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Commit 2e9e1bab authored by Mccaskey, Alex's avatar Mccaskey, Alex
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updating Eigen unsupported to latest from dev 



Signed-off-by: Mccaskey, Alex's avatarAlex McCaskey <mccaskeyaj@ornl.gov>
parent 8ae5ae9e
Pipeline #39760 passed with stages
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tpls/eigen/unsupported/CMakeLists.txt
View file @ 2e9e1bab
add_subdirectory(Eigen)
add_subdirectory(doc EXCLUDE_FROM_ALL)
if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
add_subdirectory(test) # can't do EXCLUDE_FROM_ALL here, breaks CTest
else()
add_subdirectory(test EXCLUDE_FROM_ALL)
if(BUILD_TESTING)
if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
add_subdirectory(test) # can't do EXCLUDE_FROM_ALL here, breaks CTest
else()
add_subdirectory(test EXCLUDE_FROM_ALL)
endif()
endif()
tpls/eigen/unsupported/Eigen/AdolcForward
View file @ 2e9e1bab
......@@ -40,7 +40,7 @@
# undef realloc
#endif
#include <Eigen/Core>
#include "../../Eigen/Core"
namespace Eigen {
......
tpls/eigen/unsupported/Eigen/AlignedVector3
View file @ 2e9e1bab
......@@ -10,7 +10,9 @@
#ifndef EIGEN_ALIGNED_VECTOR3
#define EIGEN_ALIGNED_VECTOR3
#include <Eigen/Geometry>
#include "../../Eigen/Geometry"
#include "../../Eigen/src/Core/util/DisableStupidWarnings.h"
namespace Eigen {
......@@ -221,4 +223,6 @@ struct evaluator<AlignedVector3<Scalar> >
}
#include "../../Eigen/src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_ALIGNED_VECTOR3
tpls/eigen/unsupported/Eigen/ArpackSupport
View file @ 2e9e1bab
......@@ -9,9 +9,7 @@
#ifndef EIGEN_ARPACKSUPPORT_MODULE_H
#define EIGEN_ARPACKSUPPORT_MODULE_H
#include <Eigen/Core>
#include <Eigen/src/Core/util/DisableStupidWarnings.h>
#include "../../Eigen/Core"
/** \defgroup ArpackSupport_Module Arpack support module
*
......@@ -22,10 +20,12 @@
* \endcode
*/
#include <Eigen/SparseCholesky>
#include "../../Eigen/SparseCholesky"
#include "../../Eigen/src/Core/util/DisableStupidWarnings.h"
#include "src/Eigenvalues/ArpackSelfAdjointEigenSolver.h"
#include <Eigen/src/Core/util/ReenableStupidWarnings.h>
#include "../../Eigen/src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_ARPACKSUPPORT_MODULE_H
/* vim: set filetype=cpp et sw=2 ts=2 ai: */
tpls/eigen/unsupported/Eigen/AutoDiff
View file @ 2e9e1bab
......@@ -28,11 +28,17 @@ namespace Eigen {
//@{
}
#include "../../Eigen/src/Core/util/DisableStupidWarnings.h"
#include "src/AutoDiff/AutoDiffScalar.h"
// #include "src/AutoDiff/AutoDiffVector.h"
#include "src/AutoDiff/AutoDiffJacobian.h"
#include "../../Eigen/src/Core/util/ReenableStupidWarnings.h"
namespace Eigen {
//@}
}
......
tpls/eigen/unsupported/Eigen/BVH
View file @ 2e9e1bab
......@@ -10,9 +10,9 @@
#ifndef EIGEN_BVH_MODULE_H
#define EIGEN_BVH_MODULE_H
#include <Eigen/Core>
#include <Eigen/Geometry>
#include <Eigen/StdVector>
#include "../../Eigen/Core"
#include "../../Eigen/Geometry"
#include "../../Eigen/StdVector"
#include <algorithm>
#include <queue>
......
tpls/eigen/unsupported/Eigen/CXX11/Tensor
View file @ 2e9e1bab
......@@ -19,16 +19,16 @@
#undef isnan
#undef isinf
#undef isfinite
#include <SYCL/sycl.hpp>
#include <CL/sycl.hpp>
#include <iostream>
#include <map>
#include <memory>
#include <utility>
#endif
#include <Eigen/src/Core/util/DisableStupidWarnings.h>
#include "../SpecialFunctions"
#include "../../../Eigen/src/Core/util/DisableStupidWarnings.h"
#include "src/util/CXX11Meta.h"
#include "src/util/MaxSizeVector.h"
......@@ -40,6 +40,8 @@
* \code
* #include <Eigen/CXX11/Tensor>
* \endcode
*
* Much of the documentation can be found \ref eigen_tensors "here".
*/
#include <cmath>
......@@ -80,12 +82,16 @@ typedef unsigned __int64 uint64_t;
#endif
#ifdef EIGEN_USE_GPU
#include <iostream>
#include <cuda_runtime.h>
#if __cplusplus >= 201103L
#include <atomic>
#include <unistd.h>
#endif
#include <iostream>
#if defined(EIGEN_USE_HIP)
#include <hip/hip_runtime.h>
#else
#include <cuda_runtime.h>
#endif
#if __cplusplus >= 201103L
#include <atomic>
#include <unistd.h>
#endif
#endif
#include "src/Tensor/TensorMacros.h"
......@@ -95,7 +101,10 @@ typedef unsigned __int64 uint64_t;
#include "src/Tensor/TensorCostModel.h"
#include "src/Tensor/TensorDeviceDefault.h"
#include "src/Tensor/TensorDeviceThreadPool.h"
#include "src/Tensor/TensorDeviceCuda.h"
#include "src/Tensor/TensorDeviceGpu.h"
#ifndef gpu_assert
#define gpu_assert(x)
#endif
#include "src/Tensor/TensorDeviceSycl.h"
#include "src/Tensor/TensorIndexList.h"
#include "src/Tensor/TensorDimensionList.h"
......@@ -108,18 +117,19 @@ typedef unsigned __int64 uint64_t;
#include "src/Tensor/TensorGlobalFunctions.h"
#include "src/Tensor/TensorBase.h"
#include "src/Tensor/TensorBlock.h"
#include "src/Tensor/TensorEvaluator.h"
#include "src/Tensor/TensorExpr.h"
#include "src/Tensor/TensorReduction.h"
#include "src/Tensor/TensorReductionCuda.h"
#include "src/Tensor/TensorReductionGpu.h"
#include "src/Tensor/TensorArgMax.h"
#include "src/Tensor/TensorConcatenation.h"
#include "src/Tensor/TensorContractionMapper.h"
#include "src/Tensor/TensorContractionBlocking.h"
#include "src/Tensor/TensorContraction.h"
#include "src/Tensor/TensorContractionThreadPool.h"
#include "src/Tensor/TensorContractionCuda.h"
#include "src/Tensor/TensorContractionGpu.h"
#include "src/Tensor/TensorConversion.h"
#include "src/Tensor/TensorConvolution.h"
#include "src/Tensor/TensorFFT.h"
......@@ -141,6 +151,7 @@ typedef unsigned __int64 uint64_t;
#include "src/Tensor/TensorGenerator.h"
#include "src/Tensor/TensorAssign.h"
#include "src/Tensor/TensorScan.h"
#include "src/Tensor/TensorTrace.h"
#include "src/Tensor/TensorSycl.h"
#include "src/Tensor/TensorExecutor.h"
......@@ -154,6 +165,6 @@ typedef unsigned __int64 uint64_t;
#include "src/Tensor/TensorIO.h"
#include <Eigen/src/Core/util/ReenableStupidWarnings.h>
#include "../../../Eigen/src/Core/util/ReenableStupidWarnings.h"
//#endif // EIGEN_CXX11_TENSOR_MODULE
tpls/eigen/unsupported/Eigen/CXX11/TensorSymmetry
View file @ 2e9e1bab
......@@ -10,9 +10,9 @@
#ifndef EIGEN_CXX11_TENSORSYMMETRY_MODULE
#define EIGEN_CXX11_TENSORSYMMETRY_MODULE
#include <unsupported/Eigen/CXX11/Tensor>
#include "Tensor"
#include <Eigen/src/Core/util/DisableStupidWarnings.h>
#include "../../../Eigen/src/Core/util/DisableStupidWarnings.h"
#include "src/util/CXX11Meta.h"
......@@ -33,7 +33,7 @@
#include "src/TensorSymmetry/StaticSymmetry.h"
#include "src/TensorSymmetry/DynamicSymmetry.h"
#include <Eigen/src/Core/util/ReenableStupidWarnings.h>
#include "../../../Eigen/src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_CXX11_TENSORSYMMETRY_MODULE
......
tpls/eigen/unsupported/Eigen/CXX11/ThreadPool
View file @ 2e9e1bab
......@@ -12,7 +12,7 @@
#include "../../../Eigen/Core"
#include <Eigen/src/Core/util/DisableStupidWarnings.h>
#include "../../../Eigen/src/Core/util/DisableStupidWarnings.h"
/** \defgroup CXX11_ThreadPool_Module C++11 ThreadPool Module
*
......@@ -44,35 +44,31 @@
#include <thread>
#include <functional>
#include <memory>
#include "src/util/CXX11Meta.h"
#include "src/util/MaxSizeVector.h"
#include "src/ThreadPool/ThreadLocal.h"
#ifndef EIGEN_THREAD_LOCAL
// There are non-parenthesized calls to "max" in the <unordered_map> header,
// which trigger a check in test/main.h causing compilation to fail.
// We work around the check here by removing the check for max in
// the case where we have to emulate thread_local.
#ifdef max
#undef max
#endif
#include <unordered_map>
#endif
#include "src/ThreadPool/ThreadYield.h"
#include "src/ThreadPool/ThreadCancel.h"
#include "src/ThreadPool/EventCount.h"
#include "src/ThreadPool/RunQueue.h"
#include "src/ThreadPool/ThreadPoolInterface.h"
#include "src/ThreadPool/ThreadEnvironment.h"
#include "src/ThreadPool/SimpleThreadPool.h"
#include "src/ThreadPool/Barrier.h"
#include "src/ThreadPool/NonBlockingThreadPool.h"
// Use the more efficient NonBlockingThreadPool by default.
namespace Eigen {
#ifndef EIGEN_USE_SIMPLE_THREAD_POOL
template <typename Env> using ThreadPoolTempl = NonBlockingThreadPoolTempl<Env>;
typedef NonBlockingThreadPool ThreadPool;
#else
template <typename Env> using ThreadPoolTempl = SimpleThreadPoolTempl<Env>;
typedef SimpleThreadPool ThreadPool;
#endif
} // namespace Eigen
#endif
#include <Eigen/src/Core/util/ReenableStupidWarnings.h>
#include "../../../Eigen/src/Core/util/ReenableStupidWarnings.h"
#endif // EIGEN_CXX11_THREADPOOL_MODULE
tpls/eigen/unsupported/Eigen/CXX11/src/Tensor/Tensor.h
View file @ 2e9e1bab
......@@ -23,12 +23,12 @@ namespace Eigen {
* The %Tensor class encompasses only dynamic-size objects so far.
*
* The first two template parameters are required:
* \tparam Scalar_ \anchor tensor_tparam_scalar Numeric type, e.g. float, double, int or std::complex<float>.
* \tparam Scalar_ Numeric type, e.g. float, double, int or `std::complex<float>`.
* User defined scalar types are supported as well (see \ref user_defined_scalars "here").
* \tparam NumIndices_ Number of indices (i.e. rank of the tensor)
*
* The remaining template parameters are optional -- in most cases you don't have to worry about them.
* \tparam Options_ \anchor tensor_tparam_options A combination of either \b #RowMajor or \b #ColMajor, and of either
* \tparam Options_ A combination of either \b #RowMajor or \b #ColMajor, and of either
* \b #AutoAlign or \b #DontAlign.
* The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter controls alignment, which is required
* for vectorization. It defaults to aligning tensors. Note that tensors currently do not support any operations that profit from vectorization.
......@@ -42,13 +42,13 @@ namespace Eigen {
* \endcode
*
* This class can be extended with the help of the plugin mechanism described on the page
* \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_TENSOR_PLUGIN.
* \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_TENSOR_PLUGIN.
*
* <i><b>Some notes:</b></i>
*
* <dl>
* <dt><b>Relation to other parts of Eigen:</b></dt>
* <dd>The midterm developement goal for this class is to have a similar hierarchy as Eigen uses for matrices, so that
* <dd>The midterm development goal for this class is to have a similar hierarchy as Eigen uses for matrices, so that
* taking blocks or using tensors in expressions is easily possible, including an interface with the vector/matrix code
* by providing .asMatrix() and .asVector() (or similar) methods for rank 2 and 1 tensors. However, currently, the %Tensor
* class does not provide any of these features and is only available as a stand-alone class that just allows for
......@@ -112,7 +112,7 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes>
EIGEN_DEVICE_FUNC inline const Scalar& coeff(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const
{
// The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
......@@ -398,6 +398,21 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
}
#if EIGEN_HAS_RVALUE_REFERENCES
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Tensor(Self&& other)
: Tensor()
{
m_storage.swap(other.m_storage);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Tensor& operator=(Self&& other)
{
m_storage.swap(other.m_storage);
return *this;
}
#endif
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Tensor& operator=(const Tensor& other)
{
......@@ -462,6 +477,18 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
// Nothing to do: rank 0 tensors have fixed size
}
#ifdef EIGEN_HAS_INDEX_LIST
template <typename FirstType, typename... OtherTypes>
EIGEN_DEVICE_FUNC
void resize(const Eigen::IndexList<FirstType, OtherTypes...>& dimensions) {
array<Index, NumIndices> dims;
for (int i = 0; i < NumIndices; ++i) {
dims[i] = static_cast<Index>(dimensions[i]);
}
resize(dims);
}
#endif
/** Custom Dimension */
#ifdef EIGEN_HAS_SFINAE
template<typename CustomDimension,
......
tpls/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorArgMax.h
View file @ 2e9e1bab
......@@ -87,6 +87,7 @@ struct TensorEvaluator<const TensorIndexTupleOp<ArgType>, Device>
IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/ false,
PacketAccess = /*TensorEvaluator<ArgType, Device>::PacketAccess*/ false,
BlockAccess = false,
PreferBlockAccess = false,
Layout = TensorEvaluator<ArgType, Device>::Layout,
CoordAccess = false, // to be implemented
RawAccess = false
......@@ -119,6 +120,12 @@ struct TensorEvaluator<const TensorIndexTupleOp<ArgType>, Device>
EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
#ifdef EIGEN_USE_SYCL
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorEvaluator<ArgType, Device>& impl() const {
return m_impl;
}
#endif
protected:
TensorEvaluator<ArgType, Device> m_impl;
};
......@@ -172,7 +179,7 @@ class TensorTupleReducerOp : public TensorBase<TensorTupleReducerOp<ReduceOp, Di
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorTupleReducerOp(const XprType& expr,
const ReduceOp& reduce_op,
const int return_dim,
const Index return_dim,
const Dims& reduce_dims)
: m_xpr(expr), m_reduce_op(reduce_op), m_return_dim(return_dim), m_reduce_dims(reduce_dims) {}
......@@ -187,12 +194,12 @@ class TensorTupleReducerOp : public TensorBase<TensorTupleReducerOp<ReduceOp, Di
const Dims& reduce_dims() const { return m_reduce_dims; }
EIGEN_DEVICE_FUNC
int return_dim() const { return m_return_dim; }
Index return_dim() const { return m_return_dim; }
protected:
typename XprType::Nested m_xpr;
const ReduceOp m_reduce_op;
const int m_return_dim;
const Index m_return_dim;
const Dims m_reduce_dims;
};
......@@ -214,6 +221,7 @@ struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Devi
IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/ false,
PacketAccess = /*TensorEvaluator<ArgType, Device>::PacketAccess*/ false,
BlockAccess = false,
PreferBlockAccess = false,
Layout = TensorEvaluator<const TensorReductionOp<ReduceOp, Dims, const TensorIndexTupleOp<ArgType> >, Device>::Layout,
CoordAccess = false, // to be implemented
RawAccess = false
......@@ -222,8 +230,11 @@ struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Devi
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
: m_orig_impl(op.expression(), device),
m_impl(op.expression().index_tuples().reduce(op.reduce_dims(), op.reduce_op()), device),
m_return_dim(op.return_dim()) {
m_return_dim(op.return_dim())
#ifdef EIGEN_USE_SYCL
,m_device(device)
#endif
{
gen_strides(m_orig_impl.dimensions(), m_strides);
if (Layout == static_cast<int>(ColMajor)) {
const Index total_size = internal::array_prod(m_orig_impl.dimensions());
......@@ -232,7 +243,7 @@ struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Devi
const Index total_size = internal::array_prod(m_orig_impl.dimensions());
m_stride_mod = (m_return_dim > 0) ? m_strides[m_return_dim - 1] : total_size;
}
m_stride_div = m_strides[m_return_dim];
m_stride_div = (m_return_dim >= 0) ? m_strides[m_return_dim] : 1;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const {
......@@ -252,7 +263,16 @@ struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Devi
return (m_return_dim < 0) ? v.first : (v.first % m_stride_mod) / m_stride_div;
}
#ifndef EIGEN_USE_SYCL
EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
#else // following functions are required by sycl
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TupleType* data() const { return m_impl.data(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index return_dim() const {return m_return_dim;}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const StrideDims& strides() const {return m_strides;}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Index& stride_mod() const {return m_stride_mod;}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Index& stride_div() const {return m_stride_div;}
const Device& device() const{return m_device;}
#endif
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
costPerCoeff(bool vectorized) const {
......@@ -288,10 +308,13 @@ struct TensorEvaluator<const TensorTupleReducerOp<ReduceOp, Dims, ArgType>, Devi
protected:
TensorEvaluator<const TensorIndexTupleOp<ArgType>, Device> m_orig_impl;
TensorEvaluator<const TensorReductionOp<ReduceOp, Dims, const TensorIndexTupleOp<ArgType> >, Device> m_impl;
const int m_return_dim;
const Index m_return_dim;
StrideDims m_strides;
Index m_stride_mod;
Index m_stride_div;
#ifdef EIGEN_USE_SYCL
const Device& m_device;
#endif
};
} // end namespace Eigen
......
tpls/eigen/unsupported/Eigen/CXX11/src/Tensor/TensorArgMaxSycl.h 0 → 100644
View file @ 2e9e1bab
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Mehdi Goli Codeplay Software Ltd.
// Ralph Potter Codeplay Software Ltd.
// Luke Iwanski Codeplay Software Ltd.
// Contact: <eigen@codeplay.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
/*****************************************************************
* TensorArgMaxSycl.h
* \brief:
* TensorArgMaxSycl
*
*****************************************************************/
#ifndef UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSOR_ARGMAX_SYCL_HPP
#define UNSUPPORTED_EIGEN_CXX11_SRC_TENSOR_TENSOR_ARGMAX_SYCL_HPP
namespace Eigen {
namespace internal {
template<typename Dims, typename XprType>
struct eval<TensorTupleReducerDeviceOp<Dims, XprType>, Eigen::Dense>
{
typedef const TensorTupleReducerDeviceOp<Dims, XprType>& type;
};
template<typename Dims, typename XprType>
struct nested<TensorTupleReducerDeviceOp<Dims, XprType>, 1,
typename eval<TensorTupleReducerDeviceOp<Dims, XprType> >::type>
{
typedef TensorTupleReducerDeviceOp<Dims, XprType> type;
};
template<typename StrideDims, typename XprType>
struct traits<TensorTupleReducerDeviceOp<StrideDims, XprType> > : public traits<XprType>
{
typedef traits<XprType> XprTraits;
typedef typename XprTraits::StorageKind StorageKind;
typedef typename XprTraits::Index Index;
typedef Index Scalar;
typedef typename XprType::Nested Nested;
typedef typename remove_reference<Nested>::type _Nested;
static const int NumDimensions = XprTraits::NumDimensions;
static const int Layout = XprTraits::Layout;
};
}// end namespace internal
template<typename StrideDims, typename XprType>
class TensorTupleReducerDeviceOp : public TensorBase<TensorTupleReducerDeviceOp<StrideDims, XprType>, ReadOnlyAccessors>
{
public:
typedef typename Eigen::internal::traits<TensorTupleReducerDeviceOp>::Scalar Scalar;
typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
typedef typename Eigen::internal::nested<TensorTupleReducerDeviceOp>::type Nested;
typedef typename Eigen::internal::traits<TensorTupleReducerDeviceOp>::StorageKind StorageKind;
typedef typename Eigen::internal::traits<TensorTupleReducerDeviceOp>::Index Index;
typedef typename XprType::CoeffReturnType TupleType;
typedef Index CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorTupleReducerDeviceOp(XprType expr,
const Index return_dim,
const StrideDims strides,
const Index stride_mod, const Index stride_div)
:m_xpr(expr), m_return_dim(return_dim), m_strides(strides), m_stride_mod(stride_mod), m_stride_div(stride_div) {}
EIGEN_DEVICE_FUNC
const typename internal::remove_all<typename XprType::Nested>::type&
expression() const { return m_xpr; }
EIGEN_DEVICE_FUNC
Index return_dim() const { return m_return_dim; }
EIGEN_DEVICE_FUNC
const StrideDims& strides() const { return m_strides; }
EIGEN_DEVICE_FUNC
const Index& stride_mod() const { return m_stride_mod; }
EIGEN_DEVICE_FUNC
const Index& stride_div() const { return m_stride_div; }
protected:
typename Eigen::internal::remove_all<typename
XprType::Nested
>::type m_xpr;
const Index m_return_dim;
const StrideDims m_strides;
const Index m_stride_mod;
const Index m_stride_div;
};
// Eval as rvalue
template<typename StrideDims, typename ArgType>
struct TensorEvaluator<const TensorTupleReducerDeviceOp<StrideDims, ArgType>, SyclKernelDevice>
{
typedef TensorTupleReducerDeviceOp<StrideDims, ArgType> XprType;
typedef typename XprType::Index Index;
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename XprType::TupleType TupleType;
typedef typename TensorEvaluator<ArgType, SyclKernelDevice>::Dimensions Dimensions;
enum {
IsAligned = false,
PacketAccess = false,
BlockAccess = false,
PreferBlockAccess = false,
Layout = TensorEvaluator<ArgType, SyclKernelDevice>::Layout,
CoordAccess = false,
RawAccess = false
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const SyclKernelDevice& device)
: m_impl(op.expression(), device), m_return_dim(op.return_dim()), m_strides(op.strides()), m_stride_mod(op.stride_mod()),
m_stride_div(op.stride_div()){}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const {
return m_impl.dimensions();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
m_impl.evalSubExprsIfNeeded(NULL);
return true;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
m_impl.cleanup();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
const TupleType v = m_impl.coeff(index);
return (m_return_dim < 0) ? v.first : (v.first % m_stride_mod) / m_stride_div;
}
typedef typename MakeGlobalPointer<typename TensorEvaluator<ArgType , SyclKernelDevice>::CoeffReturnType >::Type ptr_Dev_type;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ptr_Dev_type data() const { return const_cast<ptr_Dev_type>(m_impl.data()); }
protected:
TensorEvaluator<ArgType , SyclKernelDevice> m_impl;
const Index m_return_dim;
const StrideDims m_strides;