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Fix TensorReduction warnings and error bound for sum accuracy test.

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The sum accuracy test currently uses the default test precision for
the given scalar type.  However, scalars are generated via a normal
distribution, and given a large enough count and strong enough random
generator, the expected sum is zero.  This causes the test to
periodically fail.

Here we estimate an upper-bound for the error as `sqrt(N) * prec` for
summing N values, with each having an approximate epsilon of `prec`.

Also fixed a few warnings generated by MSVC when compiling the
reduction test.
This commit is contained in:
Antonio Sanchez
2021-10-29 22:03:44 +00:00
committed by Antonio Sanchez
parent b3bea43a2d
commit f6c8cc0e99
3 changed files with 8 additions and 4 deletions
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4
unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
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@@ -633,7 +633,7 @@ static const bool RunningOnGPU = false;
m_fastOutputStrides[i] = internal::TensorIntDivisor<Index>(m_outputStrides[i]);
}
} else {
m_outputStrides[NumOutputDims - 1] = 1;
m_outputStrides[static_cast<size_t>(NumOutputDims - 1)] = 1;
for (int i = NumOutputDims - 2; i >= 0; --i) {
m_outputStrides[i] = m_outputStrides[i + 1] * m_dimensions[i + 1];
m_fastOutputStrides[i] = internal::TensorIntDivisor<Index>(m_outputStrides[i]);
@@ -680,7 +680,7 @@ static const bool RunningOnGPU = false;
? internal::array_prod(input_dims)
: (static_cast<int>(Layout) == static_cast<int>(ColMajor))
? m_preservedStrides[0]
: m_preservedStrides[NumOutputDims - 1];
: m_preservedStrides[static_cast<size_t>(NumOutputDims - 1)];
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }