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Fix for testArithmeticCpu from TMVA #512

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Merged
merged 2 commits into from
Apr 19, 2017
Merged

Fix for testArithmeticCpu from TMVA #512

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03d27a5
[TMVA] Allow different matrix types in maximumRelativeError()
amadio Apr 19, 2017
72073d8
[TMVA] Prevent double->float conversions in TestMatrixArithmetic
amadio Apr 19, 2017
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11 changes: 5 additions & 6 deletions tmva/tmva/test/DNN/TestMatrixArithmetic.h
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Original file line number Diff line number Diff line change
Expand Up @@ -38,8 +38,7 @@ auto testMultiplication(size_t ntests)
n = rand() % 100 + 1;
k = rand() % 100 + 1;

TMatrixT<Double_t> ARef(m,k), A2Ref(m,k), ATRef(k,m) , BRef(k,n),
BTRef(n,k), CRef(m,n);
TMatrixT<Scalar_t> ARef(m,k), A2Ref(m,k), ATRef(k,m) , BRef(k,n), BTRef(n,k), CRef(m,n);
TMVA::DNN::randomMatrix(ARef);
TMVA::DNN::randomMatrix(A2Ref);
TMVA::DNN::randomMatrix(ATRef);
Expand All @@ -50,19 +49,19 @@ auto testMultiplication(size_t ntests)
// A * B
CRef.Mult(ARef,BRef);
Architecture_t::Multiply(C, A, B);
Scalar_t error = TMVA::DNN::maximumRelativeError((TMatrixT<Double_t>) C, CRef);
Scalar_t error = TMVA::DNN::maximumRelativeError(C, CRef);
maximumError = std::max(error, maximumError);

// A^T * B
CRef.TMult(ATRef,BRef);
Architecture_t::TransposeMultiply(C, AT, B);
error = TMVA::DNN::maximumRelativeError((TMatrixT<Double_t>) C, CRef);
error = TMVA::DNN::maximumRelativeError(C, CRef);
maximumError = std::max(error, maximumError);

// A * B^T
CRef.MultT(ARef,BTRef);
Architecture_t::MultiplyTranspose(C, A, BT);
error = TMVA::DNN::maximumRelativeError((TMatrixT<Double_t>) C, CRef);
error = TMVA::DNN::maximumRelativeError(C, CRef);
maximumError = std::max(error, maximumError);

// A .* B
Expand All @@ -72,7 +71,7 @@ auto testMultiplication(size_t ntests)
}
}
Architecture_t::Hadamard(A, A2);
error = TMVA::DNN::maximumRelativeError((TMatrixT<Double_t>) A, ARef);
error = TMVA::DNN::maximumRelativeError(A, ARef);
maximumError = std::max(error, maximumError);
}

Expand Down
65 changes: 25 additions & 40 deletions tmva/tmva/test/DNN/Utility.h
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
#ifndef TMVA_TEST_DNN_UTILITY
#define TMVA_TEST_DNN_UTILITY

#include <cassert>
#include <iostream>
#include <sstream>
#include <type_traits>
Expand Down Expand Up @@ -172,64 +173,48 @@ AFloat reduceMean(F f, AFloat start, const AMatrix &X)
return result / (AFloat) (m * n);
}

/** Compute the relative error of x and y normalized by y. Specialized for
* float and double to make sure both arguments are above expected machine
* precision (1e-5 and 1e-10). */
/** Compute the relative error of x and y */
//______________________________________________________________________________
template <typename AFloat>
inline AFloat relativeError(const AFloat &x,
const AFloat &y);
template <typename T>
inline T relativeError(const T &x, const T &y)
{
using std::abs;

if (x == y)
return T(0.0);

//______________________________________________________________________________
template <>
inline Double_t relativeError(const Double_t &x,
const Double_t &y)
{
if ((std::abs(x) > 1e-10) && (std::abs(y) > 1e-10)) {
return std::fabs((x - y) / y);
} else {
return std::fabs(x - y);
}
}
T diff = abs(x - y);

//______________________________________________________________________________
template <>
inline Real_t relativeError(const Real_t &x,
const Real_t &y)
{
if ((std::abs(x) > 1e-5) && (std::abs(y) > 1e-5)) {
return std::fabs((x - y) / y);
} else {
return std::fabs(x - y);
}
if (x * y == T(0.0) ||
diff < std::numeric_limits<T>::epsilon())
return diff;

return diff / (abs(x) + abs(y));
}

/*! Compute the maximum, element-wise relative error of the matrices
* X and Y normalized by the element of Y. Protected against division
* by zero. */
//______________________________________________________________________________
template <typename AMatrix>
auto maximumRelativeError(const AMatrix &X,
const AMatrix &Y)
-> decltype(X(0,0))
template <typename Matrix1, typename Matrix2>
auto maximumRelativeError(const Matrix1 &X, const Matrix2 &Y) -> decltype(X(0,0))
{
decltype(X(0,0)) curError, maxError = 0.0;

using AFloat = decltype(X(0,0));

size_t m,n;
m = X.GetNrows();
n = X.GetNcols();
size_t m = X.GetNrows();
size_t n = X.GetNcols();

AFloat maximumError = 0.0;
assert(m == Y.GetNrows());
assert(n == Y.GetNcols());

for (size_t i = 0; i < m; i++) {
for (size_t j = 0; j < n; j++) {
AFloat error = relativeError(X(i,j), Y(i,j));
maximumError = std::max(error, maximumError);
curError = relativeError(X(i,j), Y(i,j));
maxError = std::max(curError, maxError);
}
}
return maximumError;

return maxError;
}

/*! Numerically compute the derivative of the functional f using finite
Expand Down