diff options
22 files changed, 190 insertions, 65 deletions
diff --git a/Eigen/Core b/Eigen/Core index 864bde551..080511fc9 100644 --- a/Eigen/Core +++ b/Eigen/Core @@ -200,6 +200,12 @@ using std::ptrdiff_t; #include "src/Core/arch/GPU/MathFunctions.h" #endif +#if defined EIGEN_VECTORIZE_SYCL + #include "src/Core/arch/SYCL/InteropHeaders.h" + #include "src/Core/arch/SYCL/PacketMath.h" + #include "src/Core/arch/SYCL/MathFunctions.h" + #include "src/Core/arch/SYCL/TypeCasting.h" +#endif #include "src/Core/arch/Default/Settings.h" #include "src/Core/functors/TernaryFunctors.h" diff --git a/Eigen/src/Core/arch/GPU/Half.h b/Eigen/src/Core/arch/GPU/Half.h index ab9d27591..aca56fa72 100644 --- a/Eigen/src/Core/arch/GPU/Half.h +++ b/Eigen/src/Core/arch/GPU/Half.h @@ -83,7 +83,11 @@ struct __half_raw { #if defined(EIGEN_CUDACC_VER) && EIGEN_CUDACC_VER < 90000 // In CUDA < 9.0, __half is the equivalent of CUDA 9's __half_raw typedef __half __half_raw; - #endif + #endif // defined(EIGEN_HAS_CUDA_FP16) + +#elif defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__) +typedef cl::sycl::half __half_raw; + #endif EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC __half_raw raw_uint16_to_half(unsigned short x); @@ -200,6 +204,7 @@ struct half : public half_impl::half_base { x = other.x; return *this; } + }; } // end namespace Eigen diff --git a/Eigen/src/Core/util/Macros.h b/Eigen/src/Core/util/Macros.h index f59b93608..bcdede61e 100644 --- a/Eigen/src/Core/util/Macros.h +++ b/Eigen/src/Core/util/Macros.h @@ -571,20 +571,19 @@ // Does the compiler fully support const expressions? (as in c++14) #ifndef EIGEN_HAS_CONSTEXPR - #if defined(EIGEN_CUDACC) // Const expressions are supported provided that c++11 is enabled and we're using either clang or nvcc 7.5 or above - #if EIGEN_MAX_CPP_VER>=14 && (__cplusplus > 199711L && (EIGEN_COMP_CLANG || EIGEN_CUDACC_VER >= 70500)) - #define EIGEN_HAS_CONSTEXPR 1 - #endif + #if EIGEN_MAX_CPP_VER>=14 && (__cplusplus > 199711L && (EIGEN_COMP_CLANG || EIGEN_CUDACC_VER >= 70500)) + #define EIGEN_HAS_CONSTEXPR 1 + #endif #elif EIGEN_MAX_CPP_VER>=14 && (__has_feature(cxx_relaxed_constexpr) || (defined(__cplusplus) && __cplusplus >= 201402L) || \ (EIGEN_GNUC_AT_LEAST(4,8) && (__cplusplus > 199711L)) || \ (EIGEN_COMP_CLANG >= 306 && (__cplusplus > 199711L))) - #define EIGEN_HAS_CONSTEXPR 1 + #define EIGEN_HAS_CONSTEXPR 1 #endif #ifndef EIGEN_HAS_CONSTEXPR - #define EIGEN_HAS_CONSTEXPR 0 + #define EIGEN_HAS_CONSTEXPR 0 #endif #endif // EIGEN_HAS_CONSTEXPR @@ -643,9 +642,12 @@ #ifdef __CUDACC_RELAXED_CONSTEXPR__ #define EIGEN_CONSTEXPR_ARE_DEVICE_FUNC #endif - #elif defined(__clang__) && defined(__CUDA__) - // clang++ always considers constexpr functions as implicitly __host__ __device__ - #define EIGEN_CONSTEXPR_ARE_DEVICE_FUNC + // See bug 1580: clang/CUDA fails to make the following calls + // to constexpr bool std::equal_to::operator() even when + // EIGEN_CONSTEXPR_ARE_DEVICE_FUNC is defined in c++14 only. + // #elif defined(__clang__) && defined(__CUDA__) && EIGEN_HAS_CONSTEXPR == 1 + // // clang++ always considers constexpr functions as implicitly __host__ __device__ + // #define EIGEN_CONSTEXPR_ARE_DEVICE_FUNC #endif #endif @@ -1076,11 +1078,13 @@ namespace Eigen { # endif #endif -#ifdef EIGEN_HAS_VARIADIC_TEMPLATES +#if EIGEN_HAS_VARIADIC_TEMPLATES // The all function is used to enable a variadic version of eigen_assert which can take a parameter pack as its input. namespace Eigen { namespace internal { -bool all(){ return true; } + +inline bool all(){ return true; } + template<typename T, typename ...Ts> bool all(T t, Ts ... ts){ return t && all(ts...); } @@ -1088,5 +1092,15 @@ bool all(T t, Ts ... ts){ return t && all(ts...); } } #endif +// Wrapping #pragma unroll in a macro since it is required for SYCL +#if defined(__SYCL_DEVICE_ONLY__) + #if defined(_MSC_VER) + #define EIGEN_UNROLL_LOOP __pragma(unroll) + #else + #define EIGEN_UNROLL_LOOP _Pragma("unroll") + #endif +#else + #define EIGEN_UNROLL_LOOP +#endif #endif // EIGEN_MACROS_H diff --git a/Eigen/src/Core/util/Meta.h b/Eigen/src/Core/util/Meta.h index 658cfa9eb..f27b8e85d 100755 --- a/Eigen/src/Core/util/Meta.h +++ b/Eigen/src/Core/util/Meta.h @@ -569,7 +569,7 @@ template<typename T, typename U> struct scalar_product_traits } // end namespace internal namespace numext { - + #if defined(EIGEN_GPU_COMPILE_PHASE) template<typename T> EIGEN_DEVICE_FUNC void swap(T &a, T &b) { T tmp = b; b = a; a = tmp; } #else diff --git a/test/dynalloc.cpp b/test/dynalloc.cpp index ceecd76e3..1c74866ba 100644 --- a/test/dynalloc.cpp +++ b/test/dynalloc.cpp @@ -15,6 +15,7 @@ #define ALIGNMENT 1 #endif +typedef Matrix<float,16,1> Vector16f; typedef Matrix<float,8,1> Vector8f; void check_handmade_aligned_malloc() @@ -70,7 +71,7 @@ struct MyStruct { EIGEN_MAKE_ALIGNED_OPERATOR_NEW char dummychar; - Vector8f avec; + Vector16f avec; }; class MyClassA @@ -78,7 +79,7 @@ class MyClassA public: EIGEN_MAKE_ALIGNED_OPERATOR_NEW char dummychar; - Vector8f avec; + Vector16f avec; }; template<typename T> void check_dynaligned() @@ -145,6 +146,7 @@ EIGEN_DECLARE_TEST(dynalloc) CALL_SUBTEST(check_dynaligned<Vector4d>() ); CALL_SUBTEST(check_dynaligned<Vector4i>() ); CALL_SUBTEST(check_dynaligned<Vector8f>() ); + CALL_SUBTEST(check_dynaligned<Vector16f>() ); } { diff --git a/test/main.h b/test/main.h index 5d64bc736..de8a4865f 100644 --- a/test/main.h +++ b/test/main.h @@ -193,7 +193,7 @@ namespace Eigen #define EIGEN_DEFAULT_IO_FORMAT IOFormat(4, 0, " ", "\n", "", "", "", "") -#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__) +#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__) && !defined(__SYCL_DEVICE_ONLY__) #define EIGEN_EXCEPTIONS #endif @@ -272,7 +272,7 @@ namespace Eigen } #endif //EIGEN_EXCEPTIONS - #elif !defined(__CUDACC__) && !defined(__HIPCC__)// EIGEN_DEBUG_ASSERTS + #elif !defined(__CUDACC__) && !defined(__HIPCC__) && !defined(__SYCL_DEVICE_ONLY__) // EIGEN_DEBUG_ASSERTS // see bug 89. The copy_bool here is working around a bug in gcc <= 4.3 #define eigen_assert(a) \ if( (!Eigen::internal::copy_bool(a)) && (!no_more_assert) )\ @@ -329,7 +329,7 @@ namespace Eigen std::cout << "Can't VERIFY_RAISES_STATIC_ASSERT( " #a " ) with exceptions disabled\n"; #endif - #if !defined(__CUDACC__) && !defined(__HIPCC__) + #if !defined(__CUDACC__) && !defined(__HIPCC__) && !defined(__SYCL_DEVICE_ONLY__) #define EIGEN_USE_CUSTOM_ASSERT #endif @@ -845,4 +845,4 @@ int main(int argc, char *argv[]) #ifdef _MSC_VER // 4503 - decorated name length exceeded, name was truncated #pragma warning( disable : 4503) -#endif +#endif
\ No newline at end of file diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h b/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h index 97f90f638..ab3731952 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h @@ -538,8 +538,8 @@ class TensorBase<Derived, ReadOnlyAccessors> // Fourier transforms template <int FFTDataType, int FFTDirection, typename FFT> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorFFTOp<const FFT, const Derived, FFTDataType, FFTDirection> - fft(const FFT& fft) const { - return TensorFFTOp<const FFT, const Derived, FFTDataType, FFTDirection>(derived(), fft); + fft(const FFT& dims) const { + return TensorFFTOp<const FFT, const Derived, FFTDataType, FFTDirection>(derived(), dims); } // Scan. @@ -723,8 +723,8 @@ class TensorBase<Derived, ReadOnlyAccessors> template <typename Broadcast> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorBroadcastingOp<const Broadcast, const Derived> - broadcast(const Broadcast& broadcast) const { - return TensorBroadcastingOp<const Broadcast, const Derived>(derived(), broadcast); + broadcast(const Broadcast& bcast) const { + return TensorBroadcastingOp<const Broadcast, const Derived>(derived(), bcast); } template <typename Axis, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE @@ -832,8 +832,8 @@ class TensorBase<Derived, ReadOnlyAccessors> } template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorShufflingOp<const Shuffle, const Derived> - shuffle(const Shuffle& shuffle) const { - return TensorShufflingOp<const Shuffle, const Derived>(derived(), shuffle); + shuffle(const Shuffle& shfl) const { + return TensorShufflingOp<const Shuffle, const Derived>(derived(), shfl); } template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorStridingOp<const Strides, const Derived> @@ -1030,13 +1030,13 @@ class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> { template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorShufflingOp<const Shuffle, const Derived> - shuffle(const Shuffle& shuffle) const { - return TensorShufflingOp<const Shuffle, const Derived>(derived(), shuffle); + shuffle(const Shuffle& shfl) const { + return TensorShufflingOp<const Shuffle, const Derived>(derived(), shfl); } template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorShufflingOp<const Shuffle, Derived> - shuffle(const Shuffle& shuffle) { - return TensorShufflingOp<const Shuffle, Derived>(derived(), shuffle); + shuffle(const Shuffle& shfl) { + return TensorShufflingOp<const Shuffle, Derived>(derived(), shfl); } template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE @@ -1052,8 +1052,8 @@ class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> { // Select the device on which to evaluate the expression. template <typename DeviceType> - TensorDevice<Derived, DeviceType> device(const DeviceType& device) { - return TensorDevice<Derived, DeviceType>(device, derived()); + TensorDevice<Derived, DeviceType> device(const DeviceType& dev) { + return TensorDevice<Derived, DeviceType>(dev, derived()); } protected: diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h b/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h index 1db8d6124..877603421 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorBlock.h @@ -89,7 +89,7 @@ EIGEN_STRONG_INLINE void MergeResourceRequirements( // policy if block shapes/sizes conflict). *block_shape = resources[0].block_shape; *block_total_size = resources[0].block_total_size; - for (int i = 1; i < resources.size(); ++i) { + for (std::vector<TensorOpResourceRequirements>::size_type i = 1; i < resources.size(); ++i) { if (resources[i].block_shape == TensorBlockShapeType::kSkewedInnerDims && *block_shape != TensorBlockShapeType::kSkewedInnerDims) { *block_shape = TensorBlockShapeType::kSkewedInnerDims; diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h b/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h index e1649fb47..e604456e8 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h @@ -274,8 +274,8 @@ struct TensorContractionEvaluatorBase op.lhsExpression(), op.rhsExpression()), device), m_rightImpl(choose(Cond<static_cast<int>(Layout) == static_cast<int>(ColMajor)>(), op.rhsExpression(), op.lhsExpression()), device), - m_output_kernel(op.outputKernel()), m_device(device), + m_output_kernel(op.outputKernel()), m_result(NULL) { EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) == static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout)), diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h b/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h index 0d3ca966c..a07e32db0 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h @@ -527,8 +527,8 @@ struct TensorEvaluator<const TensorConvolutionOp<Indices, InputArgType, KernelAr Scalar* local = (Scalar*)m_device.allocate(kernel_sz); typedef TensorEvalToOp<const KernelArgType> EvalTo; EvalTo evalToTmp(local, m_kernelArg); - const bool PacketAccess = internal::IsVectorizable<Device, KernelArgType>::value; - internal::TensorExecutor<const EvalTo, Device, PacketAccess>::run(evalToTmp, m_device); + const bool Vectorize = internal::IsVectorizable<Device, KernelArgType>::value; + internal::TensorExecutor<const EvalTo, Device, Vectorize>::run(evalToTmp, m_device); m_kernel = local; m_local_kernel = true; @@ -786,7 +786,7 @@ struct TensorEvaluator<const TensorConvolutionOp<Indices, InputArgType, KernelAr }; EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const GpuDevice& device) - : m_inputImpl(op.inputExpression(), device), m_kernelArg(op.kernelExpression()), m_kernelImpl(op.kernelExpression(), device), m_indices(op.indices()), m_buf(NULL), m_kernel(NULL), m_local_kernel(false), m_device(device) + : m_inputImpl(op.inputExpression(), device), m_kernelImpl(op.kernelExpression(), device), m_kernelArg(op.kernelExpression()), m_indices(op.indices()), m_buf(NULL), m_kernel(NULL), m_local_kernel(false), m_device(device) { EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<InputArgType, GpuDevice>::Layout) == static_cast<int>(TensorEvaluator<KernelArgType, GpuDevice>::Layout)), YOU_MADE_A_PROGRAMMING_MISTAKE); diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h b/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h index 5a16ebe50..cc134228a 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h @@ -91,18 +91,31 @@ static EIGEN_STRONG_INLINE void wait_until_ready(SyncType* n) { } } +// An abstract interface to a device specific memory allocator. +class Allocator { + public: + virtual ~Allocator() {} + EIGEN_DEVICE_FUNC virtual void* allocate(size_t num_bytes) const = 0; + EIGEN_DEVICE_FUNC virtual void deallocate(void* buffer) const = 0; +}; // Build a thread pool device on top the an existing pool of threads. struct ThreadPoolDevice { // The ownership of the thread pool remains with the caller. - ThreadPoolDevice(ThreadPoolInterface* pool, int num_cores) : pool_(pool), num_threads_(num_cores) { } + ThreadPoolDevice(ThreadPoolInterface* pool, int num_cores, Allocator* allocator = nullptr) + : pool_(pool), num_threads_(num_cores), allocator_(allocator) { } EIGEN_STRONG_INLINE void* allocate(size_t num_bytes) const { - return internal::aligned_malloc(num_bytes); + return allocator_ ? allocator_->allocate(num_bytes) + : internal::aligned_malloc(num_bytes); } EIGEN_STRONG_INLINE void deallocate(void* buffer) const { - internal::aligned_free(buffer); + if (allocator_) { + allocator_->deallocate(buffer); + } else { + internal::aligned_free(buffer); + } } EIGEN_STRONG_INLINE void* allocate_temp(size_t num_bytes) const { @@ -275,9 +288,13 @@ struct ThreadPoolDevice { // Thread pool accessor. ThreadPoolInterface* getPool() const { return pool_; } + // Allocator accessor. + Allocator* allocator() const { return allocator_; } + private: ThreadPoolInterface* pool_; int num_threads_; + Allocator* allocator_; }; diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h b/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h index 8f7a81575..028902fea 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h @@ -126,7 +126,7 @@ struct TensorEvaluator } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void getResourceRequirements( - std::vector<internal::TensorOpResourceRequirements>* resources) const {} + std::vector<internal::TensorOpResourceRequirements>*) const {} EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void block(TensorBlock* block) const { assert(m_data != NULL); @@ -255,7 +255,7 @@ struct TensorEvaluator<const Derived, Device> } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void getResourceRequirements( - std::vector<internal::TensorOpResourceRequirements>* resources) const {} + std::vector<internal::TensorOpResourceRequirements>*) const {} EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void block(TensorBlock* block) const { assert(m_data != NULL); diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h b/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h index a456f308b..2778bf5ec 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h @@ -124,8 +124,8 @@ struct TensorEvaluator<const TensorForcedEvalOp<ArgType>, Device> } typedef TensorEvalToOp< const typename internal::remove_const<ArgType>::type > EvalTo; EvalTo evalToTmp(m_buffer, m_op); - const bool PacketAccess = internal::IsVectorizable<Device, const ArgType>::value; - internal::TensorExecutor<const EvalTo, typename internal::remove_const<Device>::type, PacketAccess>::run(evalToTmp, m_device); + const bool Vectorize = internal::IsVectorizable<Device, const ArgType>::value; + internal::TensorExecutor<const EvalTo, typename internal::remove_const<Device>::type, Vectorize>::run(evalToTmp, m_device); return true; } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() { diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h index 8ed1796df..0dd524a30 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h @@ -21,6 +21,7 @@ namespace Eigen { template<typename T> struct MakePointer { typedef T* Type; typedef T& RefType; + typedef T ScalarType; }; namespace internal{ @@ -97,7 +98,7 @@ template<typename XprType> class TensorForcedEvalOp; template<typename ExpressionType, typename DeviceType> class TensorDevice; template<typename Derived, typename Device> struct TensorEvaluator; -class NoOpOutputKernel; +struct NoOpOutputKernel; struct DefaultDevice; struct ThreadPoolDevice; diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h b/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h index fbe69aabc..98f125408 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h @@ -61,8 +61,8 @@ class TensorShufflingOp : public TensorBase<TensorShufflingOp<Shuffle, XprType> typedef typename Eigen::internal::traits<TensorShufflingOp>::StorageKind StorageKind; typedef typename Eigen::internal::traits<TensorShufflingOp>::Index Index; - EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorShufflingOp(const XprType& expr, const Shuffle& shuffle) - : m_xpr(expr), m_shuffle(shuffle) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorShufflingOp(const XprType& expr, const Shuffle& shfl) + : m_xpr(expr), m_shuffle(shfl) {} EIGEN_DEVICE_FUNC const Shuffle& shufflePermutation() const { return m_shuffle; } diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorTrace.h b/unsupported/Eigen/CXX11/src/Tensor/TensorTrace.h index c8b2fad1e..ea53bb04b 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorTrace.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorTrace.h @@ -273,11 +273,11 @@ struct TensorEvaluator<const TensorTraceOp<Dims, ArgType>, Device> Dimensions m_dimensions; TensorEvaluator<ArgType, Device> m_impl; + // Initialize the size of the trace dimension + Index m_traceDim; const Device& m_device; array<bool, NumInputDims> m_reduced; array<Index, NumReducedDims> m_reducedDims; - // Initialize the size of the trace dimension - Index m_traceDim; array<Index, NumOutputDims> m_outputStrides; array<Index, NumReducedDims> m_reducedStrides; array<Index, NumOutputDims> m_preservedStrides; diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h b/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h index 006b37921..0a394c88d 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h @@ -59,6 +59,7 @@ struct traits<Tensor<Scalar_, NumIndices_, Options_, IndexType_> > template <typename T> struct MakePointer { typedef T* Type; typedef T& RefType; + typedef T ScalarType; }; typedef typename MakePointer<Scalar>::Type PointerType; @@ -80,6 +81,7 @@ struct traits<TensorFixedSize<Scalar_, Dimensions, Options_, IndexType_> > template <typename T> struct MakePointer { typedef T* Type; typedef T& RefType; + typedef T ScalarType; }; typedef typename MakePointer<Scalar>::Type PointerType; @@ -105,6 +107,8 @@ struct traits<TensorMap<PlainObjectType, Options_, MakePointer_> > typedef MakePointer_<T> MakePointerT; typedef typename MakePointerT::Type Type; typedef typename MakePointerT::RefType RefType; + typedef typename MakePointerT::ScalarType ScalarType; + }; typedef typename MakePointer<Scalar>::Type PointerType; diff --git a/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h b/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h index 279fe5cd3..13d959df4 100755 --- a/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h +++ b/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h @@ -684,10 +684,15 @@ template<typename DerType> struct NumTraits<AutoDiffScalar<DerType> > } namespace std { + template <typename T> class numeric_limits<Eigen::AutoDiffScalar<T> > : public numeric_limits<typename T::Scalar> {}; +template <typename T> +class numeric_limits<Eigen::AutoDiffScalar<T&> > + : public numeric_limits<typename T::Scalar> {}; + } // namespace std #endif // EIGEN_AUTODIFF_SCALAR_H diff --git a/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h b/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h index dbcc9d8ac..5784cbc86 100644 --- a/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h +++ b/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsImpl.h @@ -193,6 +193,8 @@ struct lgamma_impl<float> { #if !defined(EIGEN_GPU_COMPILE_PHASE) && (defined(_BSD_SOURCE) || defined(_SVID_SOURCE)) && !defined(__APPLE__) int dummy; return ::lgammaf_r(x, &dummy); +#elif defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__) + return cl::sycl::lgamma(x); #else return ::lgammaf(x); #endif @@ -206,6 +208,8 @@ struct lgamma_impl<double> { #if !defined(EIGEN_GPU_COMPILE_PHASE) && (defined(_BSD_SOURCE) || defined(_SVID_SOURCE)) && !defined(__APPLE__) int dummy; return ::lgamma_r(x, &dummy); +#elif defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__) + return cl::sycl::lgamma(x); #else return ::lgamma(x); #endif @@ -423,13 +427,25 @@ struct erf_retval { template <> struct erf_impl<float> { EIGEN_DEVICE_FUNC - static EIGEN_STRONG_INLINE float run(float x) { return ::erff(x); } + static EIGEN_STRONG_INLINE float run(float x) { +#if defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__) + return cl::sycl::erf(x); +#else + return ::erff(x); +#endif + } }; template <> struct erf_impl<double> { EIGEN_DEVICE_FUNC - static EIGEN_STRONG_INLINE double run(double x) { return ::erf(x); } + static EIGEN_STRONG_INLINE double run(double x) { +#if defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__) + return cl::sycl::erf(x); +#else + return ::erf(x); +#endif + } }; #endif // EIGEN_HAS_C99_MATH @@ -456,13 +472,25 @@ struct erfc_retval { template <> struct erfc_impl<float> { EIGEN_DEVICE_FUNC - static EIGEN_STRONG_INLINE float run(const float x) { return ::erfcf(x); } + static EIGEN_STRONG_INLINE float run(const float x) { +#if defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__) + return cl::sycl::erfc(x); +#else + return ::erfcf(x); +#endif + } }; template <> struct erfc_impl<double> { EIGEN_DEVICE_FUNC - static EIGEN_STRONG_INLINE double run(const double x) { return ::erfc(x); } + static EIGEN_STRONG_INLINE double run(const double x) { +#if defined(EIGEN_USE_SYCL) && defined(__SYCL_DEVICE_ONLY__) + return cl::sycl::erfc(x); +#else + return ::erfc(x); +#endif + } }; #endif // EIGEN_HAS_C99_MATH diff --git a/unsupported/test/cxx11_tensor_concatenation.cpp b/unsupported/test/cxx11_tensor_concatenation.cpp index 9189a609b..f53515b4e 100644 --- a/unsupported/test/cxx11_tensor_concatenation.cpp +++ b/unsupported/test/cxx11_tensor_concatenation.cpp @@ -50,7 +50,13 @@ static void test_static_dimension_failure() .reshape(Tensor<int, 3>::Dimensions(2, 3, 1)) .concatenate(right, 0); Tensor<int, 2, DataLayout> alternative = left - .concatenate(right.reshape(Tensor<int, 2>::Dimensions{{{2, 3}}}), 0); + // Clang compiler break with {{{}}} with an ambigous error on copy constructor + // the variadic DSize constructor added for #ifndef EIGEN_EMULATE_CXX11_META_H. + // Solution: + // either the code should change to + // Tensor<int, 2>::Dimensions{{2, 3}} + // or Tensor<int, 2>::Dimensions{Tensor<int, 2>::Dimensions{{2, 3}}} + .concatenate(right.reshape(Tensor<int, 2>::Dimensions{{2, 3}}), 0); } template<int DataLayout> diff --git a/unsupported/test/cxx11_tensor_thread_pool.cpp b/unsupported/test/cxx11_tensor_thread_pool.cpp index 20a197f2b..5c3aae482 100644 --- a/unsupported/test/cxx11_tensor_thread_pool.cpp +++ b/unsupported/test/cxx11_tensor_thread_pool.cpp @@ -16,6 +16,25 @@ using Eigen::Tensor; +class TestAllocator : public Allocator { + public: + ~TestAllocator() override {} + EIGEN_DEVICE_FUNC void* allocate(size_t num_bytes) const override { + const_cast<TestAllocator*>(this)->alloc_count_++; + return internal::aligned_malloc(num_bytes); + } + EIGEN_DEVICE_FUNC void deallocate(void* buffer) const override { + const_cast<TestAllocator*>(this)->dealloc_count_++; + internal::aligned_free(buffer); + } + + int alloc_count() const { return alloc_count_; } + int dealloc_count() const { return dealloc_count_; } + + private: + int alloc_count_ = 0; + int dealloc_count_ = 0; +}; void test_multithread_elementwise() { @@ -374,14 +393,14 @@ void test_multithread_random() } template<int DataLayout> -void test_multithread_shuffle() +void test_multithread_shuffle(Allocator* allocator) { Tensor<float, 4, DataLayout> tensor(17,5,7,11); tensor.setRandom(); const int num_threads = internal::random<int>(2, 11); ThreadPool threads(num_threads); - Eigen::ThreadPoolDevice device(&threads, num_threads); + Eigen::ThreadPoolDevice device(&threads, num_threads, allocator); Tensor<float, 4, DataLayout> shuffle(7,5,11,17); array<ptrdiff_t, 4> shuffles = {{2,1,3,0}}; @@ -398,6 +417,21 @@ void test_multithread_shuffle() } } +void test_threadpool_allocate(TestAllocator* allocator) +{ + const int num_threads = internal::random<int>(2, 11); + const int num_allocs = internal::random<int>(2, 11); + ThreadPool threads(num_threads); + Eigen::ThreadPoolDevice device(&threads, num_threads, allocator); + + for (int a = 0; a < num_allocs; ++a) { + void* ptr = device.allocate(512); + device.deallocate(ptr); + } + VERIFY(allocator != nullptr); + VERIFY_IS_EQUAL(allocator->alloc_count(), num_allocs); + VERIFY_IS_EQUAL(allocator->dealloc_count(), num_allocs); +} EIGEN_DECLARE_TEST(cxx11_tensor_thread_pool) { @@ -424,6 +458,9 @@ EIGEN_DECLARE_TEST(cxx11_tensor_thread_pool) CALL_SUBTEST_6(test_memcpy()); CALL_SUBTEST_6(test_multithread_random()); - CALL_SUBTEST_6(test_multithread_shuffle<ColMajor>()); - CALL_SUBTEST_6(test_multithread_shuffle<RowMajor>()); + + TestAllocator test_allocator; + CALL_SUBTEST_6(test_multithread_shuffle<ColMajor>(nullptr)); + CALL_SUBTEST_6(test_multithread_shuffle<RowMajor>(&test_allocator)); + CALL_SUBTEST_6(test_threadpool_allocate(&test_allocator)); } diff --git a/unsupported/test/cxx11_tensor_trace.cpp b/unsupported/test/cxx11_tensor_trace.cpp index 1579bc1eb..0cb23060e 100644 --- a/unsupported/test/cxx11_tensor_trace.cpp +++ b/unsupported/test/cxx11_tensor_trace.cpp @@ -37,7 +37,7 @@ static void test_all_dimensions_trace() { VERIFY_IS_EQUAL(result1(), sum); Tensor<float, 5, DataLayout> tensor2(7, 7, 7, 7, 7); - array<ptrdiff_t, 5> dims({{2, 1, 0, 3, 4}}); + array<ptrdiff_t, 5> dims = { { 2, 1, 0, 3, 4 } }; Tensor<float, 0, DataLayout> result2 = tensor2.trace(dims); VERIFY_IS_EQUAL(result2.rank(), 0); sum = 0.0f; @@ -52,7 +52,7 @@ template <int DataLayout> static void test_simple_trace() { Tensor<float, 3, DataLayout> tensor1(3, 5, 3); tensor1.setRandom(); - array<ptrdiff_t, 2> dims1({{0, 2}}); + array<ptrdiff_t, 2> dims1 = { { 0, 2 } }; Tensor<float, 1, DataLayout> result1 = tensor1.trace(dims1); VERIFY_IS_EQUAL(result1.rank(), 1); VERIFY_IS_EQUAL(result1.dimension(0), 5); @@ -67,7 +67,7 @@ static void test_simple_trace() { Tensor<float, 4, DataLayout> tensor2(5, 5, 7, 7); tensor2.setRandom(); - array<ptrdiff_t, 2> dims2({{2, 3}}); + array<ptrdiff_t, 2> dims2 = { { 2, 3 } }; Tensor<float, 2, DataLayout> result2 = tensor2.trace(dims2); VERIFY_IS_EQUAL(result2.rank(), 2); VERIFY_IS_EQUAL(result2.dimension(0), 5); @@ -82,7 +82,7 @@ static void test_simple_trace() { } } - array<ptrdiff_t, 2> dims3({{1, 0}}); + array<ptrdiff_t, 2> dims3 = { { 1, 0 } }; Tensor<float, 2, DataLayout> result3 = tensor2.trace(dims3); VERIFY_IS_EQUAL(result3.rank(), 2); VERIFY_IS_EQUAL(result3.dimension(0), 7); @@ -99,7 +99,7 @@ static void test_simple_trace() { Tensor<float, 5, DataLayout> tensor3(3, 7, 3, 7, 3); tensor3.setRandom(); - array<ptrdiff_t, 3> dims4({{0, 2, 4}}); + array<ptrdiff_t, 3> dims4 = { { 0, 2, 4 } }; Tensor<float, 2, DataLayout> result4 = tensor3.trace(dims4); VERIFY_IS_EQUAL(result4.rank(), 2); VERIFY_IS_EQUAL(result4.dimension(0), 7); @@ -116,7 +116,7 @@ static void test_simple_trace() { Tensor<float, 5, DataLayout> tensor4(3, 7, 4, 7, 5); tensor4.setRandom(); - array<ptrdiff_t, 2> dims5({{1, 3}}); + array<ptrdiff_t, 2> dims5 = { { 1, 3 } }; Tensor<float, 3, DataLayout> result5 = tensor4.trace(dims5); VERIFY_IS_EQUAL(result5.rank(), 3); VERIFY_IS_EQUAL(result5.dimension(0), 3); @@ -140,7 +140,7 @@ template<int DataLayout> static void test_trace_in_expr() { Tensor<float, 4, DataLayout> tensor(2, 3, 5, 3); tensor.setRandom(); - array<ptrdiff_t, 2> dims({{1, 3}}); + array<ptrdiff_t, 2> dims = { { 1, 3 } }; Tensor<float, 2, DataLayout> result(2, 5); result = result.constant(1.0f) - tensor.trace(dims); VERIFY_IS_EQUAL(result.rank(), 2); @@ -168,4 +168,4 @@ EIGEN_DECLARE_TEST(cxx11_tensor_trace) { CALL_SUBTEST(test_simple_trace<RowMajor>()); CALL_SUBTEST(test_trace_in_expr<ColMajor>()); CALL_SUBTEST(test_trace_in_expr<RowMajor>()); -} +}
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