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-rw-r--r--unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h6
1 files changed, 3 insertions, 3 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h b/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
index b6dbe5a22..cca14aafd 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
@@ -120,7 +120,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
// Block based access to the XprType (input) tensor.
using TensorBlock = internal::TensorBlock<ScalarNoConst, Index, NumDims, Layout>;
using TensorBlockReader = internal::TensorBlockReader<ScalarNoConst, Index, NumDims, Layout>;
- // We do block based broadcasting using a a trick with 2x tensor rank and 0
+ // We do block based broadcasting using a trick with 2x tensor rank and 0
// strides. See block method implementation for details.
using BroadcastDimensions = DSizes<Index, 2 * NumDims>;
using BroadcastTensorBlock = internal::TensorBlock<ScalarNoConst, Index, 2 * NumDims, Layout>;
@@ -589,8 +589,8 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
std::vector<internal::TensorOpResourceRequirements>* resources) const {
// TODO(wuke): Targeting L1 size is 30% faster than targeting L{-1} on large
// tensors. But this might need further tuning.
- Index l1_cache_scalars = m_device.firstLevelCacheSize() / sizeof(Scalar);
- Index block_total_size_max = numext::maxi(Index(1), l1_cache_scalars);
+ auto block_total_size_max = numext::maxi<Eigen::Index>(
+ 1, m_device.firstLevelCacheSize() / sizeof(Scalar));
resources->push_back(internal::TensorOpResourceRequirements(
internal::TensorBlockShapeType::kSkewedInnerDims,