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Removed Eigen::DontAlign attribute

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This commit is contained in:
Michael Marshall 2019-02-05 12:50:28 +00:00
parent 5b0870bb19
commit 57e57d162f
1 changed files with 45 additions and 36 deletions
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81
Hadrons/Modules/MDistil/Distil.hpp
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@ -236,21 +236,28 @@ inline GridCartesian * MakeLowerDimGrid( GridCartesian * gridHD )
/****************************************************************************** /******************************************************************************
Perambulator object Perambulator object
This is an Eigen::Tensor of type Scalar_ and rank NumIndices_ (row-major order)
They can be persisted to disk, with the on-disk format being big endian.
Scalar_ objects are assumed to be composite objects of size Endian_Scalar_Size.
(Disable big-endian by setting Endian_Scalar_Size=1)
IndexNames contains one name for each index, and IndexNames are validated on load.
(NB: Indices of dimension 1 are not saved, and not validated on load)
******************************************************************************/ ******************************************************************************/
template<typename Scalar_, int NumIndices_, uint16_t Scalar_Unit_Size = sizeof(Scalar_)> template<typename Scalar_, int NumIndices_, uint16_t Endian_Scalar_Size = sizeof(Scalar_)>
class NamedTensor : public Eigen::Tensor<Scalar_, NumIndices_, Eigen::RowMajor | Eigen::DontAlign> class NamedTensor : public Eigen::Tensor<Scalar_, NumIndices_, Eigen::RowMajor>
{ {
public: public:
typedef Eigen::Tensor<Scalar_, NumIndices_, Eigen::RowMajor | Eigen::DontAlign> ET; typedef Eigen::Tensor<Scalar_, NumIndices_, Eigen::RowMajor> ET;
std::array<std::string,NumIndices_> IndexNames; std::array<std::string,NumIndices_> IndexNames;
public: public:
template<typename... IndexTypes> template<typename... IndexTypes>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE NamedTensor(std::array<std::string,NumIndices_> &IndexNames_, Eigen::Index firstDimension, IndexTypes... otherDimensions) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE NamedTensor(std::array<std::string,NumIndices_> &IndexNames_, Eigen::Index firstDimension, IndexTypes... otherDimensions)
: IndexNames{IndexNames_}, Eigen::Tensor<Scalar_, NumIndices_, Eigen::RowMajor | Eigen::DontAlign>(firstDimension, otherDimensions...) : IndexNames{IndexNames_}, ET(firstDimension, otherDimensions...)
{ {
// The number of dimensions used to construct a tensor must be equal to the rank of the tensor. // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 1 == NumIndices_, YOU_MADE_A_PROGRAMMING_MISTAKE) assert(sizeof...(otherDimensions) + 1 == NumIndices_
&& "NamedTensor error: dimensions in constructor != tensor rank");
} }
// Share data for timeslices we calculated with other nodes // Share data for timeslices we calculated with other nodes
@ -267,16 +274,17 @@ public:
/****************************************************************************** /******************************************************************************
Save NamedTensor binary format (NB: On-disk format is Big Endian) Save NamedTensor binary format (NB: On-disk format is Big Endian)
Assumes the Scalar_ objects are contiguous (no padding)
******************************************************************************/ ******************************************************************************/
template<typename Scalar_, int NumIndices_, uint16_t Scalar_Unit_Size> template<typename Scalar_, int NumIndices_, uint16_t Endian_Scalar_Size>
void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::WriteBinary(const std::string filename) { void NamedTensor<Scalar_, NumIndices_, Endian_Scalar_Size>::WriteBinary(const std::string filename) {
LOG(Message) << "Writing NamedTensor to \"" << filename << "\"" << std::endl; LOG(Message) << "Writing NamedTensor to \"" << filename << "\"" << std::endl;
std::ofstream w(filename, std::ios::binary); std::ofstream w(filename, std::ios::binary);
// Enforce assumption that the scalar is composed of fundamental elements of size Scalar_Unit_Size // Enforce assumption that the scalar is composed of fundamental elements of size Endian_Scalar_Size
assert((Scalar_Unit_Size == 1 || Scalar_Unit_Size == 2 || Scalar_Unit_Size == 4 || Scalar_Unit_Size == 8 ) assert((Endian_Scalar_Size == 1 || Endian_Scalar_Size == 2 || Endian_Scalar_Size == 4 || Endian_Scalar_Size == 8 )
&& "Scalar_Unit_Size should be 1, 2, 4 or 8"); && "NamedTensor error: Endian_Scalar_Size should be 1, 2, 4 or 8");
assert((sizeof(Scalar_) % Scalar_Unit_Size) == 0 && "Scalar_ is not composed of Scalar_Unit_Size" ); assert((sizeof(Scalar_) % Endian_Scalar_Size) == 0 && "NamedTensor error: Scalar_ is not composed of Endian_Scalar_Size" );
// Size of the data (in bytes) // Size of the data (in bytes)
const uint32_t Scalar_Size{sizeof(Scalar_)}; const uint32_t Scalar_Size{sizeof(Scalar_)};
const auto NumElements{this->size()}; const auto NumElements{this->size()};
@ -286,8 +294,8 @@ void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::WriteBinary(const std:
// Size of a Scalar_ // Size of a Scalar_
uint32_t u32{htobe32(Scalar_Size)}; uint32_t u32{htobe32(Scalar_Size)};
w.write(reinterpret_cast<const char *>(&u32), sizeof(u32)); w.write(reinterpret_cast<const char *>(&u32), sizeof(u32));
// Scalar_Unit_Size // Endian_Scalar_Size
uint16_t u16{htobe16(Scalar_Unit_Size)}; uint16_t u16{htobe16(Endian_Scalar_Size)};
w.write(reinterpret_cast<const char *>(&u16), sizeof(u16)); w.write(reinterpret_cast<const char *>(&u16), sizeof(u16));
// number of dimensions which aren't 1 // number of dimensions which aren't 1
u16 = static_cast<uint16_t>(this->NumIndices); u16 = static_cast<uint16_t>(this->NumIndices);
@ -315,24 +323,24 @@ void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::WriteBinary(const std:
char * const pStart{reinterpret_cast<char *>(this->data())}; char * const pStart{reinterpret_cast<char *>(this->data())};
// Swap to network byte order in place (alternative is to copy memory - still slow) // Swap to network byte order in place (alternative is to copy memory - still slow)
void * const pEnd{pStart + TotalDataSize}; void * const pEnd{pStart + TotalDataSize};
if(Scalar_Unit_Size == 8) if(Endian_Scalar_Size == 8)
for(uint64_t * p = reinterpret_cast<uint64_t *>(pStart) ; p < pEnd ; p++ ) for(uint64_t * p = reinterpret_cast<uint64_t *>(pStart) ; p < pEnd ; p++ )
* p = htobe64( * p ); * p = htobe64( * p );
else if(Scalar_Unit_Size == 4) else if(Endian_Scalar_Size == 4)
for(uint32_t * p = reinterpret_cast<uint32_t *>(pStart) ; p < pEnd ; p++ ) for(uint32_t * p = reinterpret_cast<uint32_t *>(pStart) ; p < pEnd ; p++ )
* p = htobe32( * p ); * p = htobe32( * p );
else if(Scalar_Unit_Size == 2) else if(Endian_Scalar_Size == 2)
for(uint16_t * p = reinterpret_cast<uint16_t *>(pStart) ; p < pEnd ; p++ ) for(uint16_t * p = reinterpret_cast<uint16_t *>(pStart) ; p < pEnd ; p++ )
* p = htobe16( * p ); * p = htobe16( * p );
w.write(pStart, TotalDataSize); w.write(pStart, TotalDataSize);
// Swap back from network byte order // Swap back from network byte order
if(Scalar_Unit_Size == 8) if(Endian_Scalar_Size == 8)
for(uint64_t * p = reinterpret_cast<uint64_t *>(pStart) ; p < pEnd ; p++ ) for(uint64_t * p = reinterpret_cast<uint64_t *>(pStart) ; p < pEnd ; p++ )
* p = be64toh( * p ); * p = be64toh( * p );
else if(Scalar_Unit_Size == 4) else if(Endian_Scalar_Size == 4)
for(uint32_t * p = reinterpret_cast<uint32_t *>(pStart) ; p < pEnd ; p++ ) for(uint32_t * p = reinterpret_cast<uint32_t *>(pStart) ; p < pEnd ; p++ )
* p = be32toh( * p ); * p = be32toh( * p );
else if(Scalar_Unit_Size == 2) else if(Endian_Scalar_Size == 2)
for(uint16_t * p = reinterpret_cast<uint16_t *>(pStart) ; p < pEnd ; p++ ) for(uint16_t * p = reinterpret_cast<uint16_t *>(pStart) ; p < pEnd ; p++ )
* p = be16toh( * p ); * p = be16toh( * p );
// checksum // checksum
@ -346,16 +354,17 @@ void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::WriteBinary(const std:
/****************************************************************************** /******************************************************************************
Load NamedTensor binary format (NB: On-disk format is Big Endian) Load NamedTensor binary format (NB: On-disk format is Big Endian)
Assumes the Scalar_ objects are contiguous (no padding)
******************************************************************************/ ******************************************************************************/
template<typename Scalar_, int NumIndices_, uint16_t Scalar_Unit_Size> template<typename Scalar_, int NumIndices_, uint16_t Endian_Scalar_Size>
void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::ReadBinary(const std::string filename) { void NamedTensor<Scalar_, NumIndices_, Endian_Scalar_Size>::ReadBinary(const std::string filename) {
LOG(Message) << "Reading NamedTensor from \"" << filename << "\"" << std::endl; LOG(Message) << "Reading NamedTensor from \"" << filename << "\"" << std::endl;
std::ifstream r(filename, std::ios::binary); std::ifstream r(filename, std::ios::binary);
// Enforce assumption that the scalar is composed of fundamental elements of size Scalar_Unit_Size // Enforce assumption that the scalar is composed of fundamental elements of size Endian_Scalar_Size
assert((Scalar_Unit_Size == 1 || Scalar_Unit_Size == 2 || Scalar_Unit_Size == 4 || Scalar_Unit_Size == 8 ) assert((Endian_Scalar_Size == 1 || Endian_Scalar_Size == 2 || Endian_Scalar_Size == 4 || Endian_Scalar_Size == 8 )
&& "NamedTensor error: Scalar_Unit_Size should be 1, 2, 4 or 8"); && "NamedTensor error: Endian_Scalar_Size should be 1, 2, 4 or 8");
assert((sizeof(Scalar_) % Scalar_Unit_Size) == 0 && "NamedTensor error: Scalar_ is not composed of Scalar_Unit_Size" ); assert((sizeof(Scalar_) % Endian_Scalar_Size) == 0 && "NamedTensor error: Scalar_ is not composed of Endian_Scalar_Size" );
// Size of the data in bytes // Size of the data in bytes
const uint32_t Scalar_Size{sizeof(Scalar_)}; const uint32_t Scalar_Size{sizeof(Scalar_)};
const auto NumElements{this->size()}; const auto NumElements{this->size()};
@ -367,10 +376,10 @@ void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::ReadBinary(const std::
uint32_t u32; uint32_t u32;
r.read(reinterpret_cast<char *>(&u32), sizeof(u32)); r.read(reinterpret_cast<char *>(&u32), sizeof(u32));
assert( Scalar_Size == be32toh( u32 ) && "NamedTensor error: sizeof(Scalar_)"); assert( Scalar_Size == be32toh( u32 ) && "NamedTensor error: sizeof(Scalar_)");
// Scalar_Unit_Size // Endian_Scalar_Size
uint16_t u16; uint16_t u16;
r.read(reinterpret_cast<char *>(&u16), sizeof(u16)); r.read(reinterpret_cast<char *>(&u16), sizeof(u16));
assert( Scalar_Unit_Size == be16toh( u16 ) && "NamedTensor error: Scalar_Unit_size"); assert( Endian_Scalar_Size == be16toh( u16 ) && "NamedTensor error: Scalar_Unit_size");
// number of dimensions which aren't 1 // number of dimensions which aren't 1
r.read(reinterpret_cast<char *>(&u16), sizeof(u16)); r.read(reinterpret_cast<char *>(&u16), sizeof(u16));
u16 = be16toh( u16 ); u16 = be16toh( u16 );
@ -401,13 +410,13 @@ void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::ReadBinary(const std::
void * const pEnd{pStart + TotalDataSize}; void * const pEnd{pStart + TotalDataSize};
r.read(pStart,TotalDataSize); r.read(pStart,TotalDataSize);
// Swap back from network byte order // Swap back from network byte order
if(Scalar_Unit_Size == 8) if(Endian_Scalar_Size == 8)
for(uint64_t * p = reinterpret_cast<uint64_t *>(pStart) ; p < pEnd ; p++ ) for(uint64_t * p = reinterpret_cast<uint64_t *>(pStart) ; p < pEnd ; p++ )
* p = be64toh( * p ); * p = be64toh( * p );
else if(Scalar_Unit_Size == 4) else if(Endian_Scalar_Size == 4)
for(uint32_t * p = reinterpret_cast<uint32_t *>(pStart) ; p < pEnd ; p++ ) for(uint32_t * p = reinterpret_cast<uint32_t *>(pStart) ; p < pEnd ; p++ )
* p = be32toh( * p ); * p = be32toh( * p );
else if(Scalar_Unit_Size == 2) else if(Endian_Scalar_Size == 2)
for(uint16_t * p = reinterpret_cast<uint16_t *>(pStart) ; p < pEnd ; p++ ) for(uint16_t * p = reinterpret_cast<uint16_t *>(pStart) ; p < pEnd ; p++ )
* p = be16toh( * p ); * p = be16toh( * p );
// checksum // checksum
@ -425,8 +434,8 @@ void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::ReadBinary(const std::
Save NamedTensor Hdf5 format Save NamedTensor Hdf5 format
******************************************************************************/ ******************************************************************************/
template<typename Scalar_, int NumIndices_, uint16_t Scalar_Unit_Size> template<typename Scalar_, int NumIndices_, uint16_t Endian_Scalar_Size>
void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::save(const std::string filename) const { void NamedTensor<Scalar_, NumIndices_, Endian_Scalar_Size>::save(const std::string filename) const {
LOG(Message) << "Writing NamedTensor to \"" << filename << "\"" << std::endl; LOG(Message) << "Writing NamedTensor to \"" << filename << "\"" << std::endl;
#ifndef HAVE_HDF5 #ifndef HAVE_HDF5
LOG(Message) << "Error: I/O for NamedTensor requires HDF5" << std::endl; LOG(Message) << "Error: I/O for NamedTensor requires HDF5" << std::endl;
@ -440,8 +449,8 @@ void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::save(const std::string
Load NamedTensor Hdf5 format Load NamedTensor Hdf5 format
******************************************************************************/ ******************************************************************************/
template<typename Scalar_, int NumIndices_, uint16_t Scalar_Unit_Size> template<typename Scalar_, int NumIndices_, uint16_t Endian_Scalar_Size>
void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::load(const std::string filename) { void NamedTensor<Scalar_, NumIndices_, Endian_Scalar_Size>::load(const std::string filename) {
LOG(Message) << "Reading NamedTensor from \"" << filename << "\"" << std::endl; LOG(Message) << "Reading NamedTensor from \"" << filename << "\"" << std::endl;
#ifndef HAVE_HDF5 #ifndef HAVE_HDF5
LOG(Message) << "Error: I/O for NamedTensor requires HDF5" << std::endl; LOG(Message) << "Error: I/O for NamedTensor requires HDF5" << std::endl;
@ -458,8 +467,8 @@ void NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>::load(const std::string
Perambulator object Perambulator object
******************************************************************************/ ******************************************************************************/
template<typename Scalar_, int NumIndices_, uint16_t Scalar_Unit_Size = sizeof(Scalar_)> template<typename Scalar_, int NumIndices_, uint16_t Endian_Scalar_Size = sizeof(Scalar_)>
using Perambulator = NamedTensor<Scalar_, NumIndices_, Scalar_Unit_Size>; using Perambulator = NamedTensor<Scalar_, NumIndices_, Endian_Scalar_Size>;
/************************************************************************************* /*************************************************************************************