_cast<T *>(zBuffer) + zOffsets[0];
|
|
auto outputG = reinterpret_cast<T *>(zBuffer) + zOffsets[1];
|
|
auto outputB = reinterpret_cast<T *>(zBuffer) + zOffsets[2];
|
|
|
|
|
|
for (Nd4jLong e = tid; e < tuples; e += blockDim.x * gridDim.x) {
|
|
auto _ri = bufferR + shape::getIndexOffset(e, xTadShapeInfo);
|
|
auto _gi = bufferG + shape::getIndexOffset(e, xTadShapeInfo);
|
|
auto _bi = bufferB + shape::getIndexOffset(e, xTadShapeInfo);
|
|
|
|
auto _ro = outputR + shape::getIndexOffset(e, xTadShapeInfo);
|
|
auto _go = outputG + shape::getIndexOffset(e, xTadShapeInfo);
|
|
auto _bo = outputB + shape::getIndexOffset(e, xTadShapeInfo);
|
|
|
|
T h, v_min, v_max;
|
|
helpers::rgb_to_hv(_ri[0], _gi[0], _bi[0], &h, &v_min, &v_max);
|
|
|
|
h += delta * kChannelRange;
|
|
while (h < (T) 0)
|
|
h += (T) kChannelRange;
|
|
|
|
while (h >= (T) kChannelRange)
|
|
h -= (T) kChannelRange;
|
|
|
|
helpers::hv_to_rgb(h, v_min, v_max, _ro, _go, _bo);
|
|
}
|
|
}
|
|
|
|
template <typename T>
|
|
static void _adjust_hue_single(nd4j::LaunchContext * context, NDArray *array, NDArray *output, float delta, bool isNHWC) {
|
|
// numChannels is always 3
|
|
auto tuples = array->lengthOf() / 3;
|
|
if (isNHWC) {
|
|
adjustHueSingleNHWCKernel<T><<<256, 256, 1024, *context->getCudaStream()>>>(array->specialBuffer(), array->specialShapeInfo(), output->specialBuffer(), output->specialShapeInfo(), tuples, delta);
|
|
} else {
|
|
// TODO: check this one
|
|
auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(array->getShapeInfo(), {1, 2});
|
|
auto packZ = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(output->getShapeInfo(), {1, 2});
|
|
|
|
auto tadLength = shape::length(packX.primaryShapeInfo());
|
|
|
|
adjustHueSingleNCHWKernel<T><<<256, 256, 1024, *context->getCudaStream()>>>(array->specialBuffer(), packX.platformShapeInfo(), packX.platformOffsets(), output->specialBuffer(), packZ.platformShapeInfo(), packZ.platformOffsets(), tadLength, tuples, delta);
|
|
}
|
|
}
|
|
|
|
|
|
template <typename T>
|
|
static void _adjust_hue_batch(nd4j::LaunchContext * context, NDArray *array, NDArray *output, float delta, bool isNHWC) {
|
|
auto xType = array->dataType();
|
|
|
|
// numChannels is always 3
|
|
auto tuples = array->lengthOf() / 3;
|
|
|
|
if (isNHWC) {
|
|
// in case of nhwc batch, we don't really care about examples: it's still bunch of RGB values
|
|
BUILD_SINGLE_SELECTOR(xType, _adjust_hue_single, (context, array, output, delta, isNHWC);, FLOAT_TYPES);
|
|
} else {
|
|
// TODO: check this one
|
|
auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(array->getShapeInfo(), {0, 2, 3});
|
|
auto packZ = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(output->getShapeInfo(), {0, 2, 3});
|
|
|
|
auto tadLength = shape::length(packX.primaryShapeInfo());
|
|
|
|
adjustHueSingleNCHWKernel<T><<<256, 256, 1024, *context->getCudaStream()>>>(array->specialBuffer(), packX.platformShapeInfo(), packX.platformOffsets(), output->specialBuffer(), packZ.platformShapeInfo(), packZ.platformOffsets(), tadLength, tuples, delta);
|
|
}
|
|
}
|
|
|
|
void _adjust_hue(nd4j::LaunchContext * context, NDArray *array, NDArray *output, NDArray* delta, bool isNHWC) {
|
|
auto xType = array->dataType();
|
|
|
|
float d = delta->e<float>(0);
|
|
if (array->rankOf() == 4) {
|
|
BUILD_SINGLE_SELECTOR(xType, _adjust_hue_batch, (context, array, output, d, isNHWC);, FLOAT_TYPES);
|
|
} else {
|
|
BUILD_SINGLE_SELECTOR(xType, _adjust_hue_single, (context, array, output, d, isNHWC);, FLOAT_TYPES);
|
|
}
|
|
}
|
|
|
|
*/
|
|
}
|
|
}
|
|
}
|