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-rw-r--r--unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h375
1 files changed, 343 insertions, 32 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h b/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h
index 647bcf108..ee44382cf 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h
@@ -31,6 +31,7 @@ struct traits<TensorPaddingOp<PaddingDimensions, XprType> > : public traits<XprT
typedef typename remove_reference<Nested>::type _Nested;
static const int NumDimensions = XprTraits::NumDimensions;
static const int Layout = XprTraits::Layout;
+ typedef typename XprTraits::PointerType PointerType;
};
template<typename PaddingDimensions, typename XprType>
@@ -90,18 +91,33 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
- static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+ static const int PacketSize = PacketType<CoeffReturnType, Device>::size;
+ typedef StorageMemory<CoeffReturnType, Device> Storage;
+ typedef typename Storage::Type EvaluatorPointerType;
enum {
- IsAligned = true,
- PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
- Layout = TensorEvaluator<ArgType, Device>::Layout,
- CoordAccess = true,
- RawAccess = false
+ IsAligned = true,
+ PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+ BlockAccess = TensorEvaluator<ArgType, Device>::RawAccess,
+ PreferBlockAccess = true,
+ Layout = TensorEvaluator<ArgType, Device>::Layout,
+ CoordAccess = true,
+ RawAccess = false
};
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
- : m_impl(op.expression(), device), m_padding(op.padding()), m_paddingValue(op.padding_value())
+ typedef typename internal::remove_const<Scalar>::type ScalarNoConst;
+
+ //===- Tensor block evaluation strategy (see TensorBlock.h) -------------===//
+ typedef internal::TensorBlockDescriptor<NumDims, Index> TensorBlockDesc;
+ typedef internal::TensorBlockScratchAllocator<Device> TensorBlockScratch;
+
+ typedef typename internal::TensorMaterializedBlock<ScalarNoConst, NumDims,
+ Layout, Index>
+ TensorBlock;
+ //===--------------------------------------------------------------------===//
+
+ EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+ : m_impl(op.expression(), device), m_padding(op.padding()), m_paddingValue(op.padding_value()), m_device(device)
{
// The padding op doesn't change the rank of the tensor. Directly padding a scalar would lead
// to a vector, which doesn't make sense. Instead one should reshape the scalar into a vector
@@ -135,11 +151,20 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
+ EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType) {
m_impl.evalSubExprsIfNeeded(NULL);
return true;
}
- EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+
+#ifdef EIGEN_USE_THREADS
+ template <typename EvalSubExprsCallback>
+ EIGEN_STRONG_INLINE void evalSubExprsIfNeededAsync(
+ EvaluatorPointerType, EvalSubExprsCallback done) {
+ m_impl.evalSubExprsIfNeededAsync(nullptr, [done](bool) { done(true); });
+ }
+#endif // EIGEN_USE_THREADS
+
+ EIGEN_STRONG_INLINE void cleanup() {
m_impl.cleanup();
}
@@ -148,6 +173,7 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
eigen_assert(index < dimensions().TotalSize());
Index inputIndex = 0;
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+ EIGEN_UNROLL_LOOP
for (int i = NumDims - 1; i > 0; --i) {
const Index idx = index / m_outputStrides[i];
if (isPaddingAtIndexForDim(idx, i)) {
@@ -161,6 +187,7 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
}
inputIndex += (index - m_padding[0].first);
} else {
+ EIGEN_UNROLL_LOOP
for (int i = 0; i < NumDims - 1; ++i) {
const Index idx = index / m_outputStrides[i+1];
if (isPaddingAtIndexForDim(idx, i)) {
@@ -189,18 +216,298 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
TensorOpCost cost = m_impl.costPerCoeff(vectorized);
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+ EIGEN_UNROLL_LOOP
for (int i = 0; i < NumDims; ++i)
updateCostPerDimension(cost, i, i == 0);
} else {
+ EIGEN_UNROLL_LOOP
for (int i = NumDims - 1; i >= 0; --i)
updateCostPerDimension(cost, i, i == NumDims - 1);
}
return cost;
}
- EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+ internal::TensorBlockResourceRequirements getResourceRequirements() const {
+ const size_t target_size = m_device.lastLevelCacheSize();
+ return internal::TensorBlockResourceRequirements::merge(
+ internal::TensorBlockResourceRequirements::skewed<Scalar>(target_size),
+ m_impl.getResourceRequirements());
+ }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBlock
+ block(TensorBlockDesc& desc, TensorBlockScratch& scratch,
+ bool /*root_of_expr_ast*/ = false) const {
+ // If one of the dimensions is zero, return empty block view.
+ if (desc.size() == 0) {
+ return TensorBlock(internal::TensorBlockKind::kView, NULL,
+ desc.dimensions());
+ }
+
+ static const bool IsColMajor = Layout == static_cast<int>(ColMajor);
+ const int inner_dim_idx = IsColMajor ? 0 : NumDims - 1;
+
+ Index offset = desc.offset();
+
+ // Compute offsets in the output tensor corresponding to the desc.offset().
+ DSizes<Index, NumDims> output_offsets;
+ for (int i = NumDims - 1; i > 0; --i) {
+ const int dim = IsColMajor ? i : NumDims - i - 1;
+ const int stride_dim = IsColMajor ? dim : dim + 1;
+ output_offsets[dim] = offset / m_outputStrides[stride_dim];
+ offset -= output_offsets[dim] * m_outputStrides[stride_dim];
+ }
+ output_offsets[inner_dim_idx] = offset;
+
+ // Offsets in the input corresponding to output offsets.
+ DSizes<Index, NumDims> input_offsets = output_offsets;
+ for (int i = 0; i < NumDims; ++i) {
+ const int dim = IsColMajor ? i : NumDims - i - 1;
+ input_offsets[dim] = input_offsets[dim] - m_padding[dim].first;
+ }
+
+ // Compute offset in the input buffer (at this point it might be illegal and
+ // point outside of the input buffer, because we don't check for negative
+ // offsets, it will be autocorrected in the block iteration loop below).
+ Index input_offset = 0;
+ for (int i = 0; i < NumDims; ++i) {
+ const int dim = IsColMajor ? i : NumDims - i - 1;
+ input_offset += input_offsets[dim] * m_inputStrides[dim];
+ }
+
+ // Destination buffer and scratch buffer both indexed from 0 and have the
+ // same dimensions as the requested block (for destination buffer this
+ // property is guaranteed by `desc.destination()`).
+ Index output_offset = 0;
+ const DSizes<Index, NumDims> output_strides =
+ internal::strides<Layout>(desc.dimensions());
+
+ // NOTE(ezhulenev): We initialize bock iteration state for `NumDims - 1`
+ // dimensions, skipping innermost dimension. In theory it should be possible
+ // to squeeze matching innermost dimensions, however in practice that did
+ // not show any improvements in benchmarks. Also in practice first outer
+ // dimension usually has padding, and will prevent squeezing.
+
+ // Initialize output block iterator state. Dimension in this array are
+ // always in inner_most -> outer_most order (col major layout).
+ array<BlockIteratorState, NumDims - 1> it;
+ for (int i = 0; i < NumDims - 1; ++i) {
+ const int dim = IsColMajor ? i + 1 : NumDims - i - 2;
+ it[i].count = 0;
+ it[i].size = desc.dimension(dim);
+
+ it[i].input_stride = m_inputStrides[dim];
+ it[i].input_span = it[i].input_stride * (it[i].size - 1);
+
+ it[i].output_stride = output_strides[dim];
+ it[i].output_span = it[i].output_stride * (it[i].size - 1);
+ }
+
+ const Index input_inner_dim_size =
+ static_cast<Index>(m_impl.dimensions()[inner_dim_idx]);
+
+ // Total output size.
+ const Index output_size = desc.size();
+
+ // We will fill inner dimension of this size in the output. It might be
+ // larger than the inner dimension in the input, so we might have to pad
+ // before/after we copy values from the input inner dimension.
+ const Index output_inner_dim_size = desc.dimension(inner_dim_idx);
+
+ // How many values to fill with padding BEFORE reading from the input inner
+ // dimension.
+ const Index output_inner_pad_before_size =
+ input_offsets[inner_dim_idx] < 0
+ ? numext::mini(numext::abs(input_offsets[inner_dim_idx]),
+ output_inner_dim_size)
+ : 0;
+
+ // How many values we can actually copy from the input inner dimension.
+ const Index output_inner_copy_size = numext::mini(
+ // Want to copy from input.
+ (output_inner_dim_size - output_inner_pad_before_size),
+ // Can copy from input.
+ numext::maxi(input_inner_dim_size - (input_offsets[inner_dim_idx] +
+ output_inner_pad_before_size),
+ Index(0)));
+
+ eigen_assert(output_inner_copy_size >= 0);
+
+ // How many values to fill with padding AFTER reading from the input inner
+ // dimension.
+ const Index output_inner_pad_after_size =
+ (output_inner_dim_size - output_inner_copy_size -
+ output_inner_pad_before_size);
+
+ // Sanity check, sum of all sizes must be equal to the output size.
+ eigen_assert(output_inner_dim_size ==
+ (output_inner_pad_before_size + output_inner_copy_size +
+ output_inner_pad_after_size));
+
+ // Keep track of current coordinates and padding in the output.
+ DSizes<Index, NumDims> output_coord = output_offsets;
+ DSizes<Index, NumDims> output_padded;
+ for (int i = 0; i < NumDims; ++i) {
+ const int dim = IsColMajor ? i : NumDims - i - 1;
+ output_padded[dim] = isPaddingAtIndexForDim(output_coord[dim], dim);
+ }
+
+ typedef internal::StridedLinearBufferCopy<ScalarNoConst, Index> LinCopy;
+
+ // Prepare storage for the materialized padding result.
+ const typename TensorBlock::Storage block_storage =
+ TensorBlock::prepareStorage(desc, scratch);
+
+ // TODO(ezhulenev): Squeeze multiple non-padded inner dimensions into a
+ // single logical inner dimension.
+
+ // When possible we squeeze writes for the innermost (only if non-padded)
+ // dimension with the first padded dimension. This allows to reduce the
+ // number of calls to LinCopy and better utilize vector instructions.
+ const bool squeeze_writes =
+ NumDims > 1 &&
+ // inner dimension is not padded
+ (input_inner_dim_size == m_dimensions[inner_dim_idx]) &&
+ // and equal to the block inner dimension
+ (input_inner_dim_size == output_inner_dim_size);
+
+ const int squeeze_dim = IsColMajor ? inner_dim_idx + 1 : inner_dim_idx - 1;
+
+ // Maximum coordinate on a squeeze dimension that we can write to.
+ const Index squeeze_max_coord =
+ squeeze_writes ? numext::mini(
+ // max non-padded element in the input
+ static_cast<Index>(m_dimensions[squeeze_dim] -
+ m_padding[squeeze_dim].second),
+ // max element in the output buffer
+ static_cast<Index>(output_offsets[squeeze_dim] +
+ desc.dimension(squeeze_dim)))
+ : static_cast<Index>(0);
+
+ // Iterate copying data from `m_impl.data()` to the output buffer.
+ for (Index size = 0; size < output_size;) {
+ // Detect if we are in the padded region (exclude innermost dimension).
+ bool is_padded = false;
+ for (int j = 1; j < NumDims; ++j) {
+ const int dim = IsColMajor ? j : NumDims - j - 1;
+ is_padded = output_padded[dim];
+ if (is_padded) break;
+ }
+
+ if (is_padded) {
+ // Fill single innermost dimension with padding value.
+ size += output_inner_dim_size;
+
+ LinCopy::template Run<LinCopy::Kind::FillLinear>(
+ typename LinCopy::Dst(output_offset, 1, block_storage.data()),
+ typename LinCopy::Src(0, 0, &m_paddingValue),
+ output_inner_dim_size);
+
+
+ } else if (squeeze_writes) {
+ // Squeeze multiple reads from innermost dimensions.
+ const Index squeeze_num = squeeze_max_coord - output_coord[squeeze_dim];
+ size += output_inner_dim_size * squeeze_num;
+
+ // Copy `squeeze_num` inner dimensions from input to output.
+ LinCopy::template Run<LinCopy::Kind::Linear>(
+ typename LinCopy::Dst(output_offset, 1, block_storage.data()),
+ typename LinCopy::Src(input_offset, 1, m_impl.data()),
+ output_inner_dim_size * squeeze_num);
+
+ // Update iteration state for only `squeeze_num - 1` processed inner
+ // dimensions, because we have another iteration state update at the end
+ // of the loop that will update iteration state for the last inner
+ // processed dimension.
+ it[0].count += (squeeze_num - 1);
+ input_offset += it[0].input_stride * (squeeze_num - 1);
+ output_offset += it[0].output_stride * (squeeze_num - 1);
+ output_coord[squeeze_dim] += (squeeze_num - 1);
+
+ } else {
+ // Single read from innermost dimension.
+ size += output_inner_dim_size;
+
+ { // Fill with padding before copying from input inner dimension.
+ const Index out = output_offset;
+
+ LinCopy::template Run<LinCopy::Kind::FillLinear>(
+ typename LinCopy::Dst(out, 1, block_storage.data()),
+ typename LinCopy::Src(0, 0, &m_paddingValue),
+ output_inner_pad_before_size);
+ }
+
+ { // Copy data from input inner dimension.
+ const Index out = output_offset + output_inner_pad_before_size;
+ const Index in = input_offset + output_inner_pad_before_size;
+
+ eigen_assert(output_inner_copy_size == 0 || m_impl.data() != NULL);
+
+ LinCopy::template Run<LinCopy::Kind::Linear>(
+ typename LinCopy::Dst(out, 1, block_storage.data()),
+ typename LinCopy::Src(in, 1, m_impl.data()),
+ output_inner_copy_size);
+ }
+
+ { // Fill with padding after copying from input inner dimension.
+ const Index out = output_offset + output_inner_pad_before_size +
+ output_inner_copy_size;
+
+ LinCopy::template Run<LinCopy::Kind::FillLinear>(
+ typename LinCopy::Dst(out, 1, block_storage.data()),
+ typename LinCopy::Src(0, 0, &m_paddingValue),
+ output_inner_pad_after_size);
+ }
+ }
+
+ for (int j = 0; j < NumDims - 1; ++j) {
+ const int dim = IsColMajor ? j + 1 : NumDims - j - 2;
+
+ if (++it[j].count < it[j].size) {
+ input_offset += it[j].input_stride;
+ output_offset += it[j].output_stride;
+ output_coord[dim] += 1;
+ output_padded[dim] = isPaddingAtIndexForDim(output_coord[dim], dim);
+ break;
+ }
+ it[j].count = 0;
+ input_offset -= it[j].input_span;
+ output_offset -= it[j].output_span;
+ output_coord[dim] -= it[j].size - 1;
+ output_padded[dim] = isPaddingAtIndexForDim(output_coord[dim], dim);
+ }
+ }
+
+ return block_storage.AsTensorMaterializedBlock();
+ }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EvaluatorPointerType data() const { return NULL; }
+
+#ifdef EIGEN_USE_SYCL
+ // binding placeholder accessors to a command group handler for SYCL
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void bind(cl::sycl::handler &cgh) const {
+ m_impl.bind(cgh);
+ }
+#endif
private:
+ struct BlockIteratorState {
+ BlockIteratorState()
+ : count(0),
+ size(0),
+ input_stride(0),
+ input_span(0),
+ output_stride(0),
+ output_span(0) {}
+
+ Index count;
+ Index size;
+ Index input_stride;
+ Index input_span;
+ Index output_stride;
+ Index output_span;
+ };
+
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isPaddingAtIndexForDim(
Index index, int dim_index) const {
#if defined(EIGEN_HAS_INDEX_LIST)
@@ -262,22 +569,23 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
const Index initialIndex = index;
Index inputIndex = 0;
+ EIGEN_UNROLL_LOOP
for (int i = NumDims - 1; i > 0; --i) {
- const Index first = index;
- const Index last = index + PacketSize - 1;
+ const Index firstIdx = index;
+ const Index lastIdx = index + PacketSize - 1;
const Index lastPaddedLeft = m_padding[i].first * m_outputStrides[i];
const Index firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i];
const Index lastPaddedRight = m_outputStrides[i+1];
- if (!isLeftPaddingCompileTimeZero(i) && last < lastPaddedLeft) {
+ if (!isLeftPaddingCompileTimeZero(i) && lastIdx < lastPaddedLeft) {
// all the coefficient are in the padding zone.
return internal::pset1<PacketReturnType>(m_paddingValue);
}
- else if (!isRightPaddingCompileTimeZero(i) && first >= firstPaddedRight && last < lastPaddedRight) {
+ else if (!isRightPaddingCompileTimeZero(i) && firstIdx >= firstPaddedRight && lastIdx < lastPaddedRight) {
// all the coefficient are in the padding zone.
return internal::pset1<PacketReturnType>(m_paddingValue);
}
- else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
+ else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (firstIdx >= lastPaddedLeft && lastIdx < firstPaddedRight)) {
// all the coefficient are between the 2 padding zones.
const Index idx = index / m_outputStrides[i];
inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
@@ -289,21 +597,21 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
}
}
- const Index last = index + PacketSize - 1;
- const Index first = index;
+ const Index lastIdx = index + PacketSize - 1;
+ const Index firstIdx = index;
const Index lastPaddedLeft = m_padding[0].first;
const Index firstPaddedRight = (m_dimensions[0] - m_padding[0].second);
const Index lastPaddedRight = m_outputStrides[1];
- if (!isLeftPaddingCompileTimeZero(0) && last < lastPaddedLeft) {
+ if (!isLeftPaddingCompileTimeZero(0) && lastIdx < lastPaddedLeft) {
// all the coefficient are in the padding zone.
return internal::pset1<PacketReturnType>(m_paddingValue);
}
- else if (!isRightPaddingCompileTimeZero(0) && first >= firstPaddedRight && last < lastPaddedRight) {
+ else if (!isRightPaddingCompileTimeZero(0) && firstIdx >= firstPaddedRight && lastIdx < lastPaddedRight) {
// all the coefficient are in the padding zone.
return internal::pset1<PacketReturnType>(m_paddingValue);
}
- else if ((isLeftPaddingCompileTimeZero(0) && isRightPaddingCompileTimeZero(0)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
+ else if ((isLeftPaddingCompileTimeZero(0) && isRightPaddingCompileTimeZero(0)) || (firstIdx >= lastPaddedLeft && lastIdx < firstPaddedRight)) {
// all the coefficient are between the 2 padding zones.
inputIndex += (index - m_padding[0].first);
return m_impl.template packet<Unaligned>(inputIndex);
@@ -319,23 +627,23 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
const Index initialIndex = index;
Index inputIndex = 0;
-
+ EIGEN_UNROLL_LOOP
for (int i = 0; i < NumDims - 1; ++i) {
- const Index first = index;
- const Index last = index + PacketSize - 1;
+ const Index firstIdx = index;
+ const Index lastIdx = index + PacketSize - 1;
const Index lastPaddedLeft = m_padding[i].first * m_outputStrides[i+1];
const Index firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i+1];
const Index lastPaddedRight = m_outputStrides[i];
- if (!isLeftPaddingCompileTimeZero(i) && last < lastPaddedLeft) {
+ if (!isLeftPaddingCompileTimeZero(i) && lastIdx < lastPaddedLeft) {
// all the coefficient are in the padding zone.
return internal::pset1<PacketReturnType>(m_paddingValue);
}
- else if (!isRightPaddingCompileTimeZero(i) && first >= firstPaddedRight && last < lastPaddedRight) {
+ else if (!isRightPaddingCompileTimeZero(i) && firstIdx >= firstPaddedRight && lastIdx < lastPaddedRight) {
// all the coefficient are in the padding zone.
return internal::pset1<PacketReturnType>(m_paddingValue);
}
- else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
+ else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (firstIdx >= lastPaddedLeft && lastIdx < firstPaddedRight)) {
// all the coefficient are between the 2 padding zones.
const Index idx = index / m_outputStrides[i+1];
inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
@@ -347,21 +655,21 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
}
}
- const Index last = index + PacketSize - 1;
- const Index first = index;
+ const Index lastIdx = index + PacketSize - 1;
+ const Index firstIdx = index;
const Index lastPaddedLeft = m_padding[NumDims-1].first;
const Index firstPaddedRight = (m_dimensions[NumDims-1] - m_padding[NumDims-1].second);
const Index lastPaddedRight = m_outputStrides[NumDims-1];
- if (!isLeftPaddingCompileTimeZero(NumDims-1) && last < lastPaddedLeft) {
+ if (!isLeftPaddingCompileTimeZero(NumDims-1) && lastIdx < lastPaddedLeft) {
// all the coefficient are in the padding zone.
return internal::pset1<PacketReturnType>(m_paddingValue);
}
- else if (!isRightPaddingCompileTimeZero(NumDims-1) && first >= firstPaddedRight && last < lastPaddedRight) {
+ else if (!isRightPaddingCompileTimeZero(NumDims-1) && firstIdx >= firstPaddedRight && lastIdx < lastPaddedRight) {
// all the coefficient are in the padding zone.
return internal::pset1<PacketReturnType>(m_paddingValue);
}
- else if ((isLeftPaddingCompileTimeZero(NumDims-1) && isRightPaddingCompileTimeZero(NumDims-1)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
+ else if ((isLeftPaddingCompileTimeZero(NumDims-1) && isRightPaddingCompileTimeZero(NumDims-1)) || (firstIdx >= lastPaddedLeft && lastIdx < firstPaddedRight)) {
// all the coefficient are between the 2 padding zones.
inputIndex += (index - m_padding[NumDims-1].first);
return m_impl.template packet<Unaligned>(inputIndex);
@@ -373,6 +681,7 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const
{
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+ EIGEN_UNROLL_LOOP
for (int i = 0; i < PacketSize; ++i) {
values[i] = coeff(index+i);
}
@@ -387,6 +696,8 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
PaddingDimensions m_padding;
Scalar m_paddingValue;
+
+ const Device EIGEN_DEVICE_REF m_device;
};
generated by cgit v1.2.3 (git 2.25.1) at 2024-05-25 14:48:18 +0000