Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

add kernel register #5511

Merged
merged 3 commits into from
Feb 24, 2021
Merged

add kernel register #5511

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
509cf5d
[HOST][X86] fix equal_int64; cast support bool, int32; slice support …
zhupengyang Feb 19, 2021
2f42063
test=develop
zhupengyang Feb 22, 2021
724074c
Merge branch 'develop' into scs
zhupengyang Feb 23, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
18 changes: 18 additions & 0 deletions lite/kernels/host/compare_compute.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -147,6 +147,24 @@ REGISTER_LITE_KERNEL(equal, kHost, kInt64, kAny, equal_int64, def)
.BindPaddleOpVersion("equal", 1)
.Finalize();

// float kernel has higher score when picking kernel.
// TODO(zhupengyang): merge equal_int64 later
using equal_int64_f = paddle::lite::kernels::host::CompareCompute<
PRECISION(kFloat),
paddle::lite::kernels::host::_EqualFunctor<int64_t>>;
REGISTER_LITE_KERNEL(equal, kHost, kFloat, kAny, equal_int64_f, int64)
.BindInput("X",
{LiteType::GetTensorTy(
TARGET(kHost), PRECISION(kInt64), DATALAYOUT(kAny), -1)})
.BindInput("Y",
{LiteType::GetTensorTy(
TARGET(kHost), PRECISION(kInt64), DATALAYOUT(kAny), -1)})
.BindOutput("Out",
{LiteType::GetTensorTy(
TARGET(kHost), PRECISION(kBool), DATALAYOUT(kAny), -1)})
.BindPaddleOpVersion("equal", 1)
.Finalize();

using equal_int32 = paddle::lite::kernels::host::CompareCompute<
PRECISION(kInt32),
paddle::lite::kernels::host::_EqualFunctor<int32_t>>;
Expand Down
22 changes: 22 additions & 0 deletions lite/kernels/host/range_compute.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -100,3 +100,25 @@ REGISTER_LITE_KERNEL(range, kHost, kInt32, kAny, range_int32, def)
PRECISION(kInt32),
DATALAYOUT(kAny))})
.Finalize();

// float kernel has higher score when picking kernel.
using range_int32_f =
paddle::lite::kernels::host::RangeCompute<int, PRECISION(kFloat)>;
REGISTER_LITE_KERNEL(range, kHost, kFloat, kAny, range_int32_f, int32)
.BindInput("Start",
{LiteType::GetTensorTy(TARGET(kHost),
PRECISION(kInt32),
DATALAYOUT(kAny))})
.BindInput("End",
{LiteType::GetTensorTy(TARGET(kHost),
PRECISION(kInt32),
DATALAYOUT(kAny))})
.BindInput("Step",
{LiteType::GetTensorTy(TARGET(kHost),
PRECISION(kInt32),
DATALAYOUT(kAny))})
.BindOutput("Out",
{LiteType::GetTensorTy(TARGET(kHost),
PRECISION(kInt32),
DATALAYOUT(kAny))})
.Finalize();
20 changes: 20 additions & 0 deletions lite/kernels/x86/cast_compute.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -34,3 +34,23 @@ REGISTER_LITE_KERNEL(
.BindInput("X", {LiteType::GetTensorTy(TARGET(kX86), PRECISION(kFP16))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kX86))})
.Finalize();

REGISTER_LITE_KERNEL(cast,
kX86,
kFloat,
kNCHW,
paddle::lite::kernels::x86::CastCompute<bool>,
bool_to_any)
.BindInput("X", {LiteType::GetTensorTy(TARGET(kX86), PRECISION(kBool))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kX86), PRECISION(kAny))})
.Finalize();

REGISTER_LITE_KERNEL(cast,
kX86,
kFloat,
kNCHW,
paddle::lite::kernels::x86::CastCompute<int>,
int32_to_any)
.BindInput("X", {LiteType::GetTensorTy(TARGET(kX86), PRECISION(kInt32))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kX86), PRECISION(kAny))})
.Finalize();
15 changes: 15 additions & 0 deletions lite/kernels/x86/slice_compute.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -27,3 +27,18 @@ REGISTER_LITE_KERNEL(slice,
.BindInput("EndsTensorList", {LiteType::GetTensorTy(TARGET(kX86))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kX86))})
.Finalize();

REGISTER_LITE_KERNEL(slice,
kX86,
kFloat,
kNCHW,
paddle::lite::kernels::x86::SliceCompute<int>,
int32)
.BindInput("Input",
{LiteType::GetTensorTy(TARGET(kX86), PRECISION(kInt32))})
.BindInput("StartsTensor", {LiteType::GetTensorTy(TARGET(kX86))})
.BindInput("EndsTensor", {LiteType::GetTensorTy(TARGET(kX86))})
.BindInput("StartsTensorList", {LiteType::GetTensorTy(TARGET(kX86))})
.BindInput("EndsTensorList", {LiteType::GetTensorTy(TARGET(kX86))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kX86), PRECISION(kInt32))})
.Finalize();
80 changes: 59 additions & 21 deletions lite/kernels/xpu/reshape_compute.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include "lite/kernels/xpu/reshape_compute.h"
#include <algorithm>
#include "lite/backends/xpu/xpu_header_sitter.h"
Expand All @@ -21,9 +22,10 @@ namespace lite {
namespace kernels {
namespace xpu {

void ReshapeCompute::Run() {
auto& param = this->Param<param_t>();
auto& ctx = this->ctx_->As<XPUContext>();
template <class T>
void ReshapeCompute<T>::Run() {
auto& param = this->template Param<param_t>();
auto& ctx = this->ctx_->template As<XPUContext>();
auto x = param.x;
auto output = param.output;
auto output_dims = output->dims();
Expand All @@ -32,10 +34,10 @@ void ReshapeCompute::Run() {
output->ShareDataWith(*x);
output->Resize(output_dims);
} else {
int r = xdnn::copy<float>(ctx.GetRawContext(),
param.x->data<float>(),
param.output->mutable_data<float>(TARGET(kXPU)),
param.x->numel());
int r = xdnn::copy<T>(ctx.GetRawContext(),
x->template data<T>(),
output->template mutable_data<T>(TARGET(kXPU)),
x->numel());

CHECK_EQ(r, 0);
}
Expand All @@ -50,46 +52,82 @@ REGISTER_LITE_KERNEL(reshape2,
kXPU,
kFloat,
kNCHW,
paddle::lite::kernels::xpu::ReshapeCompute,
def)
paddle::lite::kernels::xpu::ReshapeCompute<float>,
float32)
.BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU))})
.BindInput("ShapeTensor", {LiteType::GetTensorTy(TARGET(kHost))})
.BindInput("Shape", {LiteType::GetTensorTy(TARGET(kHost))})
.BindInput("ShapeTensor",
{LiteType::GetTensorTy(TARGET(kHost), PRECISION(kInt32))})
.BindInput("Shape",
{LiteType::GetTensorTy(TARGET(kHost), PRECISION(kInt32))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU))})
.BindOutput("XShape", {LiteType::GetTensorTy(TARGET(kHost))})
.Finalize();

REGISTER_LITE_KERNEL(reshape2,
kXPU,
kFloat,
kNCHW,
paddle::lite::kernels::xpu::ReshapeCompute<int>,
int32)
.BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU), PRECISION(kInt32))})
.BindInput("ShapeTensor",
{LiteType::GetTensorTy(TARGET(kHost), PRECISION(kInt32))})
.BindInput("Shape",
{LiteType::GetTensorTy(TARGET(kHost), PRECISION(kInt32))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU), PRECISION(kInt32))})
.BindOutput("XShape", {LiteType::GetTensorTy(TARGET(kHost))})
.Finalize();

REGISTER_LITE_KERNEL(reshape2,
kXPU,
kFloat,
kNCHW,
paddle::lite::kernels::xpu::ReshapeCompute<int64_t>,
int64)
.BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU), PRECISION(kInt64))})
.BindInput("ShapeTensor",
{LiteType::GetTensorTy(TARGET(kHost), PRECISION(kInt32))})
.BindInput("Shape",
{LiteType::GetTensorTy(TARGET(kHost), PRECISION(kInt32))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU), PRECISION(kInt64))})
.BindOutput("XShape", {LiteType::GetTensorTy(TARGET(kHost))})
.Finalize();

REGISTER_LITE_KERNEL(reshape,
kXPU,
kFloat,
kNCHW,
paddle::lite::kernels::xpu::ReshapeCompute,
def)
paddle::lite::kernels::xpu::ReshapeCompute<float>,
float32)
.BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU))})
.BindInput("ShapeTensor", {LiteType::GetTensorTy(TARGET(kHost))})
.BindInput("Shape", {LiteType::GetTensorTy(TARGET(kHost))})
.BindInput("ShapeTensor",
{LiteType::GetTensorTy(TARGET(kHost), PRECISION(kInt32))})
.BindInput("Shape",
{LiteType::GetTensorTy(TARGET(kHost), PRECISION(kInt32))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU))})
.Finalize();

REGISTER_LITE_KERNEL(flatten,
kXPU,
kFloat,
kNCHW,
paddle::lite::kernels::xpu::ReshapeCompute,
def)
paddle::lite::kernels::xpu::ReshapeCompute<float>,
float32)
.BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU))})
.BindInput("Shape", {LiteType::GetTensorTy(TARGET(kHost))})
.BindInput("Shape",
{LiteType::GetTensorTy(TARGET(kHost), PRECISION(kInt32))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU))})
.Finalize();

REGISTER_LITE_KERNEL(flatten2,
kXPU,
kFloat,
kNCHW,
paddle::lite::kernels::xpu::ReshapeCompute,
def)
paddle::lite::kernels::xpu::ReshapeCompute<float>,
float32)
.BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU))})
.BindInput("Shape", {LiteType::GetTensorTy(TARGET(kHost))})
.BindInput("Shape",
{LiteType::GetTensorTy(TARGET(kHost), PRECISION(kInt32))})
.BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU))})
.BindOutput("XShape", {LiteType::GetTensorTy(TARGET(kHost))})
.Finalize();
1 change: 1 addition & 0 deletions lite/kernels/xpu/reshape_compute.h
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@ namespace lite {
namespace kernels {
namespace xpu {

template <class T>
class ReshapeCompute : public KernelLite<TARGET(kXPU), PRECISION(kFloat)> {
public:
using param_t = operators::ReshapeParam;
Expand Down