raver119 c969b724bb [WIP] more CUDA stuff (#57)
* initial commit

Signed-off-by: raver119 <raver119@gmail.com>

* Added gradcheck test for dynamic_partition_bp op.

* - implementation of dilation op (cpu and cuda)

Signed-off-by: Yurii <yurii@skymind.io>

* Fixed broadcast_dynamic_shape 1D case and tests.

* Fixed usage of default integer arguments.

* Fixed dynamic_partition_bp op and tests.

* Eliminated test with grad check for dynamic_partition_bp op.

* start working on cuda svd - porting available corresponding api from cuSOLVER library

Signed-off-by: Yurii <yurii@skymind.io>

* provide prelu_bp

Signed-off-by: Yurii <yurii@skymind.io>

* - provide gruCell_bp (old version ??)

Signed-off-by: Yurii <yurii@skymind.io>

* - polishing cumsum_bp and cumprod_bp tests

Signed-off-by: Yurii <yurii@skymind.io>

* provide sparseSoftmaxCrossEntropyWithLogits and sparseSoftmaxCrossEntropyWithLogits_grad

Signed-off-by: Yurii <yurii@skymind.io>

* Fixed atomicMul with float input/output

* implementation of cuda kernel for triu_bp operation

Signed-off-by: Yurii <yurii@skymind.io>

* Refactored lup helper to add parrallel computing.

* cusolver libraries

Signed-off-by: raver119 <raver119@gmail.com>

* uncomment cuSolver APIs in svd.cu

Signed-off-by: Yurii <yurii@skymind.io>

* cusolver var

Signed-off-by: raver119 <raver119@gmail.com>

* - further work on cuSolver svd

Signed-off-by: Yurii <yurii@skymind.io>

* Implement usage of cuda solver to LUP decomposition.

* - correct naames in lup functions

Signed-off-by: Yurii <yurii@skymind.io>

* correct svdQR cuda

Signed-off-by: Yurii <yurii@skymind.io>

* - provide transpositions of input matrices in case of c order in svdCudaQR

Signed-off-by: Yurii <yurii@skymind.io>

* Fixed implementation issues with LUP usign cuda solver.

* Implementation of matrix_determinant helper with cuda kernels. Working revision.

* Implemented log_matrix_determinant helper with cuda kernels.

* - implementation of batched cuda svd

Signed-off-by: Yurii <yurii@skymind.io>

* Refactored cholesky helper and implementation of cuda solver cholesky batch.

* - implementation of cuda kernel for tile bp

Signed-off-by: Yurii <yurii@skymind.io>

* Implementation of cholesky and logdet with cuda kernels.

* - implementation of cuda kernel for sru_bidirectional

Signed-off-by: Yurii <yurii@skymind.io>

* Fixed cholesky helper.

* Cholesky op helper implementation. Working double-based cublas implementation.

* bad import excluded

Signed-off-by: raver119 <raver119@gmail.com>

* Finished with cuda implementation of cholesky helper and tests.

* - implementation of cuda kernel for sru_bidirectional_backprop operation

Signed-off-by: Yurii <yurii@skymind.io>

* Implementation of matrix_inverse op helper with cuda kernels. The first revision.

* - start working on gruCell_bp

Signed-off-by: Yurii <yurii@skymind.io>

* Implementation of matrix_inverse helper.

* - further work on new gruCell_bp

Signed-off-by: Yurii <yurii@skymind.io>

* cuBLAS related fixes

Signed-off-by: raver119 <raver119@gmail.com>

* calculateOutputShapes() now passes device buffers as well

Signed-off-by: raver119 <raver119@gmail.com>

* special concat/average/accumulate init host pointers now

Signed-off-by: raver119 <raver119@gmail.com>

* few more tweaks

Signed-off-by: raver119 <raver119@gmail.com>

* additional CudaDataBufferFactory signatures certain for data types

Signed-off-by: raver119 <raver119@gmail.com>

* cuSolver host buffer

Signed-off-by: raver119 <raver119@gmail.com>

* buffer to buffer memcpy host ptr allocation

Signed-off-by: raver119 <raver119@gmail.com>
2019-07-20 23:05:21 +10:00

115 lines
3.8 KiB
C++

/*******************************************************************************
* 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), created on 20.01.2018
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_svd)
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/svd.h>
namespace nd4j {
namespace ops {
CUSTOM_OP_IMPL(svd, 1, 1, false, 0, 3) {
auto x = INPUT_VARIABLE(0);
const int rank = x->rankOf();
REQUIRE_TRUE(rank >= 2 , 0, "SVD OP: the rank of input array must be >=2, but got %i instead!", rank);
const bool fullUV = (bool)INT_ARG(0);
const bool calcUV = (bool)INT_ARG(1);
const int switchNum = INT_ARG(2);
// #ifndef __CUDABLAS__
helpers::svd(block.launchContext(), x, {OUTPUT_VARIABLE(0), calcUV ? OUTPUT_VARIABLE(1) : nullptr, calcUV ? OUTPUT_VARIABLE(2) : nullptr}, fullUV, calcUV, switchNum);
// #endif
return Status::OK();;
}
DECLARE_TYPES(svd) {
getOpDescriptor()
->setAllowedInputTypes(0, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF})
->setSameMode(true);
}
DECLARE_SHAPE_FN(svd) {
auto inShapeInfo = inputShape->at(0);
bool fullUV = (bool)INT_ARG(0);
bool calcUV = (bool)INT_ARG(1);
const int rank = inShapeInfo[0];
REQUIRE_TRUE(rank >= 2 , 0, "SVD OP: the rank of input array must be >=2, but got %i instead!", rank);
const int diagSize = inShapeInfo[rank] < inShapeInfo[rank-1] ? inShapeInfo[rank] : inShapeInfo[rank-1];
Nd4jLong* sShapeInfo(nullptr);
if(rank == 2) {
ALLOCATE(sShapeInfo, block.getWorkspace(), shape::shapeInfoLength(1), Nd4jLong);
sShapeInfo[0] = 1;
sShapeInfo[1] = diagSize;
}
else {
ALLOCATE(sShapeInfo, block.getWorkspace(), shape::shapeInfoLength(rank-1), Nd4jLong);
sShapeInfo[0] = rank - 1;
for(int i=1; i <= rank-2; ++i)
sShapeInfo[i] = inShapeInfo[i];
sShapeInfo[rank-1] = diagSize;
}
ShapeUtils::updateStridesAndType(sShapeInfo, inShapeInfo, shape::order(inShapeInfo));
if(calcUV){
Nd4jLong *uShapeInfo(nullptr), *vShapeInfo(nullptr);
COPY_SHAPE(inShapeInfo, uShapeInfo);
COPY_SHAPE(inShapeInfo, vShapeInfo);
if(fullUV) {
uShapeInfo[rank] = uShapeInfo[rank-1];
vShapeInfo[rank-1] = vShapeInfo[rank];
}
else {
uShapeInfo[rank] = diagSize;
vShapeInfo[rank-1] = vShapeInfo[rank];
vShapeInfo[rank] = diagSize;
}
shape::updateStrides(uShapeInfo, shape::order(inShapeInfo));
shape::updateStrides(vShapeInfo, shape::order(inShapeInfo));
auto result = SHAPELIST(ConstantShapeHelper::getInstance()->createShapeInfo(ShapeDescriptor(sShapeInfo)), ConstantShapeHelper::getInstance()->createShapeInfo(ShapeDescriptor(uShapeInfo)), ConstantShapeHelper::getInstance()->createShapeInfo(ShapeDescriptor(vShapeInfo)));
RELEASE(sShapeInfo, block.workspace());
RELEASE(uShapeInfo, block.workspace());
RELEASE(vShapeInfo, block.workspace());
return result;
}
return SHAPELIST(ConstantShapeHelper::getInstance()->createFromExisting(sShapeInfo, block.workspace()));
}
}
}
#endif