cavis/libnd4j/include/loops/cuda/pairwise.chpp
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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) 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)
#ifndef PAIRWISE_CU
#define PAIRWISE_CU
#include "../pairwise_transform.h"
using namespace simdOps;
////////////////////////////////////////////////////////////////////////////////
template <typename X, typename Y, typename Z, typename OpType>
__global__ static void pairwiseSimpleShaped(void const* vx, Nd4jLong const* xShapeInfo,
void const* vy, Nd4jLong const* yShapeInfo,
void *vz, Nd4jLong const* zShapeInfo,
void *vextraParams) {
auto x = reinterpret_cast<X const*>(vx);
auto y = reinterpret_cast<Y const*>(vy);
auto z = reinterpret_cast<Z*>(vz);
auto extraParams = reinterpret_cast<Z*>(vextraParams);
int tid = blockIdx.x * blockDim.x + threadIdx.x;
__shared__ int xEws;
__shared__ int yEws;
__shared__ int zEws;
__shared__ char xOrder;
__shared__ char yOrder;
__shared__ char zOrder;
__shared__ Nd4jLong len;
if (threadIdx.x == 0) {
xEws = shape::elementWiseStride(xShapeInfo);
yEws = shape::elementWiseStride(yShapeInfo);
zEws = shape::elementWiseStride(zShapeInfo);
xOrder = shape::order(xShapeInfo);
yOrder = shape::order(yShapeInfo);
zOrder = shape::order(zShapeInfo);
len = shape::length(xShapeInfo);
}
__syncthreads();
if (xEws >= 1 && yEws >= 1 && zEws >= 1 && xOrder == yOrder && xOrder == zOrder) {
for (Nd4jLong i = tid; i < len; i += gridDim.x * blockDim.x) {
z[i * zEws] = OpType::op(x[i * xEws], y[i * yEws], extraParams);
}
}
else if (vx == vz) {
for (Nd4jLong i = tid; i < len; i += gridDim.x * blockDim.x) {
auto xOffset = shape::getIndexOffset(i, xShapeInfo);
auto yOffset = shape::getIndexOffset(i, yShapeInfo);
z[xOffset] = OpType::op(x[xOffset], y[yOffset], extraParams);
}
}
else {
for (Nd4jLong i = tid; i < len; i += gridDim.x * blockDim.x) {
auto xOffset = shape::getIndexOffset(i, xShapeInfo);
auto yOffset = shape::getIndexOffset(i, yShapeInfo);
auto zOffset = shape::getIndexOffset(i, zShapeInfo);
z[zOffset] = OpType::op(x[xOffset], y[yOffset], extraParams);
}
}
}
namespace functions {
namespace pairwise_transforms {
////////////////////////////////////////////////////////////////////////////////
template<typename X, typename Y, typename Z>
template<typename OpType>
void __host__ PairWiseTransform<X,Y,Z>::intermediateShaped(dim3& launchDims, cudaStream_t *stream,
void const* vx, Nd4jLong const* xShapeInfo,
void const* vy, Nd4jLong const* yShapeInfo,
void *vz, Nd4jLong const* zShapeInfo,
void *vextraParams){
pairwiseSimpleShaped<X, Y, Z, OpType><<<launchDims.x, launchDims.y, launchDims.z, *stream>>>(vx, xShapeInfo, vy, yShapeInfo, vz, zShapeInfo, vextraParams);
}
////////////////////////////////////////////////////////////////////////////////
template<typename X, typename Y, typename Z>
void __host__ PairWiseTransform<X,Y,Z>::executeCudaShaped(dim3& launchDims, cudaStream_t *stream, int opNum, void const* vx, Nd4jLong const* xShapeInfo, void const* vy, Nd4jLong const* yShapeInfo, void *vz, Nd4jLong const* zShapeInfo, void* vextraParams) {
DISPATCH_BY_OPNUM_TTT(intermediateShaped, PARAMS(launchDims, stream, vx, xShapeInfo, vy, yShapeInfo, vz, zShapeInfo, vextraParams), PAIRWISE_TRANSFORM_OPS);
}
/*
BUILD_PAIRWISE_TEMPLATE(template class ND4J_EXPORT PairWiseTransform, , PAIRWISE_TYPES_0);
BUILD_PAIRWISE_TEMPLATE(template class ND4J_EXPORT PairWiseTransform, , PAIRWISE_TYPES_1);
BUILD_PAIRWISE_TEMPLATE(template class ND4J_EXPORT PairWiseTransform, , PAIRWISE_TYPES_2);
BUILD_PAIRWISE_TEMPLATE(template class ND4J_EXPORT PairWiseTransform, , PAIRWISE_TYPES_3);
BUILD_PAIRWISE_TEMPLATE(template class ND4J_EXPORT PairWiseTransform, , PAIRWISE_TYPES_4);
BUILD_PAIRWISE_TEMPLATE(template class ND4J_EXPORT PairWiseTransform, , PAIRWISE_TYPES_5);
BUILD_PAIRWISE_TEMPLATE(template class ND4J_EXPORT PairWiseTransform, , PAIRWISE_TYPES_6);
BUILD_PAIRWISE_TEMPLATE(template class ND4J_EXPORT PairWiseTransform, , PAIRWISE_TYPES_7);
BUILD_PAIRWISE_TEMPLATE(template class ND4J_EXPORT PairWiseTransform, , PAIRWISE_TYPES_8);
BUILD_PAIRWISE_TEMPLATE(template class ND4J_EXPORT PairWiseTransform, , PAIRWISE_TYPES_9);
*/
}
}
#endif // PAIRWISE_CU