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Assertion updates to macros (mostly) with backtrace.

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WIlson flow to include options for DBW2, Iwasaki, Symanzik.
View logging for data assurance
This commit is contained in:
Peter Boyle
2025-08-07 15:48:38 +00:00
parent 41f344bbd3
commit 9e6a4a4737
306 changed files with 2013 additions and 1928 deletions
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Grid/serialisation/BaseIO.h
+11 -11
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@@ -307,14 +307,14 @@ namespace Grid {
constexpr unsigned int ContainerRank{Traits::Rank}; // Only non-zero for containers
constexpr unsigned int TotalRank{TensorRank + ContainerRank};
const Index NumElements{output.size()};
assert( NumElements > 0 );
GRID_ASSERT( NumElements > 0 );
// Get the dimensionality of the tensor
std::vector<std::size_t> TotalDims(TotalRank);
for(auto i = 0; i < TensorRank; i++ ) {
auto dim = output.dimension(i);
TotalDims[i] = static_cast<size_t>(dim);
assert( TotalDims[i] == dim ); // check we didn't lose anything in the conversion
GRID_ASSERT( TotalDims[i] == dim ); // check we didn't lose anything in the conversion
}
for(auto i = 0; i < ContainerRank; i++ )
TotalDims[TensorRank + i] = Traits::Dimension(i);
@@ -452,7 +452,7 @@ namespace Grid {
std::vector<std::size_t> dimData;
std::vector<Scalar> buf;
upcast->readMultiDim( s, buf, dimData );
assert(dimData.size() == TotalRank && "EigenIO: Tensor rank mismatch" );
GRID_ASSERT(dimData.size() == TotalRank && "EigenIO: Tensor rank mismatch" );
// Make sure that the number of elements read matches dimensions read
std::size_t NumContainers = 1;
for( auto i = 0 ; i < TensorRank ; i++ )
@@ -460,10 +460,10 @@ namespace Grid {
// If our scalar object is a Container, make sure it's dimensions match what we read back
std::size_t ElementsPerContainer = 1;
for( auto i = 0 ; i < ContainerRank ; i++ ) {
assert( dimData[TensorRank+i] == Traits::Dimension(i) && "Tensor Container dimensions don't match data" );
GRID_ASSERT( dimData[TensorRank+i] == Traits::Dimension(i) && "Tensor Container dimensions don't match data" );
ElementsPerContainer *= dimData[TensorRank+i];
}
assert( NumContainers * ElementsPerContainer == buf.size() && "EigenIO: Number of elements != product of dimensions" );
GRID_ASSERT( NumContainers * ElementsPerContainer == buf.size() && "EigenIO: Number of elements != product of dimensions" );
// Now see whether the tensor is the right shape, or can be made to be
const auto & dims = output.dimensions();
bool bShapeOK = (output.data() != nullptr);
@@ -487,7 +487,7 @@ namespace Grid {
for( int i = TensorRank - 1; i != -1 && ++MyIndex[i] == dims[i]; i-- )
MyIndex[i] = 0;
}
assert( pSource == &buf[NumContainers * ElementsPerContainer] );
GRID_ASSERT( pSource == &buf[NumContainers * ElementsPerContainer] );
}
template <typename T>
@@ -495,7 +495,7 @@ namespace Grid {
typename std::enable_if<EigenIO::is_tensor_fixed<ETensor>::value, void>::type
Reader<T>::Reshape(ETensor &t, const std::array<typename ETensor::Index, ETensor::NumDimensions> &dims )
{
assert( 0 && "EigenIO: Fixed tensor dimensions can't be changed" );
GRID_ASSERT( 0 && "EigenIO: Fixed tensor dimensions can't be changed" );
}
template <typename T>
@@ -505,7 +505,7 @@ namespace Grid {
{
#ifdef GRID_OMP
// The memory counter is the reason this must be done from the primary thread
assert(omp_in_parallel()==0 && "Deserialisation which resizes Eigen tensor must happen from primary thread");
GRID_ASSERT(omp_in_parallel()==0 && "Deserialisation which resizes Eigen tensor must happen from primary thread");
#endif
EigenIO::EigenResizeCounter -= static_cast<uint64_t>(t.size()) * sizeof(typename ETensor::Scalar);
//t.reshape( dims );
@@ -561,7 +561,7 @@ namespace Grid {
template <typename T1, typename T2>
static inline typename std::enable_if<EigenIO::is_tensor<T1>::value && EigenIO::is_tensor<T2>::value, bool>::type
CompareMember(const T1 &lhs, const T2 &rhs) {
// First check whether dimensions match (Eigen tensor library will assert if they don't match)
// First check whether dimensions match (Eigen tensor library will GRID_ASSERT if they don't match)
bool bReturnValue = (T1::NumIndices == T2::NumIndices);
for( auto i = 0 ; bReturnValue && i < T1::NumIndices ; i++ )
bReturnValue = ( lhs.dimension(i) == rhs.dimension(i) );
@@ -593,7 +593,7 @@ namespace Grid {
WriteMember(std::ostream &os, const T &object) {
using Index = typename T::Index;
const Index NumElements{object.size()};
assert( NumElements > 0 );
GRID_ASSERT( NumElements > 0 );
Index count = 1;
os << "T<";
for( int i = 0; i < T::NumIndices; i++ ) {
@@ -603,7 +603,7 @@ namespace Grid {
os << ",";
os << dim;
}
assert( count == NumElements && "Number of elements doesn't match tensor dimensions" );
GRID_ASSERT( count == NumElements && "Number of elements doesn't match tensor dimensions" );
os << ">{";
const typename T::Scalar * p = object.data();
for( Index i = 0; i < count; i++ ) {
Grid/serialisation/BinaryIO.h
+2 -2
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@@ -103,7 +103,7 @@ NAMESPACE_BEGIN(Grid);
uint64_t tmp = 1;
for( auto i = 0 ; i < rank ; i++ )
tmp *= Dimensions[i];
assert( tmp == NumElements && "Dimensions don't match size of data being written" );
GRID_ASSERT( tmp == NumElements && "Dimensions don't match size of data being written" );
// Total number of elements
write("", tmp);
// Number of dimensions
@@ -158,7 +158,7 @@ NAMESPACE_BEGIN(Grid);
dim[i] = tmp;
count *= tmp;
}
assert( count == NumElements && "Dimensions don't match size of data being read" );
GRID_ASSERT( count == NumElements && "Dimensions don't match size of data being read" );
buf.resize(count);
for( auto i = 0; i < count; ++i)
read("", buf[i]);
Grid/serialisation/Hdf5IO.h
+1 -1
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@@ -174,7 +174,7 @@ namespace Grid
// Now make sure overall size is not too big
hsize_t OverflowCheck = ElementsPerChunk;
ElementsPerChunk *= d;
assert( OverflowCheck == ElementsPerChunk / d && "Product of dimensions overflowed hsize_t" );
GRID_ASSERT( OverflowCheck == ElementsPerChunk / d && "Product of dimensions overflowed hsize_t" );
// If product of dimensions too big, reduce by prime factors
while( ElementsPerChunk > MaxElements && ( ElementsPerChunk & 1 ) == 0 ) {
bTooBig = true;
Grid/serialisation/VectorUtils.h
+5 -5
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@@ -447,9 +447,9 @@ namespace Grid {
using Traits = GridTypeMapper<typename is_flattenable<W>::grid_type>;
const int gridRank{Traits::Rank};
const int dimRank{static_cast<int>(dim_.size())};
assert(dimRank >= gridRank && "Tensor rank too low for Grid tensor");
GRID_ASSERT(dimRank >= gridRank && "Tensor rank too low for Grid tensor");
for (int i=0; i<gridRank; ++i) {
assert(dim_[dimRank - gridRank + i] == Traits::Dimension(i) && "Tensor dimension doesn't match Grid tensor");
GRID_ASSERT(dim_[dimRank - gridRank + i] == Traits::Dimension(i) && "Tensor dimension doesn't match Grid tensor");
}
dim_.resize(dimRank - gridRank);
}
@@ -461,7 +461,7 @@ namespace Grid {
, dim_(dim)
{
checkInnermost(vector_);
assert(dim_.size() == is_flattenable<V>::vecRank && "Tensor rank doesn't match nested std::vector rank");
GRID_ASSERT(dim_.size() == is_flattenable<V>::vecRank && "Tensor rank doesn't match nested std::vector rank");
resize(vector_, 0);
fill(vector_);
}
@@ -512,14 +512,14 @@ namespace Grid {
{
if( bFirst)
{
assert( Dims.size() == Depth && "Bug: Delete this message after testing" );
GRID_ASSERT( Dims.size() == Depth && "Bug: Delete this message after testing" );
Dims.push_back(v[0].size());
if (!Dims[Depth])
return false;
}
else
{
assert( Dims.size() >= Depth + 1 && "Bug: Delete this message after testing" );
GRID_ASSERT( Dims.size() >= Depth + 1 && "Bug: Delete this message after testing" );
}
for (std::size_t i = 0; i < v.size(); ++i)
{
Grid/serialisation/XmlIO.h
+1 -1
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@@ -145,7 +145,7 @@ namespace Grid
write("dim", d);
count *= d;
}
assert( count == NumElements && "XmlIO : element count doesn't match dimensions" );
GRID_ASSERT( count == NumElements && "XmlIO : element count doesn't match dimensions" );
static const char sName[] = "tensor";
for( int i = 0 ; i < Rank ; i++ ) {
MyIndex[i] = 0;