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Add Transpose function (#91)

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* Add Transpose function

* csrcs->csrc

* Add transpose unittest

* Add reduce_max_large_dim unittest
This commit is contained in:
Jack Zhou
2022-08-10 19:00:16 +08:00
committed by GitHub
parent bf5affb510
commit 7fb8dd7916
9 changed files with 298 additions and 13 deletions
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36
csrc/fastdeploy/function/reduce.cc
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@@ -12,11 +12,13 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "fastdeploy/function/reduce.h"
#include <set>
#include "fastdeploy/function/eigen.h"
#include "fastdeploy/function/reduce.h"
#include "fastdeploy/function/reduce_functor.h"
#include "fastdeploy/function/transpose.h"
#include "fastdeploy/utils/utils.h"
namespace fastdeploy {
@@ -71,7 +73,7 @@ void ReduceFunctor(const FDTensor& input, FDTensor* output,
inline void GetShuffledDim(const std::vector<int64_t>& src_dims,
std::vector<int64_t>* dst_dims,
const std::vector<int64_t>& reduced_dims,
std::vector<int>* perm_axis) {
std::vector<int64_t>* perm_axis) {
// check if it's a reduced dim
std::vector<bool> src_dims_check(src_dims.size(), false);
size_t src_size = src_dims.size();
@@ -104,19 +106,33 @@ template <typename OutT>
void GetShuffledInput(const FDTensor& input, FDTensor* shuffled_input,
const std::vector<int64_t>& dims) {
auto shuffled_dims = input.shape;
std::vector<int> perm_axis(input.shape.size());
std::vector<int64_t> perm_axis(input.shape.size());
GetShuffledDim(input.shape, &shuffled_dims, dims, &perm_axis);
shuffled_input->Allocate(shuffled_dims, input.dtype);
// TODO(zhoushunjie) : Need to implement trans function
// phi::funcs::TransposeNormal<DeviceContext, OutT> trans;
// trans(dev_ctx, input, shuffled_input, perm_axis);
Transpose(input, shuffled_input, perm_axis);
}
//////////////// HandleLargeDim
template <typename OutT, typename Functor>
void HandleLargeDim(const FDTensor& input, FDTensor* output,
const std::vector<int64_t>& dims, bool keep_dim) {
auto out_dims = input.shape;
std::vector<int64_t> dims_ref = dims;
auto x_rank = input.shape.size();
for (size_t i = 0; i < dims_ref.size(); ++i) {
if (dims_ref[i] < 0) dims_ref[i] = x_rank + dims_ref[i];
out_dims[dims_ref[i]] = 1;
}
if (!keep_dim) {
const int kDelFlag = -2;
for (size_t i = 0; i < dims_ref.size(); ++i) {
out_dims[dims_ref[i]] = kDelFlag;
}
out_dims.erase(remove(out_dims.begin(), out_dims.end(), kDelFlag),
out_dims.end());
}
output->Allocate(out_dims, TypeToDataType<OutT>::dtype);
// shuffle the reduced dim to the end
FDTensor shuffled_input;
GetShuffledInput<OutT>(input, &shuffled_input, dims);
@@ -126,11 +142,9 @@ void HandleLargeDim(const FDTensor& input, FDTensor* output,
const int64_t reduced = shuffled_input.Numel() / unreduced;
shuffled_input.Allocate({unreduced, reduced}, TypeToDataType<OutT>::dtype);
auto output_dim = output->shape;
output->Allocate({unreduced}, TypeToDataType<OutT>::dtype);
output->shape = {unreduced};
ReduceFunctor<OutT, 2, 1, Functor>(shuffled_input, output, {1}, keep_dim);
output->shape = output_dim;
output->shape = out_dims;
}
////////////// ReduceKernel
@@ -152,7 +166,7 @@ void ReduceKernelImpl(const FDTensor& input, FDTensor* output,
} else {
int ndim = input.shape.size();
int rdim = dims.size();
if (ndim > 3) {
if (ndim > 4) {
HandleLargeDim<OutT, Functor>(input, output, dims, keep_dim);
} else {
HANDLE_REDUCE_DIM(4, 3);