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Legacy API changes (#441)
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* one more initial commit

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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
******************************************************************************/
//
// Created by raver119 on 30.11.17.
//
#include <ops/declarable/helpers/im2col.h>
#include <helpers/PointersManager.h>
namespace sd {
namespace ops {
namespace helpers {
//////////////////////////////////////////////////////////////////////////
// input [bS, iC, iH, iW] is convoluted to output [bS, iC, kH, kW, oH, oW]
template <typename T>
__global__ static void im2colCuda(const void *image, void *columns,
const Nd4jLong *imShapeInfo, const Nd4jLong *colShapeInfo,
const int sH, const int sW,
const int pH, const int pW,
const int dH, const int dW,
const double zeroPadValD) {
T zeroPadVal = static_cast<T>(zeroPadValD); //Value to use when value is padding. Usually 0 but not always
const auto im = reinterpret_cast<const T*>(image);
auto col = reinterpret_cast<T*>(columns);
__shared__ Nd4jLong colLen, iH, iW;
__shared__ int imRank, colRank, *sharedMem;
if (threadIdx.x == 0) {
extern __shared__ unsigned char shmem[];
sharedMem = reinterpret_cast<int*>(shmem);
colRank = 6;
imRank = 4;
colLen = shape::length(colShapeInfo);
iH = imShapeInfo[3];
iW = imShapeInfo[4];
}
__syncthreads();
const auto colInd = threadIdx.x + blockIdx.x * blockDim.x;
if(colInd >= colLen)
return;
auto coords = sharedMem + threadIdx.x * colRank;
shape::index2coords(colInd, colShapeInfo, coords);
const auto colOffset = shape::getOffset(colShapeInfo, coords);
coords[2] = (-pH + coords[2] * dH) + coords[4] * sH; // imH
coords[3] = (-pW + coords[3] * dW) + coords[5] * sW; // imW
if (static_cast<unsigned>(coords[2]) >= static_cast<unsigned>(iH) || static_cast<unsigned>(coords[3]) >= static_cast<unsigned>(iW))
col[colOffset] = zeroPadVal;
else
col[colOffset] = im[shape::getOffset(imShapeInfo, coords)];
}
//////////////////////////////////////////////////////////////////////////
template <typename T>
static void im2colCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, sd::LaunchContext & context, const void *image, void *columns, const Nd4jLong *imShapeInfo, const Nd4jLong *colShapeInfo, int sH, int sW, int pH, int pW, int dH, int dW, double zeroPadVal) {
im2colCuda<T><<<blocksPerGrid, threadsPerBlock, threadsPerBlock * sizeof(int) * 6 /* rank of columns = 6 */, *context.getCudaStream()>>>(image, columns, imShapeInfo, colShapeInfo, sH, sW, pH, pW, dH, dW, zeroPadVal);
}
//////////////////////////////////////////////////////////////////////////
void im2col(sd::LaunchContext& context, const NDArray& image, NDArray& columns, const int kH, const int kW, const int sH, const int sW, const int pH, const int pW, const int dH, const int dW, const NDArray& arrZeroPadVal) {
PointersManager manager(&context, "im2col");
const int threadsPerBlock = 512;
const int blocksPerGrid = (columns.lengthOf() + threadsPerBlock - 1) / threadsPerBlock;
NDArray::prepareSpecialUse({&columns}, {&image});
BUILD_SINGLE_SELECTOR(columns.dataType(), im2colCudaLauncher, (blocksPerGrid, threadsPerBlock, context, image.specialBuffer(), columns.specialBuffer(), image.specialShapeInfo(), columns.specialShapeInfo(), sH, sW, pH, pW, dH, dW, arrZeroPadVal.e<double>(0)), FLOAT_TYPES);
NDArray::registerSpecialUse({&columns}, {&image});
manager.synchronize();
}
}
}
}