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Revert "Improves performance of operator Transpose (#5550)" (#5911)

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This reverts commit e5c8040c52.
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Changming Sun 2020-11-24 00:01:03 -08:00 committed by GitHub
parent 9992f0f812
commit 782303324e
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2 changed files with 92 additions and 163 deletions
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222
onnxruntime/core/providers/cpu/tensor/transpose.cc
View file

@ -15,65 +15,23 @@ namespace onnxruntime {
etc.
*/
typedef struct MultiIndex {
size_t index;
size_t upper_bound;
int64_t stride;
MultiIndex() {}
MultiIndex(size_t i, size_t n, int64_t s) {
index = i;
upper_bound = n;
stride = s;
// ComputeOffset: compute offset into a tensor. This is essentially the dot-product of
// index and stride, restricted to the specified number of axes.
static inline size_t ComputeOffset(const std::vector<int64_t>& index, const std::vector<size_t>& stride, int64_t num_axes) {
size_t offset = 0;
for (int64_t j = 0; j < num_axes; ++j) {
offset += index[j] * stride[j];
}
} MultiIndex;
static size_t IncrementIndexAndComputeOffsetSetup(MultiIndex* mindex, int64_t num_axes, const std::vector<int64_t>& target_dims,
const std::vector<size_t>& stride, size_t element_size) {
size_t naxes = 0;
for (int64_t i = 0; i < num_axes; ++i) {
if (target_dims[i] == 1)
continue;
mindex[naxes] = MultiIndex(0, static_cast<size_t>(target_dims[i]), stride[i] * element_size);
++naxes;
}
return naxes;
return offset;
}
// Combines multi-index increment and corresponding pointer in the tensor to transpose.
static void IncrementIndexAndComputeOffset(MultiIndex* mindex, size_t naxes, const uint8_t*& local_source) {
MultiIndex* it = mindex + (naxes - 1);
local_source += it->stride;
if (++it->index < it->upper_bound)
return;
local_source -= it->stride * it->index;
it->index = 0;
--it;
MultiIndex* rend = mindex - 1;
for (; it != rend; --it) {
local_source += it->stride;
if (++it->index < it->upper_bound)
break;
local_source -= it->stride * it->index;
it->index = 0;
}
}
// Combines multi-index increment and corresponding pointer in the string tensor to transpose.
static void IncrementIndexAndComputeOffset(MultiIndex* mindex, size_t naxes, const std::string*& local_source) {
MultiIndex* it = mindex + (naxes - 1);
local_source += it->stride;
if (++it->index < it->upper_bound)
return;
local_source -= it->stride * it->index;
it->index = 0;
--it;
MultiIndex* rend = mindex - 1;
for (; it != rend; --it) {
local_source += it->stride;
if (++it->index < it->upper_bound)
break;
local_source -= it->stride * it->index;
it->index = 0;
// IncrementIndex: Increment an index into a tensor (in lexicographic ordering), wrapping
// around the specified upper_bound.
static inline void IncrementIndex(std::vector<int64_t>& index, const std::vector<int64_t>& upper_bound, int64_t num_axes) {
for (int64_t k = num_axes - 1; k >= 0; --k) {
index[k]++;
if (index[k] < upper_bound[k]) break;
index[k] = 0;
}
}
@ -97,13 +55,17 @@ static void DoTransposeImpl(int64_t num_axes, const std::vector<int64_t>& target
size_t num_blocks, size_t num_elts_in_block, const std::vector<size_t>& stride,
const uint8_t* source, uint8_t* target, size_t element_size) {
size_t blocksize = num_elts_in_block * element_size;
std::vector<MultiIndex> mindex(num_axes);
size_t naxes = IncrementIndexAndComputeOffsetSetup(mindex.data(), num_axes, target_dims, stride, element_size);
const uint8_t* local_source = source;
// index used to iterate over target iteration-space
std::vector<int64_t> target_index(num_axes, 0);
for (size_t i = 0; i < num_blocks; ++i) {
memcpy(target, local_source, blocksize);
IncrementIndexAndComputeOffset(mindex.data(), naxes, local_source);
// convert target_index into an offset in source data
size_t source_offset = ComputeOffset(target_index, stride, num_axes);
// copy
memcpy(target, source + source_offset * element_size, blocksize);
// increment target_index:
IncrementIndex(target_index, target_dims, num_axes);
target += blocksize;
}
}
@ -111,14 +73,17 @@ static void DoTransposeImpl(int64_t num_axes, const std::vector<int64_t>& target
static void DoTransposeImpl(int64_t num_axes, const std::vector<int64_t>& target_dims,
size_t num_blocks, size_t num_elts_in_block, const std::vector<size_t>& stride,
const std::string* source, std::string* target) {
ORT_ENFORCE(num_axes > 0, "Transpose not implemented for empty tensors.");
std::vector<MultiIndex> mindex(num_axes);
size_t naxes = IncrementIndexAndComputeOffsetSetup(mindex.data(), num_axes, target_dims, stride, 1);
const std::string* local_source = source;
// index used to iterate over target iteration-space
std::vector<int64_t> target_index(num_axes, 0);
for (size_t i = 0; i < num_blocks; ++i) {
DoTransposeSingleBlock(num_elts_in_block, local_source, target);
IncrementIndexAndComputeOffset(mindex.data(), naxes, local_source);
// convert target_index into an offset in source data
size_t source_offset = ComputeOffset(target_index, stride, num_axes);
// copy
DoTransposeSingleBlock(num_elts_in_block, source + source_offset, target);
// increment target_index:
IncrementIndex(target_index, target_dims, num_axes);
target += num_elts_in_block;
}
}
@ -128,39 +93,67 @@ inline void CopyPrim(uint8_t* target, const uint8_t* source) {
*reinterpret_cast<T*>(target) = *reinterpret_cast<const T*>(source);
}
// The function does not check num_axes > 0 but this is expected.
template <class T>
static void TypedDoTransposeEltWise(int64_t num_axes, const std::vector<int64_t>& target_dims, size_t num_blocks,
const std::vector<size_t>& stride, const uint8_t* source, uint8_t* target) {
std::vector<MultiIndex> mindex(num_axes);
size_t naxes = IncrementIndexAndComputeOffsetSetup(mindex.data(), num_axes, target_dims, stride, sizeof(T));
const uint8_t* local_source = source;
for (size_t i = 0; i < num_blocks; ++i) {
CopyPrim<uint64_t>(target, local_source);
IncrementIndexAndComputeOffset(mindex.data(), naxes, local_source);
target += sizeof(T);
}
}
// DoTransposeEltWise: specialization of DoTranspose for the num_elts_in_block=1 case.
// copies source tensor to target, transposing elements.
// The stride vector indicates the transposition.
static void DoTransposeEltWise(int64_t num_axes, const std::vector<int64_t>& target_dims, size_t num_blocks,
const std::vector<size_t>& stride, const uint8_t* source, uint8_t* target,
size_t element_size) {
// index used to iterate over target iteration-space
std::vector<int64_t> target_index(num_axes, 0);
switch (element_size) {
case sizeof(uint64_t):
TypedDoTransposeEltWise<uint64_t>(num_axes, target_dims, num_blocks, stride, source, target);
for (size_t i = 0; i < num_blocks; ++i) {
// convert target_index into an offset in source data
size_t source_offset = ComputeOffset(target_index, stride, num_axes);
// copy
CopyPrim<uint64_t>(target, source + (source_offset * element_size));
// increment target_index:
IncrementIndex(target_index, target_dims, num_axes);
target += element_size;
}
break;
case sizeof(uint32_t):
TypedDoTransposeEltWise<uint32_t>(num_axes, target_dims, num_blocks, stride, source, target);
for (size_t i = 0; i < num_blocks; ++i) {
// convert target_index into an offset in source data
size_t source_offset = ComputeOffset(target_index, stride, num_axes);
// copy
CopyPrim<uint32_t>(target, source + (source_offset * element_size));
// increment target_index:
IncrementIndex(target_index, target_dims, num_axes);
target += element_size;
}
break;
case sizeof(uint16_t):
TypedDoTransposeEltWise<uint16_t>(num_axes, target_dims, num_blocks, stride, source, target);
for (size_t i = 0; i < num_blocks; ++i) {
// convert target_index into an offset in source data
size_t source_offset = ComputeOffset(target_index, stride, num_axes);
// copy
CopyPrim<uint16_t>(target, source + (source_offset * element_size));
// increment target_index:
IncrementIndex(target_index, target_dims, num_axes);
target += element_size;
}
break;
case sizeof(uint8_t):
TypedDoTransposeEltWise<uint8_t>(num_axes, target_dims, num_blocks, stride, source, target);
for (size_t i = 0; i < num_blocks; ++i) {
// convert target_index into an offset in source data
size_t source_offset = ComputeOffset(target_index, stride, num_axes);
// copy
*target = *(source + (source_offset * element_size));
// increment target_index:
IncrementIndex(target_index, target_dims, num_axes);
target += element_size;
}
break;
default:
assert(false);
@ -169,15 +162,17 @@ static void DoTransposeEltWise(int64_t num_axes, const std::vector<int64_t>& tar
static void DoTransposeEltWise(int64_t num_axes, const std::vector<int64_t>& target_dims, size_t num_blocks,
const std::vector<size_t>& stride, const std::string* source, std::string* target) {
ORT_ENFORCE(num_axes > 0, "Transpose not implemented for empty tensors.");
std::vector<MultiIndex> mindex(num_axes);
size_t naxes = IncrementIndexAndComputeOffsetSetup(mindex.data(), num_axes, target_dims, stride, 1);
// index used to iterate over target iteration-space
const std::string* local_source = source;
std::vector<int64_t> target_index(num_axes, 0);
for (size_t i = 0; i < num_blocks; ++i) {
*target = *local_source;
IncrementIndexAndComputeOffset(mindex.data(), naxes, local_source);
// convert target_index into an offset in source data
size_t source_offset = ComputeOffset(target_index, stride, num_axes);
// copy
*target = *(source + source_offset);
// increment target_index:
IncrementIndex(target_index, target_dims, num_axes);
target++;
}
}
@ -279,15 +274,13 @@ template <typename T>
static void SimpleTransposeSingleAxisOutwards(const T* input_data, T* output_data,
int64_t num_loops, int64_t num_writers,
int64_t writes_per_loop, int64_t writes_per_writer_per_loop) {
const T* end;
for (int64_t l = 0; l < num_loops; ++l) {
T* output_for_first_writer = output_data;
for (auto wwpl = 0; wwpl < writes_per_writer_per_loop; ++wwpl) {
T* output_for_current_writer = output_for_first_writer;
end = input_data + num_writers;
for (; input_data != end;) {
for (int64_t w = 0; w < num_writers; ++w) {
*output_for_current_writer = *input_data++;
// skip to output position for next writer
@ -386,15 +379,13 @@ template <typename T>
static void SimpleTransposeSingleAxisInwards(const T* input_data, T* output_data,
int64_t num_loops, int64_t num_readers,
int64_t reads_per_loop, int64_t reads_per_reader_per_loop) {
T* end;
for (int64_t l = 0; l < num_loops; ++l) {
const T* input_for_first_reader = input_data;
for (auto rrpl = 0; rrpl < reads_per_reader_per_loop; ++rrpl) {
const T* input_for_current_reader = input_for_first_reader;
end = output_data + num_readers;
for (; output_data != end;) {
for (int64_t r = 0; r < num_readers; ++r) {
*output_data++ = *input_for_current_reader;
// skip to input position for next reader
input_for_current_reader += reads_per_reader_per_loop;
@ -569,20 +560,6 @@ static bool IsMovingSingleAxis(const std::vector<size_t>& permutations, size_t&
return single_axis_moved;
}
bool IsReshape(const std::vector<size_t>& perm, const std::vector<int64_t>& input_dims) {
// As long as the dims with values > 1 stay in the same order, it's a reshape.
// Example: Shape=(1,1,1024,4096) -> perm=(2,0,3,1).
size_t last_permuted_axis = 0;
for (size_t i = 0; i < perm.size(); ++i) {
if (input_dims[perm[i]] == 1)
continue;
if (perm[i] < last_permuted_axis)
return false;
last_permuted_axis = perm[i];
}
return true;
}
//`input_shape_override` overrides the shape of `input` for compute purposes.
Status TransposeBase::DoTranspose(const std::vector<size_t>& permutations, const Tensor& input, Tensor& output,
const TensorShape* input_shape_override) {
@ -595,14 +572,6 @@ Status TransposeBase::DoTranspose(const std::vector<size_t>& permutations, const
status = ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Mismatched data types between input and output Tensors. ",
input_type, " != ", output_type);
} else {
TensorShape shape = input_shape_override ? *input_shape_override : input.Shape();
if (IsReshape(permutations, shape.GetDims())) {
// As long as the dims with values > 1 stay in the same order, it's a reshape.
// Example: Shape=(1,1,1024,4096) -> perm=(2,0,3,1).
CopyCpuTensor(&input, &output);
return Status::OK();
}
size_t from = 0, to = 0;
bool moving_single_axis = IsMovingSingleAxis(permutations, from, to);
@ -638,13 +607,6 @@ Status Transpose::Compute(OpKernelContext* ctx) const {
if (output_shape.Size() == 0)
return Status::OK();
if (IsReshape(*p_perm, input_dims)) {
// As long as the dims with values > 1 stay in the same order, it's a reshape.
// Example: Shape=(1,1,1024,4096) -> perm=(2,0,3,1).
CopyCpuTensor(&X, &Y);
return Status::OK();
}
size_t from = 0, to = 0;
bool moving_single_axis = IsMovingSingleAxis(*p_perm, from, to);

33
onnxruntime/test/providers/cpu/tensor/transpose_test.cc
View file

@ -246,39 +246,6 @@ TEST(TransposeOpTest, ThreeDimSuffix) {
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false); //TensorRT: illegal error
}
TEST(TransposeOpTest, TransposeReshape) {
std::vector<int64_t> input_shape({1, 4, 2, 1, 3});
std::vector<float> input_vals = {
1.0f, 2.0f, 3.0f,
4.0f, 5.0f, 6.0f,
1.1f, 2.1f, 3.1f,
4.1f, 5.1f, 6.1f,
1.2f, 2.2f, 3.2f,
4.2f, 5.2f, 6.2f,
1.3f, 2.3f, 3.3f,
4.3f, 5.3f, 6.3f};
std::vector<int64_t> perm = {1, 3, 2, 4, 0};
std::vector<int64_t> expected_shape({4, 1, 2, 3, 1});
auto expected_vals = {
1.0f, 2.0f, 3.0f,
4.0f, 5.0f, 6.0f,
1.1f, 2.1f, 3.1f,
4.1f, 5.1f, 6.1f,
1.2f, 2.2f, 3.2f,
4.2f, 5.2f, 6.2f,
1.3f, 2.3f, 3.3f,
4.3f, 5.3f, 6.3f};
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false); //TensorRT: illegal error
}
TEST(TransposeOpTest, ThreeDimStr) {
std::vector<int64_t> input_shape({4, 2, 3});
std::vector<std::string> input_vals = {