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Add const to non-mutating member functions across remaining modules

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libeigen/eigen!2222

Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>
This commit is contained in:
Rasmus Munk Larsen
2026-02-26 13:58:04 -08:00
parent 13b61529f4
commit 3adfa9bd37
22 changed files with 158 additions and 146 deletions
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2
unsupported/Eigen/src/Tensor/TensorContractionThreadPool.h
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@@ -281,7 +281,7 @@ struct TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgT
// Dummy struct to represent an empty DoneCallback.
struct NoCallback {
void operator()() { eigen_assert(false && "NoCallback should never be called"); }
void operator()() const { eigen_assert(false && "NoCallback should never be called"); }
};
// ------------------------------------------------------------------------ //

4
unsupported/Eigen/src/Tensor/TensorForcedEval.h
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@@ -72,7 +72,7 @@ namespace internal {
template <typename Device, typename CoeffReturnType>
struct non_integral_type_placement_new {
template <typename StorageType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void operator()(Index numValues, StorageType m_buffer) {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void operator()(Index numValues, StorageType m_buffer) const {
// Initialize non-trivially constructible types.
if (!internal::is_arithmetic<CoeffReturnType>::value) {
for (Index i = 0; i < numValues; ++i) new (m_buffer + i) CoeffReturnType();
@@ -86,7 +86,7 @@ struct non_integral_type_placement_new {
template <typename CoeffReturnType>
struct non_integral_type_placement_new<Eigen::SyclDevice, CoeffReturnType> {
template <typename StorageType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void operator()(Index, StorageType) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void operator()(Index, StorageType) const {}
};
} // end namespace internal

12
unsupported/Eigen/src/Tensor/TensorScan.h
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@@ -143,7 +143,7 @@ EIGEN_STRONG_INLINE void ReducePacket(Self& self, Index offset, typename Self::C
template <typename Self, bool Vectorize, bool Parallel>
struct ReduceBlock {
EIGEN_STRONG_INLINE void operator()(Self& self, Index idx1, typename Self::CoeffReturnType* data) {
EIGEN_STRONG_INLINE void operator()(Self& self, Index idx1, typename Self::CoeffReturnType* data) const {
for (Index idx2 = 0; idx2 < self.stride(); idx2++) {
// Calculate the starting offset for the scan
Index offset = idx1 + idx2;
@@ -155,7 +155,7 @@ struct ReduceBlock {
// Specialization for vectorized reduction.
template <typename Self>
struct ReduceBlock<Self, /*Vectorize=*/true, /*Parallel=*/false> {
EIGEN_STRONG_INLINE void operator()(Self& self, Index idx1, typename Self::CoeffReturnType* data) {
EIGEN_STRONG_INLINE void operator()(Self& self, Index idx1, typename Self::CoeffReturnType* data) const {
using Packet = typename Self::PacketReturnType;
const int PacketSize = internal::unpacket_traits<Packet>::size;
Index idx2 = 0;
@@ -204,7 +204,7 @@ EIGEN_STRONG_INLINE Index AdjustBlockSize(Index item_size, Index block_size) {
template <typename Self>
struct ReduceBlock<Self, /*Vectorize=*/true, /*Parallel=*/true> {
EIGEN_STRONG_INLINE void operator()(Self& self, Index idx1, typename Self::CoeffReturnType* data) {
EIGEN_STRONG_INLINE void operator()(Self& self, Index idx1, typename Self::CoeffReturnType* data) const {
using Scalar = typename Self::CoeffReturnType;
using Packet = typename Self::PacketReturnType;
const int PacketSize = internal::unpacket_traits<Packet>::size;
@@ -243,7 +243,7 @@ struct ReduceBlock<Self, /*Vectorize=*/true, /*Parallel=*/true> {
template <typename Self>
struct ReduceBlock<Self, /*Vectorize=*/false, /*Parallel=*/true> {
EIGEN_STRONG_INLINE void operator()(Self& self, Index idx1, typename Self::CoeffReturnType* data) {
EIGEN_STRONG_INLINE void operator()(Self& self, Index idx1, typename Self::CoeffReturnType* data) const {
using Scalar = typename Self::CoeffReturnType;
self.device().parallelFor(
self.stride(), TensorOpCost(self.size(), self.size(), 16 * self.size()),
@@ -261,7 +261,7 @@ struct ReduceBlock<Self, /*Vectorize=*/false, /*Parallel=*/true> {
// Specialization for multi-threaded execution.
template <typename Self, typename Reducer, bool Vectorize>
struct ScanLauncher<Self, Reducer, ThreadPoolDevice, Vectorize> {
void operator()(Self& self, typename Self::CoeffReturnType* data) {
void operator()(Self& self, typename Self::CoeffReturnType* data) const {
using Scalar = typename Self::CoeffReturnType;
using Packet = typename Self::PacketReturnType;
const int PacketSize = internal::unpacket_traits<Packet>::size;
@@ -333,7 +333,7 @@ __global__ EIGEN_HIP_LAUNCH_BOUNDS_1024 void ScanKernel(Self self, Index total_s
template <typename Self, typename Reducer, bool Vectorize>
struct ScanLauncher<Self, Reducer, GpuDevice, Vectorize> {
void operator()(const Self& self, typename Self::CoeffReturnType* data) {
void operator()(const Self& self, typename Self::CoeffReturnType* data) const {
Index total_size = internal::array_prod(self.dimensions());
Index num_blocks = (total_size / self.size() + 63) / 64;
Index block_size = 64;