cavis/libnd4j/include/ops/declarable/platform/mkldnn/deconv3d.cpp

467 lines
28 KiB
C++
Raw Normal View History

/*******************************************************************************
* 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 Yurii Shyrma (iuriish@yahoo.com)
//
#include <ops/declarable/PlatformHelper.h>
#include <ops/declarable/OpRegistrator.h>
#include <system/platform_boilerplate.h>
#include <helpers/MKLDNNStream.h>
#include "mkldnnUtils.h"
#include <ops/declarable/helpers/convolutions.h>
namespace sd {
namespace ops {
namespace platforms {
//////////////////////////////////////////////////////////////////////////
static void deconv3dMKLDNN(const NDArray* input, const NDArray* weights, const NDArray* bias, NDArray* output,
const int kD, const int kH, const int kW, const int sD, const int sH, const int sW,
const int pD, const int pH, const int pW, const int dD, const int dH, const int dW,
const bool isNCDHW, const int wFormat) {
// mkl supports weights in [oC, iC, kD, kH, kW] only
int bS, iC, iD, iH, iW, oC, oD, oH, oW; // batch size, input channels, input depth/height/width, output channels, output depth/height/width;
int indIOioC, indIOioD, indWoC, indWiC, indWkD; // corresponding indexes
ConvolutionUtils::getSizesAndIndexesConv3d(isNCDHW, wFormat, *input, *output, bS, iC, iD, iH, iW, oC, oD, oH, oW, indIOioC, indIOioD, indWoC, indWiC, indWkD);
dnnl::memory::dims strides = { sD, sH, sW };
dnnl::memory::dims padding = { pD, pH, pW };
dnnl::memory::dims padding_r = { (iD - 1) * sD - oD + kD - pD, (iH - 1) * sH - oH + kH - pH, (iW - 1) * sW - oW + kW - pW };
dnnl::memory::dims dilation = { dD-1, dH-1, dW-1 };
std::vector<int> permut;
if(0 == wFormat)
permut = {3,4,0,1,2}; // [kD, kH, kW, oC, iC] -> [oC, iC, kD, kH, kW]
else if(1 == wFormat)
permut = {1,0,2,3,4}; // [iC, oC, kD, kH, kW] -> [oC, iC, kD, kH, kW]
else
permut = {4,0,1,2,3}; // [iC, kD, kH, kW, oC] -> [oC, iC, kD, kH, kW]
// input type
dnnl::memory::data_type xType;
if(input->dataType() == DataType::FLOAT32)
xType = dnnl::memory::data_type::f32;
else if(input->dataType() == DataType::HALF)
xType = dnnl::memory::data_type::f16;
else if(input->dataType() == DataType::UINT8)
xType = dnnl::memory::data_type::u8;
else
xType = dnnl::memory::data_type::s8;
// weights type
dnnl::memory::data_type wType = xType;
if(xType == dnnl::memory::data_type::u8)
wType = dnnl::memory::data_type::s8;
// output and bias type (have the same types)
dnnl::memory::data_type zType;
if(output->dataType() == DataType::FLOAT32)
zType = dnnl::memory::data_type::f32;
else if(output->dataType() == DataType::HALF)
zType = dnnl::memory::data_type::f16;
else if(output->dataType() == DataType::UINT8)
zType = dnnl::memory::data_type::u8;
else if(output->dataType() == DataType::INT8)
zType = dnnl::memory::data_type::s8;
else
zType = dnnl::memory::data_type::s32;
dnnl::memory::format_tag xFormatMkl = isNCDHW ? dnnl::memory::format_tag::ncdhw : dnnl::memory::format_tag::ndhwc;
dnnl::memory::format_tag wFormatMkl = dnnl::memory::format_tag::oidhw;
dnnl::memory::dims xDims = {bS, iC, iD, iH, iW};
dnnl::memory::dims wDims = {oC, iC, kD, kH, kW};
dnnl::memory::dims zDims = {bS, oC, oD, oH, oW};
// memory descriptors for arrays
// input
dnnl::memory::desc x_mkl_md = dnnl::memory::desc(xDims, xType, dnnl::memory::format_tag::any);
dnnl::memory::desc x_user_md = dnnl::memory::desc(xDims, xType, xFormatMkl);
mkldnnUtils::setBlockStrides(*input, x_user_md);
// weights
dnnl::memory::desc w_mkl_md = dnnl::memory::desc(wDims, wType, dnnl::memory::format_tag::any);
dnnl::memory::desc w_user_md = dnnl::memory::desc(wDims, wType, wFormatMkl);
mkldnnUtils::setBlockStrides(*weights, w_user_md, permut);
// bias
dnnl::memory::desc b_mkl_md;
if(bias != nullptr)
b_mkl_md = dnnl::memory::desc({oC}, zType, dnnl::memory::format_tag::x);
// output
dnnl::memory::desc z_mkl_md = dnnl::memory::desc(zDims, zType, dnnl::memory::format_tag::any);
dnnl::memory::desc z_user_md = dnnl::memory::desc(zDims, zType, xFormatMkl);
mkldnnUtils::setBlockStrides(*output, z_user_md);
auto engine = mkldnnUtils::getEngine(LaunchContext::defaultContext()->engine());
// operation primitive description
dnnl::deconvolution_forward::desc op_desc(dnnl::prop_kind::forward_inference, dnnl::algorithm::deconvolution_direct,
x_mkl_md, w_mkl_md, b_mkl_md, z_mkl_md, strides, dilation, padding, padding_r);
dnnl::deconvolution_forward::primitive_desc op_prim_desc(op_desc, engine);
// arguments (memory buffers) necessary for calculations
std::unordered_map<int, dnnl::memory> args;
dnnl::stream stream(engine);
// provide memory buffers and check whether reorder is required
// input
mkldnnUtils::loadDataToMklStream(*input, engine, stream, x_user_md, op_prim_desc.src_desc(), args[DNNL_ARG_SRC]);
// weights
mkldnnUtils::loadDataToMklStream(*weights, engine, stream, w_user_md, op_prim_desc.weights_desc(), args[DNNL_ARG_WEIGHTS]);
// bias
if(bias != nullptr) {
Legacy API changes (#441) * initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * another initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * another initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one more initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Refactored buffer() and shapeInfo() methods usage with NDArray class. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt Graph class methods to use const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt choose op to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt where op shape method to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt lstsq op to use constant empty shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt matrix_diag_part op shape routine to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt determinant ops to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt mean_pairwssqerr_loss ops to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt shape methods for loss ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt log_loss op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt shape methods for ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt dilation2d ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted deconv2d ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted dynamicRNN op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods for ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods for lstm layer ops. Signed-off-by: shugeo <sgazeos@gmail.com> * few updates Signed-off-by: raver119@gmail.com <raver119@gmail.com> * first cuda tweak Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Adopt constant shapes for sconv2d ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt constant shapes for gru ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt constant shapes with shape methods for segment ops and so on. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted constant shapes with unsorted_segment_* ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted constant shapes with gamma op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods of reduce_stddev ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods for reduce_* ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt shape method for squeeze op. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt strided_slice shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored concat op shape method to adopt constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape method for mirror_pad op. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted split op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted tile ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Added const cast for mkldnn routines handles. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored logSoftMaxForVector_ routine to conform with proper data and shape pointer casts. Signed-off-by: shugeo <sgazeos@gmail.com> * Cosmetic changes to proper usage of constant pointers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored a couple shape comparators for strides and addBias helpers to proper use data pointers with inplace option. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored depthToSpace helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored histogram helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored im2col helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored gather and gatherND helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage on percentile helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed gather shape with helpers and range buffer usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with space to depth helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage and constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with LUP decomposition> Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored onehot_ helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pad and prefix to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactoed softmax helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed space to batch helpers to use buffers properly. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed stack and split helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with sparse to dense helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with mindistance_ helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with tile helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed constant shape usage with legacy pairwise bool ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored a couple of methods to adopt constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed broadcasting with constant shape." Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const usage with inplace reverse and constant shapes with legacy reduction. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored legacy ops with const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored sort to adopt constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected sort for constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed constant shape usage with special methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored Context to conform with constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * CUDA broadcasting headers Signed-off-by: raver119@gmail.com <raver119@gmail.com> * pairwise/indexreduce/random headers Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Refactored native ops to adopt constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * legacy reduce3/scalar headers Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Corrected pullRow signature and tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected routines to proper use of constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored tests to use constant shapes properly. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored legacy ops tests to use constant shapes properly. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored buffer usage with NDArray tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed native ops tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed special concat routine. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with test. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with a test. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored TAD.h and tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored calcStrides* routines to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed miscelaneous errors with constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * NativeOps const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Corrected definitions for declared functions. Signed-off-by: shugeo <sgazeos@gmail.com> * NativeOps const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * few more const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed const shapes with shape routines. Signed-off-by: shugeo <sgazeos@gmail.com> * few more const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed shape method for broadcastable case. Signed-off-by: shugeo <sgazeos@gmail.com> * few more const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * xw_plus_b BP shape fn restored Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed signatures with broadcasting. Signed-off-by: shugeo <sgazeos@gmail.com> * Repaired backprops shape methods for a set of operations. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored broadcast bool for cuda. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored methods for 3 args with const qualifier. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed a couple of kernel signatures for broadcasting. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernels signatures for const buffers and shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pairwise methods to persistent buffers and shapes usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt const to buffers and shapes with kernels. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt const to buffers and shapes with scalar kernels. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored indexreduce kernels signatures to use const buffers and shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pairwise kernels to adopt cons shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pairwise bool kernels to adopt cons shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored random special ops to conform with const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored native ops to conform with const shapes and buffers under cuda platform. Signed-off-by: shugeo <sgazeos@gmail.com> * Cosmetical changes only. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shapes and buffers error. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected start pos routine. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored methods to conform with const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored helpers to use proper methods instead. Signed-off-by: shugeo <sgazeos@gmail.com> * bunch of changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next bunch of changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next bunch of changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed execScalar declaration. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed execScalar declaration. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected const shape cases with sort and so on. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shapes for sort. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored kernel declarations to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernels declarations to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected kernel declarations to adopt const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernels declarations to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed segment helpers kernels declarations and so on to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shape usage with segment and solve helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernel declaration with adjustWeight helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed cuda implementations for constant shape helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted const shape usage with kernels. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted top_k kernels to use const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected kernels declarations to adopt const shapes with helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored NDArray definitions to adopt const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shapes with image suppression helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Slight improvement with buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored buffer usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored buffer usage with tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shape usage with definitions. Signed-off-by: shugeo <sgazeos@gmail.com> * minor updates on cpu side Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Refactored const shape usage with ConstantDescritor and native ops with cuda platform. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored tear and tile kernels to adopt with const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * softmax_loop fix Signed-off-by: raver119 <raver119@gmail.com> * update missing signature Signed-off-by: raver119@gmail.com <raver119@gmail.com> * softmax again Signed-off-by: raver119@gmail.com <raver119@gmail.com> * few more missing consts Signed-off-by: raver119 <raver119@gmail.com> * new methods updated Signed-off-by: raver119@gmail.com <raver119@gmail.com> Co-authored-by: shugeo <sgazeos@gmail.com>
2020-05-09 07:06:14 +02:00
auto b_mkl_mem = dnnl::memory(b_mkl_md, engine, const_cast<void*>(bias->buffer()));
args[DNNL_ARG_BIAS] = b_mkl_mem;
}
// output
auto z_user_mem = mkldnnUtils::loadDataToMklStream(*output, engine, stream, z_user_md, op_prim_desc.dst_desc(), args[DNNL_ARG_DST]);
// run calculations
dnnl::deconvolution_forward(op_prim_desc).execute(stream, args);
// reorder outputs if necessary
if (op_prim_desc.dst_desc() != z_user_mem.get_desc())
dnnl::reorder(args[DNNL_ARG_DST], z_user_mem).execute(stream, args[DNNL_ARG_DST], z_user_mem);
stream.wait();
// shape::printArray(z_mkl_mem.map_data<float>(),8);
}
//////////////////////////////////////////////////////////////////////////
static void deconv3dBackPropMKLDNN(const NDArray* input, const NDArray* weights, const NDArray* gradO, NDArray* gradI, NDArray* gradW, NDArray* gradB,
const int kD, const int kH, const int kW,
const int sD, const int sH, const int sW,
const int pD, const int pH, const int pW,
const int dD, const int dH, const int dW,
const bool isNCDHW, const int wFormat) {
// mkl supports weights/gradW in [oC, iC, kD, kH, kW] format only
int bS, iC, iD, iH, iW, oC, oD, oH, oW; // batch size, input channels, input depth/height/width, output channels, output depth/height/width;
int indIOioC, indIOioD, indWoC, indWiC, indWkD; // corresponding indexes
ConvolutionUtils::getSizesAndIndexesConv3d(isNCDHW, wFormat, *input, *gradO, bS, iC, iD, iH, iW, oC, oD, oH, oW, indIOioC, indIOioD, indWoC, indWiC, indWkD);
dnnl::memory::dims strides = { sD, sH, sW };
dnnl::memory::dims padding = { pD, pH, pW };
dnnl::memory::dims padding_r = { (iD - 1) * sD - oD + kD - pD, (iH - 1) * sH - oH + kH - pH, (iW - 1) * sW - oW + kW - pW };
dnnl::memory::dims dilation = { dD-1, dH-1, dW-1 };
std::vector<int> permut;
if(0 == wFormat)
permut = {3,4,0,1,2}; // [kD, kH, kW, oC, iC] -> [oC, iC, kD, kH, kW]
else if(1 == wFormat)
permut = {1,0,2,3,4}; // [iC, oC, kD, kH, kW] -> [oC, iC, kD, kH, kW]
else
permut = {4,0,1,2,3}; // [iC, kD, kH, kW, oC] -> [oC, iC, kD, kH, kW]
// input type
dnnl::memory::data_type xType = input->dataType() == DataType::FLOAT32 ? dnnl::memory::data_type::f32 : dnnl::memory::data_type::bf16;
// weights type
dnnl::memory::data_type wType = weights->dataType() == DataType::FLOAT32 ? dnnl::memory::data_type::f32 : dnnl::memory::data_type::bf16;
// gradO type
dnnl::memory::data_type gradOType = gradO->dataType() == DataType::FLOAT32 ? dnnl::memory::data_type::f32 : dnnl::memory::data_type::bf16;
// gradI type
dnnl::memory::data_type gradIType = gradI->dataType() == DataType::FLOAT32 ? dnnl::memory::data_type::f32 : dnnl::memory::data_type::bf16;
// gradW type
dnnl::memory::data_type gradWType = gradW->dataType() == DataType::FLOAT32 ? dnnl::memory::data_type::f32 : dnnl::memory::data_type::bf16;
// gradB type
dnnl::memory::data_type gradBType = gradB != nullptr ? (gradB->dataType() == DataType::FLOAT32 ? dnnl::memory::data_type::f32 : dnnl::memory::data_type::bf16) : dnnl::memory::data_type::f32;
dnnl::memory::format_tag xFormatMkl = isNCDHW ? dnnl::memory::format_tag::ncdhw : dnnl::memory::format_tag::ndhwc;
dnnl::memory::format_tag wFormatMkl = dnnl::memory::format_tag::oidhw;
dnnl::memory::dims xDims = {bS, iC, iD, iH, iW};
dnnl::memory::dims wDims = {oC, iC, kD, kH, kW};
dnnl::memory::dims zDims = {bS, oC, oD, oH, oW};
// memory descriptors for arrays
// input
dnnl::memory::desc x_mkl_md = dnnl::memory::desc(xDims, xType, dnnl::memory::format_tag::any);
dnnl::memory::desc x_user_md = dnnl::memory::desc(xDims, xType, xFormatMkl);
mkldnnUtils::setBlockStrides(*input, x_user_md);
// weights
dnnl::memory::desc w_mkl_md = dnnl::memory::desc(wDims, wType, dnnl::memory::format_tag::any);
dnnl::memory::desc w_user_md = dnnl::memory::desc(wDims, wType, wFormatMkl);
mkldnnUtils::setBlockStrides(*weights, w_user_md, permut);
// gradO
dnnl::memory::desc gradO_mkl_md = dnnl::memory::desc(zDims, gradOType, dnnl::memory::format_tag::any);
dnnl::memory::desc gradO_user_md = dnnl::memory::desc(zDims, gradOType, xFormatMkl);
mkldnnUtils::setBlockStrides(*gradO, gradO_user_md);
// gradI
dnnl::memory::desc gradI_mkl_md = dnnl::memory::desc(xDims, gradIType, dnnl::memory::format_tag::any);
dnnl::memory::desc gradI_user_md = dnnl::memory::desc(xDims, gradIType, xFormatMkl);
mkldnnUtils::setBlockStrides(*gradI, gradI_user_md);
// gradW
dnnl::memory::desc gradW_mkl_md = dnnl::memory::desc(wDims, gradWType, dnnl::memory::format_tag::any);
dnnl::memory::desc gradW_user_md = dnnl::memory::desc(wDims, gradWType, wFormatMkl);
mkldnnUtils::setBlockStrides(*gradW, gradW_user_md, permut);
// gradB
dnnl::memory::desc gradB_mkl_md;
if(gradB != nullptr)
gradB_mkl_md = dnnl::memory::desc({oC}, gradBType, dnnl::memory::format_tag::x);
auto engine = mkldnnUtils::getEngine(LaunchContext::defaultContext()->engine());
// forward primitive description
dnnl::deconvolution_forward::desc op_ff_desc(dnnl::prop_kind::forward_inference, dnnl::algorithm::deconvolution_direct, x_mkl_md, w_mkl_md, gradB_mkl_md, gradO_mkl_md, strides, dilation, padding, padding_r);
dnnl::deconvolution_forward::primitive_desc op_ff_prim_desc(op_ff_desc, engine);
// backward data primitive description
dnnl::deconvolution_backward_data::desc op_data_bp_desc(dnnl::algorithm::deconvolution_direct, gradI_mkl_md, w_mkl_md, gradO_mkl_md, strides, dilation, padding, padding_r);
dnnl::deconvolution_backward_data::primitive_desc op_data_bp_prim_desc(op_data_bp_desc, engine, op_ff_prim_desc);
// backward weights primitive description
dnnl::deconvolution_backward_weights::desc op_weights_bp_desc(dnnl::algorithm::deconvolution_direct, x_mkl_md, gradW_mkl_md, gradB_mkl_md, gradO_mkl_md, strides, dilation, padding, padding_r);
dnnl::deconvolution_backward_weights::primitive_desc op_weights_bp_prim_desc(op_weights_bp_desc, engine, op_ff_prim_desc);
// arguments (memory buffers) necessary for calculations
std::unordered_map<int, dnnl::memory> args;
dnnl::stream stream(engine);
// provide memory buffers and check whether reorder is required
// input
mkldnnUtils::loadDataToMklStream(*input, engine, stream, x_user_md, op_weights_bp_prim_desc.src_desc(), args[DNNL_ARG_SRC]);
// weights
mkldnnUtils::loadDataToMklStream(*weights, engine, stream, w_user_md, op_data_bp_prim_desc.weights_desc(), args[DNNL_ARG_WEIGHTS]);
// gradO
Legacy API changes (#441) * initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * another initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * another initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one more initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Refactored buffer() and shapeInfo() methods usage with NDArray class. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt Graph class methods to use const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt choose op to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt where op shape method to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt lstsq op to use constant empty shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt matrix_diag_part op shape routine to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt determinant ops to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt mean_pairwssqerr_loss ops to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt shape methods for loss ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt log_loss op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt shape methods for ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt dilation2d ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted deconv2d ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted dynamicRNN op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods for ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods for lstm layer ops. Signed-off-by: shugeo <sgazeos@gmail.com> * few updates Signed-off-by: raver119@gmail.com <raver119@gmail.com> * first cuda tweak Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Adopt constant shapes for sconv2d ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt constant shapes for gru ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt constant shapes with shape methods for segment ops and so on. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted constant shapes with unsorted_segment_* ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted constant shapes with gamma op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods of reduce_stddev ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods for reduce_* ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt shape method for squeeze op. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt strided_slice shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored concat op shape method to adopt constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape method for mirror_pad op. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted split op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted tile ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Added const cast for mkldnn routines handles. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored logSoftMaxForVector_ routine to conform with proper data and shape pointer casts. Signed-off-by: shugeo <sgazeos@gmail.com> * Cosmetic changes to proper usage of constant pointers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored a couple shape comparators for strides and addBias helpers to proper use data pointers with inplace option. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored depthToSpace helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored histogram helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored im2col helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored gather and gatherND helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage on percentile helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed gather shape with helpers and range buffer usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with space to depth helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage and constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with LUP decomposition> Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored onehot_ helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pad and prefix to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactoed softmax helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed space to batch helpers to use buffers properly. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed stack and split helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with sparse to dense helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with mindistance_ helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with tile helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed constant shape usage with legacy pairwise bool ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored a couple of methods to adopt constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed broadcasting with constant shape." Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const usage with inplace reverse and constant shapes with legacy reduction. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored legacy ops with const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored sort to adopt constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected sort for constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed constant shape usage with special methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored Context to conform with constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * CUDA broadcasting headers Signed-off-by: raver119@gmail.com <raver119@gmail.com> * pairwise/indexreduce/random headers Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Refactored native ops to adopt constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * legacy reduce3/scalar headers Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Corrected pullRow signature and tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected routines to proper use of constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored tests to use constant shapes properly. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored legacy ops tests to use constant shapes properly. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored buffer usage with NDArray tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed native ops tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed special concat routine. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with test. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with a test. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored TAD.h and tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored calcStrides* routines to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed miscelaneous errors with constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * NativeOps const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Corrected definitions for declared functions. Signed-off-by: shugeo <sgazeos@gmail.com> * NativeOps const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * few more const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed const shapes with shape routines. Signed-off-by: shugeo <sgazeos@gmail.com> * few more const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed shape method for broadcastable case. Signed-off-by: shugeo <sgazeos@gmail.com> * few more const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * xw_plus_b BP shape fn restored Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed signatures with broadcasting. Signed-off-by: shugeo <sgazeos@gmail.com> * Repaired backprops shape methods for a set of operations. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored broadcast bool for cuda. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored methods for 3 args with const qualifier. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed a couple of kernel signatures for broadcasting. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernels signatures for const buffers and shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pairwise methods to persistent buffers and shapes usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt const to buffers and shapes with kernels. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt const to buffers and shapes with scalar kernels. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored indexreduce kernels signatures to use const buffers and shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pairwise kernels to adopt cons shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pairwise bool kernels to adopt cons shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored random special ops to conform with const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored native ops to conform with const shapes and buffers under cuda platform. Signed-off-by: shugeo <sgazeos@gmail.com> * Cosmetical changes only. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shapes and buffers error. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected start pos routine. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored methods to conform with const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored helpers to use proper methods instead. Signed-off-by: shugeo <sgazeos@gmail.com> * bunch of changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next bunch of changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next bunch of changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed execScalar declaration. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed execScalar declaration. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected const shape cases with sort and so on. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shapes for sort. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored kernel declarations to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernels declarations to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected kernel declarations to adopt const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernels declarations to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed segment helpers kernels declarations and so on to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shape usage with segment and solve helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernel declaration with adjustWeight helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed cuda implementations for constant shape helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted const shape usage with kernels. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted top_k kernels to use const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected kernels declarations to adopt const shapes with helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored NDArray definitions to adopt const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shapes with image suppression helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Slight improvement with buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored buffer usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored buffer usage with tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shape usage with definitions. Signed-off-by: shugeo <sgazeos@gmail.com> * minor updates on cpu side Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Refactored const shape usage with ConstantDescritor and native ops with cuda platform. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored tear and tile kernels to adopt with const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * softmax_loop fix Signed-off-by: raver119 <raver119@gmail.com> * update missing signature Signed-off-by: raver119@gmail.com <raver119@gmail.com> * softmax again Signed-off-by: raver119@gmail.com <raver119@gmail.com> * few more missing consts Signed-off-by: raver119 <raver119@gmail.com> * new methods updated Signed-off-by: raver119@gmail.com <raver119@gmail.com> Co-authored-by: shugeo <sgazeos@gmail.com>
2020-05-09 07:06:14 +02:00
auto gradO_user_mem = dnnl::memory(gradO_user_md, engine, const_cast<void*>(gradO->buffer()));
const bool gradOReorderW = op_weights_bp_prim_desc.diff_dst_desc() != gradO_user_mem.get_desc();
const bool gradOReorderD = op_data_bp_prim_desc.diff_dst_desc() != gradO_user_mem.get_desc();
auto gradO_mkl_memW = gradOReorderW ? dnnl::memory(op_weights_bp_prim_desc.diff_dst_desc(), engine) : gradO_user_mem;
auto gradO_mkl_memD = gradOReorderD ? dnnl::memory(op_data_bp_prim_desc.diff_dst_desc(), engine) : gradO_user_mem;
if (gradOReorderW)
dnnl::reorder(gradO_user_mem, gradO_mkl_memW).execute(stream, gradO_user_mem, gradO_mkl_memW);
if (gradOReorderD)
dnnl::reorder(gradO_user_mem, gradO_mkl_memD).execute(stream, gradO_user_mem, gradO_mkl_memD);
args[DNNL_ARG_DIFF_DST] = gradO_mkl_memD;
// gradI
auto gradI_user_mem = mkldnnUtils::loadDataToMklStream(*gradI, engine, stream, gradI_user_md, op_data_bp_prim_desc.diff_src_desc(), args[DNNL_ARG_DIFF_SRC]);
// gradW
auto gradW_user_mem = mkldnnUtils::loadDataToMklStream(*gradW, engine, stream, gradW_user_md, op_weights_bp_prim_desc.diff_weights_desc(), args[DNNL_ARG_DIFF_WEIGHTS]);
// gradB
if(gradB != nullptr) {
Legacy API changes (#441) * initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * another initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * another initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one more initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next step Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Refactored buffer() and shapeInfo() methods usage with NDArray class. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt Graph class methods to use const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt choose op to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt where op shape method to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt lstsq op to use constant empty shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt matrix_diag_part op shape routine to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt determinant ops to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt mean_pairwssqerr_loss ops to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt shape methods for loss ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt log_loss op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt shape methods for ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt dilation2d ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted deconv2d ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted dynamicRNN op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods for ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods for lstm layer ops. Signed-off-by: shugeo <sgazeos@gmail.com> * few updates Signed-off-by: raver119@gmail.com <raver119@gmail.com> * first cuda tweak Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Adopt constant shapes for sconv2d ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt constant shapes for gru ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt constant shapes with shape methods for segment ops and so on. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted constant shapes with unsorted_segment_* ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted constant shapes with gamma op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods of reduce_stddev ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape methods for reduce_* ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt shape method for squeeze op. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt strided_slice shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored concat op shape method to adopt constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted shape method for mirror_pad op. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted split op shape method. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted tile ops shape methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Added const cast for mkldnn routines handles. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored logSoftMaxForVector_ routine to conform with proper data and shape pointer casts. Signed-off-by: shugeo <sgazeos@gmail.com> * Cosmetic changes to proper usage of constant pointers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored a couple shape comparators for strides and addBias helpers to proper use data pointers with inplace option. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored depthToSpace helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored histogram helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored im2col helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored gather and gatherND helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage on percentile helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed gather shape with helpers and range buffer usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with space to depth helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage and constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with LUP decomposition> Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored onehot_ helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pad and prefix to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactoed softmax helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed space to batch helpers to use buffers properly. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed stack and split helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with sparse to dense helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with mindistance_ helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with tile helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed constant shape usage with legacy pairwise bool ops. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored a couple of methods to adopt constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed broadcasting with constant shape." Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const usage with inplace reverse and constant shapes with legacy reduction. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored legacy ops with const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored sort to adopt constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected sort for constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed constant shape usage with special methods. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored Context to conform with constant shape usage. Signed-off-by: shugeo <sgazeos@gmail.com> * CUDA broadcasting headers Signed-off-by: raver119@gmail.com <raver119@gmail.com> * pairwise/indexreduce/random headers Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Refactored native ops to adopt constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * legacy reduce3/scalar headers Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Corrected pullRow signature and tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected routines to proper use of constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored tests to use constant shapes properly. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored legacy ops tests to use constant shapes properly. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored buffer usage with NDArray tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed native ops tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed special concat routine. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with test. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed buffer usage with a test. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored TAD.h and tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored calcStrides* routines to use constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed miscelaneous errors with constant shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * NativeOps const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Corrected definitions for declared functions. Signed-off-by: shugeo <sgazeos@gmail.com> * NativeOps const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * few more const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed const shapes with shape routines. Signed-off-by: shugeo <sgazeos@gmail.com> * few more const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed shape method for broadcastable case. Signed-off-by: shugeo <sgazeos@gmail.com> * few more const changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * xw_plus_b BP shape fn restored Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed signatures with broadcasting. Signed-off-by: shugeo <sgazeos@gmail.com> * Repaired backprops shape methods for a set of operations. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored broadcast bool for cuda. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored methods for 3 args with const qualifier. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed a couple of kernel signatures for broadcasting. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernels signatures for const buffers and shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pairwise methods to persistent buffers and shapes usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt const to buffers and shapes with kernels. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopt const to buffers and shapes with scalar kernels. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored indexreduce kernels signatures to use const buffers and shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pairwise kernels to adopt cons shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored pairwise bool kernels to adopt cons shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored random special ops to conform with const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored native ops to conform with const shapes and buffers under cuda platform. Signed-off-by: shugeo <sgazeos@gmail.com> * Cosmetical changes only. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shapes and buffers error. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected start pos routine. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored methods to conform with const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored helpers to use proper methods instead. Signed-off-by: shugeo <sgazeos@gmail.com> * bunch of changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next bunch of changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * next bunch of changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Fixed execScalar declaration. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed execScalar declaration. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected const shape cases with sort and so on. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shapes for sort. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored kernel declarations to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernels declarations to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected kernel declarations to adopt const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernels declarations to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed segment helpers kernels declarations and so on to adopt const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shape usage with segment and solve helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed kernel declaration with adjustWeight helper. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed cuda implementations for constant shape helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted const shape usage with kernels. Signed-off-by: shugeo <sgazeos@gmail.com> * Adopted top_k kernels to use const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Corrected kernels declarations to adopt const shapes with helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored NDArray definitions to adopt const shapes and buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shapes with image suppression helpers. Signed-off-by: shugeo <sgazeos@gmail.com> * Slight improvement with buffers. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored buffer usage. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored buffer usage with tests. Signed-off-by: shugeo <sgazeos@gmail.com> * Fixed const shape usage with definitions. Signed-off-by: shugeo <sgazeos@gmail.com> * minor updates on cpu side Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Refactored const shape usage with ConstantDescritor and native ops with cuda platform. Signed-off-by: shugeo <sgazeos@gmail.com> * Refactored tear and tile kernels to adopt with const shapes. Signed-off-by: shugeo <sgazeos@gmail.com> * softmax_loop fix Signed-off-by: raver119 <raver119@gmail.com> * update missing signature Signed-off-by: raver119@gmail.com <raver119@gmail.com> * softmax again Signed-off-by: raver119@gmail.com <raver119@gmail.com> * few more missing consts Signed-off-by: raver119 <raver119@gmail.com> * new methods updated Signed-off-by: raver119@gmail.com <raver119@gmail.com> Co-authored-by: shugeo <sgazeos@gmail.com>
2020-05-09 07:06:14 +02:00
auto gradB_mkl_mem = dnnl::memory(gradB_mkl_md, engine, gradB->buffer());
args[DNNL_ARG_DIFF_BIAS] = gradB_mkl_mem;
}
// run backward data calculations
dnnl::deconvolution_backward_data(op_data_bp_prim_desc).execute(stream, args);
if(gradOReorderW || gradOReorderD)
args[DNNL_ARG_DIFF_DST] = gradO_mkl_memW;
// run backward weights calculations
dnnl::deconvolution_backward_weights(op_weights_bp_prim_desc).execute(stream, args);
// reorder gradI if necessary
if (op_data_bp_prim_desc.diff_src_desc() != gradI_user_mem.get_desc())
dnnl::reorder(args[DNNL_ARG_DIFF_SRC], gradI_user_mem).execute(stream, args[DNNL_ARG_DIFF_SRC], gradI_user_mem);
if (op_weights_bp_prim_desc.diff_weights_desc() != gradW_user_mem.get_desc())
dnnl::reorder(args[DNNL_ARG_DIFF_WEIGHTS], gradW_user_mem).execute(stream, args[DNNL_ARG_DIFF_WEIGHTS], gradW_user_mem);
stream.wait();
// shape::printArray(z_mkl_mem.map_data<float>(),8);
}
//////////////////////////////////////////////////////////////////////////
cuDNN integration (#150) * initial commit Signed-off-by: raver119 <raver119@gmail.com> * one file Signed-off-by: raver119 <raver119@gmail.com> * few more includes Signed-off-by: raver119 <raver119@gmail.com> * m? Signed-off-by: raver119 <raver119@gmail.com> * const Signed-off-by: raver119 <raver119@gmail.com> * cudnn linkage in tests Signed-off-by: raver119 <raver119@gmail.com> * culibos Signed-off-by: raver119 <raver119@gmail.com> * static reminder Signed-off-by: raver119 <raver119@gmail.com> * platform engine tag Signed-off-by: raver119 <raver119@gmail.com> * HAVE_CUDNN moved to config.h.in Signed-off-by: raver119 <raver119@gmail.com> * include Signed-off-by: raver119 <raver119@gmail.com> * include Signed-off-by: raver119 <raver119@gmail.com> * skip cudnn handle creation if there's not cudnn Signed-off-by: raver119 <raver119@gmail.com> * meh Signed-off-by: raver119 <raver119@gmail.com> * target device in context Signed-off-by: raver119 <raver119@gmail.com> * platform engines Signed-off-by: raver119 <raver119@gmail.com> * platform engines Signed-off-by: raver119 <raver119@gmail.com> * allow multiple -h args Signed-off-by: raver119 <raver119@gmail.com> * allow multiple -h args Signed-off-by: raver119 <raver119@gmail.com> * move mkldnn out of CPU block Signed-off-by: raver119 <raver119@gmail.com> * link to mkldnn on cuda Signed-off-by: raver119 <raver119@gmail.com> * less prints Signed-off-by: raver119 <raver119@gmail.com> * minor tweaks Signed-off-by: raver119 <raver119@gmail.com> * next step Signed-off-by: raver119 <raver119@gmail.com> * conv2d NCHW draft Signed-off-by: raver119 <raver119@gmail.com> * conv2d biasAdd Signed-off-by: raver119 <raver119@gmail.com> * test for MKL/CUDNN combined use Signed-off-by: raver119 <raver119@gmail.com> * - provide additional code for conv2d ff based on cudnn api, not tested yet Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on conv2d helper based on using cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - fixing several cuda bugs which appeared after cudnn lib had been started to use Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of conv2d backprop op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - implementaion of conv3d and conv3d_bp ops based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - bugs fixing in conv3d/conv3d_bp ops (cudnn in use) Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of depthwiseConv2d (ff/bp) op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of batchnorm ff op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - disable cudnn batchnorm temporary Signed-off-by: Yurii <iuriish@yahoo.com> * - add minor change in cmake Signed-off-by: Yurii <iuriish@yahoo.com> * engine for depthwise mkldnn Signed-off-by: raver119 <raver119@gmail.com> * couple of includes Signed-off-by: raver119 <raver119@gmail.com> * - provide permutation to cudnn batchnorm ff when format is NHWC Signed-off-by: Yurii <iuriish@yahoo.com> * lgamma fix Signed-off-by: raver119 <raver119@gmail.com> * - eliminate memory leak in two tests Signed-off-by: Yurii <iuriish@yahoo.com> Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2020-01-20 19:32:46 +01:00
PLATFORM_IMPL(deconv3d, ENGINE_CPU) {
auto input = INPUT_VARIABLE(0); // [bS, iD, iH, iW, iC] (NDHWC) or [bS, iC, iD, iH, iW] (NCDHW)
auto weights = INPUT_VARIABLE(1); // [kD, kH, kW, oC, iC], [iC, oC, kD, kH, kW], [iC, kD, kH, kW, oC]
auto bias = block.width() > 2 ? INPUT_VARIABLE(2) : nullptr; // [oC]
auto output = OUTPUT_VARIABLE(0); // [bS, oD, oH, oW, oC] (NDHWC) or [bS, oC, oD, oH, oW] (NCDHW)
REQUIRE_TRUE(input->rankOf() == 5, 0, "CUSTOM DECONV3D_MKLDNN OP: rank of input array must be equal to 5, but got %i instead !", input->rankOf());
REQUIRE_TRUE(weights->rankOf() == 5, 0, "CUSTOM DECONV3D_MKLDNN OP: rank of weights array must be equal to 5, but got %i instead !", weights->rankOf());
int kD = INT_ARG(0) > 0 ? INT_ARG(0) : static_cast<int>(weights->sizeAt(0)); // filter(kernel) depth
int kH = INT_ARG(1) > 0 ? INT_ARG(1) : static_cast<int>(weights->sizeAt(1)); // filter(kernel) height
int kW = INT_ARG(2) > 0 ? INT_ARG(2) : static_cast<int>(weights->sizeAt(2)); // filter(kernel) width
int sD = INT_ARG(3); // strides depth
int sH = INT_ARG(4); // strides height
int sW = INT_ARG(5); // strides width
int pD = INT_ARG(6); // paddings depth
int pH = INT_ARG(7); // paddings height
int pW = INT_ARG(8); // paddings width
int dD = INT_ARG(9); // dilations depth
int dH = INT_ARG(10); // dilations height
int dW = INT_ARG(11); // dilations width
int isSameMode = INT_ARG(12); // 0-SAME, 1-VALID
int isNCDHW = block.getIArguments()->size() > 13 ? !INT_ARG(13) : 1; // INT_ARG(13): 1-NDHWC, 0-NCDHW
int wFormat = block.getIArguments()->size() > 14 ? INT_ARG(14) : 0; // 0 - [kD, kH, kW, oC, iC], 1 - [iC, oC, kD, kH, kW], 2 - [iC, kD, kH, kW, oC]
int bS, iC, iD, iH, iW, oC, oD, oH, oW; // batch size, input channels, input depth/height/width, output channels, output depth/height/width;
int indIOioC, indIOioD, indWoC, indWiC, indWkD; // corresponding indexes
ConvolutionUtils::getSizesAndIndexesConv3d(isNCDHW, wFormat, *input, *output, bS, iC, iD, iH, iW, oC, oD, oH, oW, indIOioC, indIOioD, indWoC, indWiC, indWkD);
std::vector<Nd4jLong> expectedWeightsShape = ConvolutionUtils::expectWeightsShape(wFormat, kD, kH, kW, oC, iC);
REQUIRE_TRUE(weights->isSameShape(expectedWeightsShape), 0, "CUSTOM DECONV3D_MKLDNN OP: wrong shape of weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(expectedWeightsShape).c_str(), ShapeUtils::shapeAsString(weights).c_str());
if (bias)
REQUIRE_TRUE(bias->rankOf() <= 2 && oC == bias->lengthOf(), 0, "CUSTOM DECONV3D_MKLDNN OP: wrong shape of array with biases, expected rank, length: <=2, %i, but got %i, %i instead !", oC, bias->rankOf(), bias->lengthOf());
if(isSameMode){ // SAME
//Note: we're intentionally swapping iH and oH, to calculated the padding for a"normal" conv (not deconv) forward pass
ConvolutionUtils::calcPadding3D(pD, pH, pW, iD, iH, iW, oD, oH, oW, kD, kH, kW, sD, sH, sW, dD, dH, dW);
}
deconv3dMKLDNN(input, weights, bias, output, kD, kH, kW, sD, sH, sW, pD, pH, pW, dD, dH, dW, isNCDHW, wFormat);
return Status::OK();
}
cuDNN integration (#150) * initial commit Signed-off-by: raver119 <raver119@gmail.com> * one file Signed-off-by: raver119 <raver119@gmail.com> * few more includes Signed-off-by: raver119 <raver119@gmail.com> * m? Signed-off-by: raver119 <raver119@gmail.com> * const Signed-off-by: raver119 <raver119@gmail.com> * cudnn linkage in tests Signed-off-by: raver119 <raver119@gmail.com> * culibos Signed-off-by: raver119 <raver119@gmail.com> * static reminder Signed-off-by: raver119 <raver119@gmail.com> * platform engine tag Signed-off-by: raver119 <raver119@gmail.com> * HAVE_CUDNN moved to config.h.in Signed-off-by: raver119 <raver119@gmail.com> * include Signed-off-by: raver119 <raver119@gmail.com> * include Signed-off-by: raver119 <raver119@gmail.com> * skip cudnn handle creation if there's not cudnn Signed-off-by: raver119 <raver119@gmail.com> * meh Signed-off-by: raver119 <raver119@gmail.com> * target device in context Signed-off-by: raver119 <raver119@gmail.com> * platform engines Signed-off-by: raver119 <raver119@gmail.com> * platform engines Signed-off-by: raver119 <raver119@gmail.com> * allow multiple -h args Signed-off-by: raver119 <raver119@gmail.com> * allow multiple -h args Signed-off-by: raver119 <raver119@gmail.com> * move mkldnn out of CPU block Signed-off-by: raver119 <raver119@gmail.com> * link to mkldnn on cuda Signed-off-by: raver119 <raver119@gmail.com> * less prints Signed-off-by: raver119 <raver119@gmail.com> * minor tweaks Signed-off-by: raver119 <raver119@gmail.com> * next step Signed-off-by: raver119 <raver119@gmail.com> * conv2d NCHW draft Signed-off-by: raver119 <raver119@gmail.com> * conv2d biasAdd Signed-off-by: raver119 <raver119@gmail.com> * test for MKL/CUDNN combined use Signed-off-by: raver119 <raver119@gmail.com> * - provide additional code for conv2d ff based on cudnn api, not tested yet Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on conv2d helper based on using cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - fixing several cuda bugs which appeared after cudnn lib had been started to use Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of conv2d backprop op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - implementaion of conv3d and conv3d_bp ops based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - bugs fixing in conv3d/conv3d_bp ops (cudnn in use) Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of depthwiseConv2d (ff/bp) op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of batchnorm ff op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - disable cudnn batchnorm temporary Signed-off-by: Yurii <iuriish@yahoo.com> * - add minor change in cmake Signed-off-by: Yurii <iuriish@yahoo.com> * engine for depthwise mkldnn Signed-off-by: raver119 <raver119@gmail.com> * couple of includes Signed-off-by: raver119 <raver119@gmail.com> * - provide permutation to cudnn batchnorm ff when format is NHWC Signed-off-by: Yurii <iuriish@yahoo.com> * lgamma fix Signed-off-by: raver119 <raver119@gmail.com> * - eliminate memory leak in two tests Signed-off-by: Yurii <iuriish@yahoo.com> Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2020-01-20 19:32:46 +01:00
PLATFORM_CHECK(deconv3d, ENGINE_CPU) {
auto input = INPUT_VARIABLE(0);
auto weights = INPUT_VARIABLE(1);
auto bias = block.width() > 2 ? INPUT_VARIABLE(2) : nullptr;
auto output = INPUT_VARIABLE(0);
int dD = INT_ARG(9); // dilations depth
int dH = INT_ARG(10); // dilations height
int dW = INT_ARG(11); // dilations width
int isSameMode = INT_ARG(12); // 0-SAME, 1-VALID
const DataType xType = input->dataType();
const DataType wType = weights->dataType();
const DataType zType = output->dataType();
const DataType bType = bias != nullptr ? bias->dataType() : zType;
return block.isUseMKLDNN() && (dD <= 1 && dH <= 1 && dW <= 1 && !isSameMode) &&
(
(xType==DataType::FLOAT32 && wType==DataType::FLOAT32 && bType==DataType::FLOAT32 && zType==DataType::FLOAT32) ||
((xType==DataType::UINT8 || xType==DataType::INT8) && wType==DataType::INT8 && (zType==DataType::UINT8 || zType==DataType::INT8 || zType==DataType::INT32 || zType==DataType::FLOAT32) && bType == zType)
);
}
//////////////////////////////////////////////////////////////////////////
cuDNN integration (#150) * initial commit Signed-off-by: raver119 <raver119@gmail.com> * one file Signed-off-by: raver119 <raver119@gmail.com> * few more includes Signed-off-by: raver119 <raver119@gmail.com> * m? Signed-off-by: raver119 <raver119@gmail.com> * const Signed-off-by: raver119 <raver119@gmail.com> * cudnn linkage in tests Signed-off-by: raver119 <raver119@gmail.com> * culibos Signed-off-by: raver119 <raver119@gmail.com> * static reminder Signed-off-by: raver119 <raver119@gmail.com> * platform engine tag Signed-off-by: raver119 <raver119@gmail.com> * HAVE_CUDNN moved to config.h.in Signed-off-by: raver119 <raver119@gmail.com> * include Signed-off-by: raver119 <raver119@gmail.com> * include Signed-off-by: raver119 <raver119@gmail.com> * skip cudnn handle creation if there's not cudnn Signed-off-by: raver119 <raver119@gmail.com> * meh Signed-off-by: raver119 <raver119@gmail.com> * target device in context Signed-off-by: raver119 <raver119@gmail.com> * platform engines Signed-off-by: raver119 <raver119@gmail.com> * platform engines Signed-off-by: raver119 <raver119@gmail.com> * allow multiple -h args Signed-off-by: raver119 <raver119@gmail.com> * allow multiple -h args Signed-off-by: raver119 <raver119@gmail.com> * move mkldnn out of CPU block Signed-off-by: raver119 <raver119@gmail.com> * link to mkldnn on cuda Signed-off-by: raver119 <raver119@gmail.com> * less prints Signed-off-by: raver119 <raver119@gmail.com> * minor tweaks Signed-off-by: raver119 <raver119@gmail.com> * next step Signed-off-by: raver119 <raver119@gmail.com> * conv2d NCHW draft Signed-off-by: raver119 <raver119@gmail.com> * conv2d biasAdd Signed-off-by: raver119 <raver119@gmail.com> * test for MKL/CUDNN combined use Signed-off-by: raver119 <raver119@gmail.com> * - provide additional code for conv2d ff based on cudnn api, not tested yet Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on conv2d helper based on using cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - fixing several cuda bugs which appeared after cudnn lib had been started to use Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of conv2d backprop op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - implementaion of conv3d and conv3d_bp ops based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - bugs fixing in conv3d/conv3d_bp ops (cudnn in use) Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of depthwiseConv2d (ff/bp) op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of batchnorm ff op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - disable cudnn batchnorm temporary Signed-off-by: Yurii <iuriish@yahoo.com> * - add minor change in cmake Signed-off-by: Yurii <iuriish@yahoo.com> * engine for depthwise mkldnn Signed-off-by: raver119 <raver119@gmail.com> * couple of includes Signed-off-by: raver119 <raver119@gmail.com> * - provide permutation to cudnn batchnorm ff when format is NHWC Signed-off-by: Yurii <iuriish@yahoo.com> * lgamma fix Signed-off-by: raver119 <raver119@gmail.com> * - eliminate memory leak in two tests Signed-off-by: Yurii <iuriish@yahoo.com> Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2020-01-20 19:32:46 +01:00
PLATFORM_IMPL(deconv3d_bp, ENGINE_CPU) {
auto input = INPUT_VARIABLE(0); // [bS, iD, iH, iW, iC] (NDHWC) or [bS, iC, iD, iH, iW] (NCDHW)
auto weights = INPUT_VARIABLE(1); // [kD, kH, kW, oC, iC], [iC, oC, kD, kH, kW], [iC, kD, kH, kW, oC]
auto bias = block.width() > 3 ? INPUT_VARIABLE(2) : nullptr; // [oC]
auto gradO = block.width() > 3 ? INPUT_VARIABLE(3) : INPUT_VARIABLE(2); // [bS, oD, oH, oW, oC] (NDHWC) or [bS, oC, oD, oH, oW] (NCDHW), epsilon_next
auto gradI = OUTPUT_VARIABLE(0); // [bS, iD, iH, iW, iC] (NDHWC) or [bS, iC, iD, iH, iW] (NCDHW), gradI
auto gradW = OUTPUT_VARIABLE(1); // [kD, kH, kW, oC, iC], [iC, oC, kD, kH, kW], [iC, kD, kH, kW, oC]
auto gradB = block.width() > 3 ? OUTPUT_VARIABLE(2) : nullptr; // [oC]
REQUIRE_TRUE(input->rankOf() == 5, 0, "CUSTOM DECONV3D_MKLDNN_BP OP: rank of input array must be equal to 5, but got %i instead !", input->rankOf());
REQUIRE_TRUE(weights->rankOf() == 5, 0, "CUSTOM DECONV3D_MKLDNN_BP OP: rank of weights array must be equal to 5 , but got %i instead !", weights->rankOf());
REQUIRE_TRUE(gradO->rankOf() == 5, 0, "CUSTOM DECONV3D_MKLDNN_BP OP: rank of output gradients (next epsilon) array must be equal to 5, but got %i instead !", gradO->rankOf());
int kD = INT_ARG(0) > 0 ? INT_ARG(0) : static_cast<int>(weights->sizeAt(0));// filter(kernel) depth
int kH = INT_ARG(1) > 0 ? INT_ARG(1) : static_cast<int>(weights->sizeAt(1));// filter(kernel) height
int kW = INT_ARG(2) > 0 ? INT_ARG(2) : static_cast<int>(weights->sizeAt(2));// filter(kernel) width
int sD = INT_ARG(3); // strides depth
int sH = INT_ARG(4); // strides height
int sW = INT_ARG(5); // strides width
int pD = INT_ARG(6); // paddings depth
int pH = INT_ARG(7); // paddings height
int pW = INT_ARG(8); // paddings width
int dD = INT_ARG(9); // dilations depth
int dH = INT_ARG(10); // dilations height
int dW = INT_ARG(11); // dilations width
int isSameMode = INT_ARG(12); // 0-SAME, 1-VALID
int isNCDHW = block.getIArguments()->size() > 13 ? !INT_ARG(13) : 1; // INT_ARG(13): 1-NDHWC, 0-NCDHW
int wFormat = block.getIArguments()->size() > 14 ? INT_ARG(14) : 0; // 0 - [kD, kH, kW, oC, iC], 1 - [iC, oC, kD, kH, kW], 2 - [iC, kD, kH, kW, oC]
int bS, iC, iD, iH, iW, oC, oD, oH, oW; // batch size, input channels, input depth/height/width, output channels, output depth/height/width;
int indIOioC, indIOioD, indWoC, indWiC, indWkD; // corresponding indexes
ConvolutionUtils::getSizesAndIndexesConv3d(isNCDHW, wFormat, *input, *gradO, bS, iC, iD, iH, iW, oC, oD, oH, oW, indIOioC, indIOioD, indWoC, indWiC, indWkD);
int trueoD, trueoH, trueoW; // true output height, width
ConvolutionUtils::calcOutSizeDeconv3D(trueoD, trueoH, trueoW, kD, kH, kW, sD, sH, sW, pD, pH, pW, dD, dH, dW, iD, iH, iW, isSameMode);
std::vector<Nd4jLong> expectedGradOShape = ShapeUtils::composeShapeUsingDimsAndIdx({bS,oC,trueoD,trueoH,trueoW, 0,indIOioC,indIOioD,indIOioD+1,indIOioD+2});
std::vector<Nd4jLong> expectedWeightsShape = ConvolutionUtils::expectWeightsShape(wFormat, kD, kH, kW, oC, iC);
REQUIRE_TRUE(gradO->isSameShape(expectedGradOShape), 0, "CUSTOM DECONV3D_MKLDNN_BP OP: wrong shape of output gradients (next epsilon) array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(expectedGradOShape).c_str(), ShapeUtils::shapeAsString(gradO).c_str());
REQUIRE_TRUE(weights->isSameShape(expectedWeightsShape), 0, "CUSTOM DECONV3D_MKLDNN_BP OP: wrong shape of weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(expectedWeightsShape).c_str(), ShapeUtils::shapeAsString(weights).c_str());
if(bias)
REQUIRE_TRUE(bias->rankOf() <= 2 && oC == bias->lengthOf(), 0, "CUSTOM DECONV3D_MKLDNN_BP OP: wrong shape of array with biases, expected rank, length: <=2, %i, but got %i, %i instead !", oC, bias->rankOf(), bias->lengthOf());
if(isSameMode) // Note: we're intentionally swapping iH and oH, to calculated the padding for a"normal" conv (not deconv) forward pass
ConvolutionUtils::calcPadding3D(pD, pH, pW, iD, iH, iW, oD, oH, oW, kD, kH, kW, sD, sH, sW, dD, dH, dW);
deconv3dBackPropMKLDNN(input, weights, gradO, gradI, gradW, gradB, kD, kH, kW, sD, sH, sW, pD, pH, pW, dD, dH, dW, isNCDHW, wFormat);
return Status::OK();
}
cuDNN integration (#150) * initial commit Signed-off-by: raver119 <raver119@gmail.com> * one file Signed-off-by: raver119 <raver119@gmail.com> * few more includes Signed-off-by: raver119 <raver119@gmail.com> * m? Signed-off-by: raver119 <raver119@gmail.com> * const Signed-off-by: raver119 <raver119@gmail.com> * cudnn linkage in tests Signed-off-by: raver119 <raver119@gmail.com> * culibos Signed-off-by: raver119 <raver119@gmail.com> * static reminder Signed-off-by: raver119 <raver119@gmail.com> * platform engine tag Signed-off-by: raver119 <raver119@gmail.com> * HAVE_CUDNN moved to config.h.in Signed-off-by: raver119 <raver119@gmail.com> * include Signed-off-by: raver119 <raver119@gmail.com> * include Signed-off-by: raver119 <raver119@gmail.com> * skip cudnn handle creation if there's not cudnn Signed-off-by: raver119 <raver119@gmail.com> * meh Signed-off-by: raver119 <raver119@gmail.com> * target device in context Signed-off-by: raver119 <raver119@gmail.com> * platform engines Signed-off-by: raver119 <raver119@gmail.com> * platform engines Signed-off-by: raver119 <raver119@gmail.com> * allow multiple -h args Signed-off-by: raver119 <raver119@gmail.com> * allow multiple -h args Signed-off-by: raver119 <raver119@gmail.com> * move mkldnn out of CPU block Signed-off-by: raver119 <raver119@gmail.com> * link to mkldnn on cuda Signed-off-by: raver119 <raver119@gmail.com> * less prints Signed-off-by: raver119 <raver119@gmail.com> * minor tweaks Signed-off-by: raver119 <raver119@gmail.com> * next step Signed-off-by: raver119 <raver119@gmail.com> * conv2d NCHW draft Signed-off-by: raver119 <raver119@gmail.com> * conv2d biasAdd Signed-off-by: raver119 <raver119@gmail.com> * test for MKL/CUDNN combined use Signed-off-by: raver119 <raver119@gmail.com> * - provide additional code for conv2d ff based on cudnn api, not tested yet Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on conv2d helper based on using cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - fixing several cuda bugs which appeared after cudnn lib had been started to use Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of conv2d backprop op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - implementaion of conv3d and conv3d_bp ops based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - bugs fixing in conv3d/conv3d_bp ops (cudnn in use) Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of depthwiseConv2d (ff/bp) op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of batchnorm ff op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - disable cudnn batchnorm temporary Signed-off-by: Yurii <iuriish@yahoo.com> * - add minor change in cmake Signed-off-by: Yurii <iuriish@yahoo.com> * engine for depthwise mkldnn Signed-off-by: raver119 <raver119@gmail.com> * couple of includes Signed-off-by: raver119 <raver119@gmail.com> * - provide permutation to cudnn batchnorm ff when format is NHWC Signed-off-by: Yurii <iuriish@yahoo.com> * lgamma fix Signed-off-by: raver119 <raver119@gmail.com> * - eliminate memory leak in two tests Signed-off-by: Yurii <iuriish@yahoo.com> Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2020-01-20 19:32:46 +01:00
PLATFORM_CHECK(deconv3d_bp, ENGINE_CPU) {
auto input = INPUT_VARIABLE(0); // [bS, iD, iH, iW, iC] (NHWC) or [bS, iD, iC, iH, iW] (NCDHW)
auto weights = INPUT_VARIABLE(1); // [kD, kH, kW, oC, iC], [iC, oC, kD, kH, kW], [iC, kD, kH, kW, oC]
auto bias = block.width() > 3 ? INPUT_VARIABLE(2) : nullptr; // [oC]
auto gradO = block.width() > 3 ? INPUT_VARIABLE(3) : INPUT_VARIABLE(2); // [bS, oD, oH, oW, oC] (NHWC) or [bS, oC, oD, oH, oW] (NCDHW), epsilon_next
auto gradI = OUTPUT_VARIABLE(0); // [bS, iD, iH, iW, iC] (NHWC) or [bS, iC, iD, iH, iW] (NCDHW), gradI
auto gradW = OUTPUT_VARIABLE(1); // [kD, kH, kW, oC, iC], [iC, oC, kD, kH, kW], [iC, kD, kH, kW, oC]
auto gradB = block.width() > 3 ? OUTPUT_VARIABLE(2) : nullptr; // [oC]
int dD = INT_ARG(9); // dilations depth
int dH = INT_ARG(10); // dilations height
int dW = INT_ARG(11); // dilations width
int isSameMode = INT_ARG(12); // 0-SAME, 1-VALID
const DataType xType = input->dataType();
const DataType wType = weights->dataType();
const DataType gradOType = gradO->dataType();
const DataType gradIType = gradI->dataType();
const DataType gradWType = gradW->dataType();
const DataType gradBType = gradB != nullptr ? gradB->dataType() : DataType::FLOAT32;
return block.isUseMKLDNN() && (dD <= 1 && dH <= 1 && dW <= 1 && !isSameMode) && ((xType==DataType::FLOAT32 || xType==DataType::BFLOAT16) && (wType==DataType::FLOAT32 || wType==DataType::BFLOAT16) && (gradOType==DataType::FLOAT32 || gradOType==DataType::BFLOAT16) && (gradIType==DataType::FLOAT32 || gradIType==DataType::BFLOAT16) && (gradWType==DataType::FLOAT32 || gradWType==DataType::BFLOAT16) && (gradBType==DataType::FLOAT32 || gradBType==DataType::BFLOAT16) );
}
}
}
}