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Legacy API changes (#441)
* initial commit

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* another initial commit

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* another initial commit

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* one more initial commit

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* next step

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* next step

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* next step

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* next step

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* Refactored buffer() and shapeInfo() methods usage with NDArray class.

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* Adopt Graph class methods to use const shapes.

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* Adopt choose op to use constant shapes.

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* Adopt where op shape method to use constant shapes.

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* Adopt lstsq op to use constant empty shapes.

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* Adopt matrix_diag_part op shape routine to use constant shapes.

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* Adopt determinant ops to use constant shapes.

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* Adopt mean_pairwssqerr_loss ops to use constant shapes.

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* Adopt ops shape methods.

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* Adopt shape methods for loss ops.

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* Adopt log_loss op shape method.

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* Adopt shape methods for ops.

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* Adopt dilation2d ops shape methods.

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* Adopted deconv2d ops shape methods.

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* Adopted dynamicRNN op shape method.

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* Adopted shape methods for ops.

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* Adopted shape methods for lstm layer ops.

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* few updates

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* first cuda tweak

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* Adopt constant shapes for sconv2d ops.

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* Adopt constant shapes for gru ops.

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* Adopt constant shapes with shape methods for segment ops and so on.

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* Adopted constant shapes with unsorted_segment_* ops.

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* Adopted constant shapes with gamma op shape method.

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* Adopted shape methods of reduce_stddev ops.

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* Adopted shape methods for reduce_* ops.

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* Adopt shape method for squeeze op.

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* Adopt strided_slice shape method.

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* Refactored concat op shape method to adopt constant shapes.

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* Adopted shape method for mirror_pad op.

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* Adopted split op shape method.

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* Adopted tile ops shape methods.

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* Added const cast for mkldnn routines handles.

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* Refactored logSoftMaxForVector_ routine to conform with proper data and shape pointer casts.

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* Cosmetic changes to proper usage of constant pointers.

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* Refactored a couple shape comparators for strides and addBias helpers to proper use data pointers with inplace option.

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* Refactored depthToSpace helpers.

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* Refactored histogram helpers.

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* Refactored im2col helpers.

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* Refactored gather and gatherND helpers.

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* Fixed buffer usage on percentile helper.

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* Fixed gather shape with helpers and range buffer usage.

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* Fixed buffer usage with space to depth helpers.

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* Fixed buffer usage and constant shapes.

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* Fixed buffer usage with LUP decomposition>

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* Refactored onehot_ helper.

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* Refactored pad and prefix to use constant shapes.

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* Refactoed softmax helpers.

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* Fixed space to batch helpers to use buffers properly.

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* Fixed stack and split helpers.

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* Fixed buffer usage with sparse to dense helpers.

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* Fixed buffer usage with mindistance_ helpers.

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* Fixed buffer usage with tile helper.

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* Fixed constant shape usage.

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* Fixed constant shape usage with legacy pairwise bool ops.

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* Refactored a couple of methods to adopt constant shape usage.

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* Fixed broadcasting with constant shape."

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* Fixed const usage with inplace reverse and constant shapes with legacy reduction.

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* Refactored legacy ops with const shapes.

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* Refactored sort to adopt constant shapes.

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* Corrected sort for constant shape usage.

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* Fixed constant shape usage with special methods.

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* Refactored Context to conform with constant shape usage.

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* CUDA broadcasting headers

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* pairwise/indexreduce/random headers

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* Refactored native ops to adopt constant shapes.

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* legacy reduce3/scalar headers

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* Corrected pullRow signature and tests.

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* Corrected routines to proper use of constant shapes.

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* Refactored tests to use constant shapes properly.

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* Refactored legacy ops tests to use constant shapes properly.

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* Refactored buffer usage with NDArray tests.

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* Fixed native ops tests.

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* Fixed special concat routine.

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* Fixed buffer usage with test.

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* Fixed buffer usage with a test.

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* Refactored TAD.h and tests.

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* Refactored calcStrides* routines to use constant shapes.

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* Fixed miscelaneous errors with constant shapes.

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* NativeOps const changes

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* Corrected definitions for declared functions.

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* NativeOps const changes

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* few more const changes

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* Fixed const shapes with shape routines.

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* few more const changes

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* Fixed shape method for broadcastable case.

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* few more const changes

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* xw_plus_b BP shape fn restored

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* Fixed signatures with broadcasting.

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* Repaired backprops shape methods for a set of operations.

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* Refactored broadcast bool for cuda.

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* Refactored methods for 3 args with const qualifier.

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* Fixed a couple of kernel signatures for broadcasting.

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* Fixed kernels signatures for const buffers and shapes.

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* Refactored pairwise methods to persistent buffers and shapes usage.

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* Adopt const to buffers and shapes with kernels.

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* Adopt const to buffers and shapes with scalar kernels.

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* Refactored indexreduce kernels signatures to use const buffers and shapes.

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* Refactored pairwise kernels to adopt cons shapes and buffers.

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* Refactored pairwise bool kernels to adopt cons shapes and buffers.

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* Refactored random special ops to conform with const shapes and buffers.

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* Refactored native ops to conform with const shapes and buffers under cuda platform.

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* Cosmetical changes only.

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* Fixed const shapes and buffers error.

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* Corrected start pos routine.

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* Refactored methods to conform with const shapes and buffers.

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* Refactored helpers to use proper methods instead.

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* bunch of changes

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* next bunch of changes

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* next bunch of changes

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* Fixed execScalar declaration.

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* Fixed execScalar declaration.

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* Corrected const shape cases with sort and so on.

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* Fixed const shapes for sort.

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* Refactored kernel declarations to adopt const shapes.

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* Fixed kernels declarations to adopt const shapes.

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* Corrected kernel declarations to adopt const shapes and buffers.

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* Fixed kernels declarations to adopt const shapes.

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* Fixed segment helpers kernels declarations and so on to adopt const shapes.

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* Fixed const shape usage with segment and solve helpers.

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* Fixed kernel declaration with adjustWeight helper.

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* Fixed cuda implementations for constant shape helpers.

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* Adopted const shape usage with kernels.

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* Adopted top_k kernels to use const shapes and buffers.

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* Corrected kernels declarations to adopt const shapes with helpers.

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* Refactored NDArray definitions to adopt const shapes and buffers.

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* Fixed const shapes with image suppression helpers.

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* Slight improvement with buffers.

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* Refactored buffer usage.

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* Refactored buffer usage with tests.

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* Fixed const shape usage with definitions.

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* minor updates on cpu side

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* Refactored const shape usage with ConstantDescritor and native ops with cuda platform.

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* Refactored tear and tile kernels to adopt with const shapes.

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* softmax_loop fix

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* update missing signature

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* softmax again

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* few more missing consts

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* new methods updated

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Co-authored-by: shugeo <sgazeos@gmail.com>
2020-05-09 08:06:14 +03:00

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/*******************************************************************************
* 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 Oleh Semeniv (oleg.semeniv@gmail.com)
//
#include <system/op_boilerplate.h>
#include <ops/declarable/helpers/updatersHelpers.h>
#include <helpers/PointersManager.h>
#include <math/platformmath.h>
#include <math/templatemath.h>
namespace sd {
namespace ops {
namespace helpers {
///////////////////////////////////////////////////////////////////
template<typename T>
__global__ void adaDeltaUpdaterCuda(const void* vx, const Nd4jLong* xShapeInfo, const void* vinMsg, const Nd4jLong* inMsgShapeInfo,
const void* vinMsdx, const Nd4jLong* inMsdxShapeInfo, void* vz, const Nd4jLong* zShapeInfo, void* vstMsg,
const Nd4jLong* stMsgShapeInfo, void* vstMsdx, const Nd4jLong* stMsdxShapeInfo, const T rho, const T epsilon) {
const auto grad = reinterpret_cast<const T*>(vx);
const auto initMsg= reinterpret_cast<const T*>(vinMsg);
const auto initMsdx = reinterpret_cast<const T*>(vinMsdx);
auto up = reinterpret_cast<T*>(vz);
auto stMsg = reinterpret_cast<T*>(vstMsg);
auto stMsdx = reinterpret_cast<T*>(vstMsdx);
__shared__ Nd4jLong xLen;
__shared__ T rhoT;
__shared__ bool bEWS, bOrdering, bXZsame, bXInMsgSame, bXStMsgSame, bXInMsdxSame, bXStMsdxSame;
if (threadIdx.x == 0) {
xLen = shape::length(xShapeInfo);
rhoT = (1 - rho);
bEWS = 1 == shape::elementWiseStride(xShapeInfo) && 1 == shape::elementWiseStride(zShapeInfo) &&
1 == shape::elementWiseStride(stMsgShapeInfo) && 1 == shape::elementWiseStride(inMsgShapeInfo) &&
1 == shape::elementWiseStride(stMsdxShapeInfo) && 1 == shape::elementWiseStride(inMsdxShapeInfo);
bOrdering = shape::order(xShapeInfo) == shape::order(zShapeInfo) && shape::order(zShapeInfo) == shape::order(stMsgShapeInfo) &&
shape::order(stMsgShapeInfo) == shape::order(inMsgShapeInfo) && shape::order(inMsgShapeInfo) == shape::order(stMsdxShapeInfo) &&
shape::order(stMsdxShapeInfo) == shape::order(inMsdxShapeInfo);
bXZsame = shape::haveSameShapeAndStrides(xShapeInfo, zShapeInfo);
bXInMsgSame = shape::haveSameShapeAndStrides(xShapeInfo, inMsgShapeInfo);
bXStMsgSame = shape::haveSameShapeAndStrides(xShapeInfo, stMsgShapeInfo);
bXInMsdxSame = shape::haveSameShapeAndStrides(xShapeInfo, inMsdxShapeInfo);
bXStMsdxSame = shape::haveSameShapeAndStrides(xShapeInfo, stMsdxShapeInfo);
}
__syncthreads();
int coords[MAX_RANK];
for (Nd4jLong i = blockIdx.x * blockDim.x + threadIdx.x; i < xLen; i += gridDim.x * blockDim.x) {
auto xOffset = i, zOffset = i, initMsgOffset = i, initMsdxOffset = i, stMsgOffset = i, stMsdxOffset = i;
if (!bEWS || !bOrdering){
shape::index2coords(i, xShapeInfo, coords);
xOffset = shape::getOffset(xShapeInfo, coords);
zOffset = bXZsame ? xOffset : shape::getOffset(zShapeInfo, coords);
initMsgOffset = bXInMsgSame ? xOffset : shape::getOffset(inMsgShapeInfo, coords);
stMsgOffset = bXStMsgSame ? xOffset : shape::getOffset(stMsgShapeInfo, coords);
initMsdxOffset = bXInMsdxSame ? xOffset : shape::getOffset(inMsdxShapeInfo, coords);
stMsdxOffset = bXStMsdxSame ? xOffset : shape::getOffset(stMsdxShapeInfo, coords);
}
stMsg[stMsgOffset] = rho * initMsg[initMsgOffset] + grad[xOffset] * grad[xOffset] * rhoT;
up[zOffset] = grad[xOffset] * (sd::math::nd4j_sqrt<T, T>(initMsdx[initMsdxOffset] + epsilon) / sd::math::nd4j_sqrt<T, T>(stMsg[stMsgOffset] + epsilon));
stMsdx[stMsdxOffset] = rho * initMsdx[initMsdxOffset] + up[zOffset] * up[zOffset] * rhoT;
}
}
///////////////////////////////////////////////////////////////////
template<typename T>
linkage void adaDeltaUpdaterCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const cudaStream_t* stream, const void* vx, const Nd4jLong* xShapeInfo,
const void* vinMsg, const Nd4jLong* inMsgShapeInfo, const void* vinMsdx, const Nd4jLong* inMsdxShapeInfo,
void* vz, const Nd4jLong* zShapeInfo, void* vstMsg, const Nd4jLong* stMsgShapeInfo,
void* vstMsdx, const Nd4jLong* stMsdxShapeInfo, const double dRho, const double dEpsilon) {
const T rho = static_cast<T>(dRho);
const T epsilon = static_cast<T>(dEpsilon);
adaDeltaUpdaterCuda<T><<<blocksPerGrid, threadsPerBlock, 256, * stream>>>(vx, xShapeInfo, vinMsg, inMsgShapeInfo,
vinMsdx, inMsdxShapeInfo, vz, zShapeInfo, vstMsg, stMsgShapeInfo, vstMsdx, stMsdxShapeInfo, rho, epsilon);
}
///////////////////////////////////////////////////////////////////
void updaterAdaDelta(sd::LaunchContext* context, const NDArray& gradient, const NDArray& initStateMsg, const NDArray& initStateMsdx,
NDArray& update, NDArray& stateMsg, NDArray& stateMsdx, const double dRho, const double dEpsilon) {
PointersManager manager(context, "adaDeltaUpdater");
const int threadsPerBlock = MAX_NUM_THREADS / 4;
const int blocksPerGrid = (gradient.lengthOf() + threadsPerBlock - 1) / threadsPerBlock;
NDArray::prepareSpecialUse({ &update, &stateMsg, &stateMsdx }, { &gradient, &initStateMsg, &initStateMsdx });
BUILD_SINGLE_SELECTOR(gradient.dataType(), adaDeltaUpdaterCudaLauncher, (blocksPerGrid, threadsPerBlock, context->getCudaStream(), gradient.specialBuffer(), gradient.specialShapeInfo(),
initStateMsg.specialBuffer(), initStateMsg.specialShapeInfo(), initStateMsdx.specialBuffer(), initStateMsdx.specialShapeInfo(),
update.specialBuffer(), update.specialShapeInfo(),stateMsg.specialBuffer(), stateMsg.specialShapeInfo(),
stateMsdx.specialBuffer(), stateMsdx.specialShapeInfo(), dRho, dEpsilon), FLOAT_TYPES);
NDArray::registerSpecialUse({ &update, &stateMsg, &stateMsdx }, { &gradient, &initStateMsg, &initStateMsdx });
manager.synchronize();
}
}
}
}