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Remove V2 suffix from TensorBlock

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This commit is contained in:
Eugene Zhulenev
2019-12-10 15:40:23 -08:00
parent dbca11e880
commit 1c879eb010
37 changed files with 341 additions and 341 deletions
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50
unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
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@@ -114,7 +114,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
enum {
IsAligned = true,
PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
BlockAccessV2 = TensorEvaluator<ArgType, Device>::BlockAccessV2,
BlockAccess = TensorEvaluator<ArgType, Device>::BlockAccess,
PreferBlockAccess = true,
Layout = TensorEvaluator<ArgType, Device>::Layout,
RawAccess = false
@@ -130,12 +130,12 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
typedef internal::TensorBlockDescriptor<NumDims, Index> TensorBlockDesc;
typedef internal::TensorBlockScratchAllocator<Device> TensorBlockScratch;
typedef typename TensorEvaluator<const ArgType, Device>::TensorBlockV2
typedef typename TensorEvaluator<const ArgType, Device>::TensorBlock
ArgTensorBlock;
typedef typename internal::TensorMaterializedBlock<ScalarNoConst, NumDims,
Layout, Index>
TensorBlockV2;
TensorBlock;
//===--------------------------------------------------------------------===//
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
@@ -617,19 +617,19 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
internal::TensorBlockV2ResourceRequirements getResourceRequirements() const {
internal::TensorBlockResourceRequirements getResourceRequirements() const {
// TODO(wuke): Targeting L1 size is 30% faster than targeting L{-1} on large
// tensors. But this might need further tuning.
const size_t target_block_size = numext::maxi<size_t>(
1, m_device.firstLevelCacheSize() / sizeof(Scalar));
return internal::TensorBlockV2ResourceRequirements::merge(
{internal::TensorBlockV2ShapeType::kSkewedInnerDims, target_block_size},
return internal::TensorBlockResourceRequirements::merge(
{internal::TensorBlockShapeType::kSkewedInnerDims, target_block_size},
m_impl.getResourceRequirements());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBlockV2
blockV2(TensorBlockDesc& desc, TensorBlockScratch& scratch,
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBlock
block(TensorBlockDesc& desc, TensorBlockScratch& scratch,
bool /*root_of_expr_ast*/ = false) const {
BlockBroadcastingParams params = blockBroadcastingParams(desc);
@@ -638,8 +638,8 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
}
// Prepare storage for the materialized broadcasting result.
const typename TensorBlockV2::Storage block_storage =
TensorBlockV2::prepareStorage(desc, scratch);
const typename TensorBlock::Storage block_storage =
TensorBlock::prepareStorage(desc, scratch);
ScalarNoConst* materialized_output = block_storage.data();
// We potentially will need to materialize input blocks.
@@ -843,10 +843,10 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
return params;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBlockV2 emptyBlock() const {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBlock emptyBlock() const {
DSizes<Index, NumDims> dimensions;
for (int i = 0; i < NumDims; ++i) dimensions[i] = 0;
return TensorBlockV2(internal::TensorBlockKind::kView, NULL, dimensions);
return TensorBlock(internal::TensorBlockKind::kView, NULL, dimensions);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index BroadcastBlockAlongBcastDim(
@@ -856,7 +856,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
size_t* materialized_input_size) const {
if (params.bcast_dim_size == 1) {
// We just need one block read using the ready-set values above.
return BroadcastBlockV2(
return BroadcastBlock(
params.input_block_sizes, params.input_block_strides,
params.bcast_block_sizes, params.bcast_block_strides,
params.bcast_input_strides, bcast_offset, 0, scratch,
@@ -873,7 +873,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
params.bcast_block_strides[broadcast_bcast_dim] =
params.output_strides[params.bcast_dim];
return BroadcastBlockV2(
return BroadcastBlock(
params.input_block_sizes, params.input_block_strides,
params.bcast_block_sizes, params.bcast_block_strides,
params.bcast_input_strides, bcast_offset, 0, scratch,
@@ -942,7 +942,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
params.output_strides[params.bcast_dim] *
params.input_dims[params.bcast_dim];
num_output_coeffs += BroadcastBlockV2(
num_output_coeffs += BroadcastBlock(
params.input_block_sizes, params.input_block_strides,
params.bcast_block_sizes, params.bcast_block_strides,
params.bcast_input_strides, bcast_offset, 0, scratch,
@@ -964,7 +964,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
const Index offset = (first_multiple - bcast_dim_left_index) *
m_outputStrides[params.bcast_dim];
num_output_coeffs += BroadcastBlockV2(
num_output_coeffs += BroadcastBlock(
params.input_block_sizes, params.input_block_strides,
params.bcast_block_sizes, params.bcast_block_strides,
params.bcast_input_strides, bcast_offset, offset, scratch,
@@ -987,7 +987,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
const Index offset = (last_multiple - bcast_dim_left_index) *
m_outputStrides[params.bcast_dim];
num_output_coeffs += BroadcastBlockV2(
num_output_coeffs += BroadcastBlock(
params.input_block_sizes, params.input_block_strides,
params.bcast_block_sizes, params.bcast_block_strides,
params.bcast_input_strides, bcast_offset, offset, scratch,
@@ -1005,7 +1005,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
params.bcast_block_strides[copy_bcast_dim] =
params.output_strides[params.bcast_dim];
num_output_coeffs += BroadcastBlockV2(
num_output_coeffs += BroadcastBlock(
params.input_block_sizes, params.input_block_strides,
params.bcast_block_sizes, params.bcast_block_strides,
params.bcast_input_strides, bcast_offset, 0, scratch,
@@ -1016,7 +1016,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
}
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index BroadcastBlockV2(
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index BroadcastBlock(
const Dimensions& input_block_sizes,
const Dimensions& input_block_strides,
const BroadcastDimensions& bcast_block_sizes,
@@ -1032,7 +1032,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
IsColMajor ? indexColMajor(input_offset) : indexRowMajor(input_offset),
input_block_sizes);
ArgTensorBlock input_block = m_impl.blockV2(input_desc, scratch);
ArgTensorBlock input_block = m_impl.block(input_desc, scratch);
// ---------------------------------------------------------------------- //
// Materialize input block into a temporary memory buffer only if it's not
@@ -1071,14 +1071,14 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
// ---------------------------------------------------------------------- //
// Copy data from materialized input block to the materialized output, using
// given broadcast strides (strides with zeroes).
typedef internal::TensorBlockIOV2<ScalarNoConst, Index, 2 * NumDims, Layout>
TensorBlockIOV2;
typedef internal::TensorBlockIO<ScalarNoConst, Index, 2 * NumDims, Layout>
TensorBlockIO;
typename TensorBlockIOV2::Src src(bcast_input_strides, input_buffer);
typename TensorBlockIOV2::Dst dst(bcast_block_sizes, bcast_block_strides,
typename TensorBlockIO::Src src(bcast_input_strides, input_buffer);
typename TensorBlockIO::Dst dst(bcast_block_sizes, bcast_block_strides,
materialized_output + offset);
return TensorBlockIOV2::Copy(dst, src);
return TensorBlockIO::Copy(dst, src);
}
protected: