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authorGravatar Eugene Zhulenev <ezhulenev@google.com>2018-08-01 12:35:19 -0700
committerGravatar Eugene Zhulenev <ezhulenev@google.com>2018-08-01 12:35:19 -0700
commit64abdf1d7eb17174f571751346dd0cbadcf3bc52 (patch)
treea112affc194ca8a976e5bba18e46fa9fc9d2179a /unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h
parent385b3ff12f1dd41a096908a0103873a768a8597d (diff)
Fix typo + get rid of redundant member variables for block sizes
Diffstat (limited to 'unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h')
-rw-r--r--unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h17
1 files changed, 8 insertions, 9 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h b/unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h
index 7579ab507..aca2ead12 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorChipping.h
@@ -202,9 +202,6 @@ struct TensorEvaluator<const TensorChippingOp<DimId, ArgType>, Device>
m_inputStrides[i] = m_inputStrides[i + 1] * input_dims[i + 1];
}
}
-
- m_block_total_size_max =
- numext::maxi<Index>(1, device.lastLevelCacheSize() / sizeof(Scalar));
}
}
@@ -290,9 +287,11 @@ struct TensorEvaluator<const TensorChippingOp<DimId, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void getResourceRequirements(
std::vector<internal::TensorOpResourceRequirements>* resources) const {
+ auto block_total_size_max = numext::maxi<Eigen::Index>(
+ 1, m_device.lastLevelCacheSize() / sizeof(Scalar));
resources->push_back(internal::TensorOpResourceRequirements(
internal::TensorBlockShapeType::kSkewedInnerDims,
- m_block_total_size_max));
+ block_total_size_max));
m_impl.getResourceRequirements(resources);
}
@@ -370,13 +369,14 @@ struct TensorEvaluator<const TensorChippingOp<DimId, ArgType>, Device>
{
Index inputIndex;
if ((static_cast<int>(Layout) == static_cast<int>(ColMajor) && m_dim.actualDim() == 0) ||
- (static_cast<int>(Layout) == static_cast<int>(RowMajor) && m_dim.actualDim() == NumInputDims-1)) {
+ (static_cast<int>(Layout) == static_cast<int>(RowMajor) && m_dim.actualDim() == NumInputDims - 1)) {
// m_stride is equal to 1, so let's avoid the integer division.
eigen_assert(m_stride == 1);
inputIndex = index * m_inputStride + m_inputOffset;
- } else if ((static_cast<int>(Layout) == static_cast<int>(ColMajor) && m_dim.actualDim() == NumInputDims-1) ||
- (static_cast<int>(Layout) == static_cast<int>(RowMajor) && m_dim.actualDim() == 0)) {
- // m_stride is aways greater than index, so let's avoid the integer division.
+ } else if ((static_cast<int>(Layout) == static_cast<int>(ColMajor) && m_dim.actualDim() == NumInputDims - 1) ||
+ (static_cast<int>(Layout) == static_cast<int>(RowMajor) && m_dim.actualDim() == 0)) {
+ // m_stride is aways greater than index, so let's avoid the integer
+ // division.
eigen_assert(m_stride > index);
inputIndex = index + m_inputOffset;
} else {
@@ -392,7 +392,6 @@ struct TensorEvaluator<const TensorChippingOp<DimId, ArgType>, Device>
Index m_stride;
Index m_inputOffset;
Index m_inputStride;
- Index m_block_total_size_max;
DSizes<Index, NumInputDims> m_inputStrides;
TensorEvaluator<ArgType, Device> m_impl;
const internal::DimensionId<DimId> m_dim;