Skip to content

xpu kernels support api int64 vector inputs, test=kunlun #49336

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

Merged
QingshuChen merged 1 commit into from
Dec 29, 2022
Merged

xpu kernels support api int64 vector inputs, test=kunlun #49336

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
2 changes: 1 addition & 1 deletion cmake/external/xpu.cmake
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ set(XPU_RT_LIB_NAME "libxpurt.so")
if(NOT DEFINED XPU_BASE_URL)
set(XPU_BASE_URL_WITHOUT_DATE
"https://baidu-kunlun-product.su.bcebos.com/KL-SDK/klsdk-dev")
set(XPU_BASE_URL "${XPU_BASE_URL_WITHOUT_DATE}/20221215")
set(XPU_BASE_URL "${XPU_BASE_URL_WITHOUT_DATE}/20221227")
else()
set(XPU_BASE_URL "${XPU_BASE_URL}")
endif()
Expand Down
40 changes: 24 additions & 16 deletions paddle/phi/kernels/xpu/compare_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -52,22 +52,30 @@ void XPUCompareKernelImpl(const Context& dev_ctx,
PADDLE_ENFORCE_XDNN_SUCCESS(ret, "compare op");
}

#define DEFINE_XPU_COMPARE_KERNEL(name, functor) \
template <typename T, typename Context> \
void name##RawKernel(const Context& dev_ctx, \
const DenseTensor& x, \
const DenseTensor& y, \
int axis, \
DenseTensor* out) { \
using XPUType = typename XPUTypeTrait<T>::Type; \
XPUCompareKernelImpl<T, XPUType, Context>(dev_ctx, x, y, out, functor); \
} \
template <typename T, typename Context> \
void name##Kernel(const Context& dev_ctx, \
const DenseTensor& x, \
const DenseTensor& y, \
DenseTensor* out) { \
name##RawKernel<T, Context>(dev_ctx, x, y, -1, out); \
#define DEFINE_XPU_COMPARE_KERNEL(name, functor) \
template <typename T, typename Context> \
void name##RawKernel(const Context& dev_ctx, \
const DenseTensor& x, \
const DenseTensor& y, \
int axis, \
DenseTensor* out) { \
using XPUType = typename XPUTypeTrait<T>::Type; \
auto f = [](xpu::Context* ctx, \
const XPUType* x, \
const XPUType* y, \
bool* z, \
const std::vector<int>& xshape, \
const std::vector<int>& yshape) { \
return functor(ctx, x, y, z, xshape, yshape); \
}; \
XPUCompareKernelImpl<T, XPUType, Context>(dev_ctx, x, y, out, f); \
} \
template <typename T, typename Context> \
void name##Kernel(const Context& dev_ctx, \
const DenseTensor& x, \
const DenseTensor& y, \
DenseTensor* out) { \
name##RawKernel<T, Context>(dev_ctx, x, y, -1, out); \
}

DEFINE_XPU_COMPARE_KERNEL(Equal, xpu::broadcast_equal<XPUType>)
Expand Down
13 changes: 11 additions & 2 deletions paddle/phi/kernels/xpu/elementwise_add_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -54,8 +54,17 @@ void AddRawKernel(const Context& dev_ctx,
int axis,
DenseTensor* out) {
using XPUType = typename XPUTypeTrait<T>::Type;
XPUElementwise<T, XPUType>(
dev_ctx, x, y, axis, out, xpu::broadcast_add<XPUType>);

auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
XPUType* z,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_add<XPUType>(ctx, x, y, z, xshape, yshape);
};

XPUElementwise<T, XPUType>(dev_ctx, x, y, axis, out, f);
}

} // namespace phi
Expand Down
24 changes: 15 additions & 9 deletions paddle/phi/kernels/xpu/elementwise_divide_grad_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -35,15 +35,21 @@ void DivideGradKernel(const Context& dev_ctx,
DenseTensor* dy) {
using XPUType = typename XPUTypeTrait<T>::Type;
funcs::ElementwiseGradPreProcess(dout, dx);
XPUElementwiseGrad<T, XPUType>(dev_ctx,
x,
y,
dout,
axis,
dx,
dy,
xpu::broadcast_div_grad<XPUType>,
true);

auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
const XPUType* z,
const XPUType* dz,
XPUType* dy,
XPUType* dx,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_div_grad<XPUType>(
ctx, x, y, z, dz, dy, dx, xshape, yshape);
};

XPUElementwiseGrad<T, XPUType>(dev_ctx, x, y, dout, axis, dx, dy, f, true);
}

} // namespace phi
Expand Down
12 changes: 10 additions & 2 deletions paddle/phi/kernels/xpu/elementwise_divide_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -31,8 +31,16 @@ void DivideRawKernel(const Context& dev_ctx,
int axis,
DenseTensor* out) {
using XPUType = typename XPUTypeTrait<T>::Type;
XPUElementwise<T, XPUType>(
dev_ctx, x, y, axis, out, xpu::broadcast_div<XPUType>);
auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
XPUType* z,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_div<XPUType>(ctx, x, y, z, xshape, yshape);
};

XPUElementwise<T, XPUType>(dev_ctx, x, y, axis, out, f);
}

} // namespace phi
Expand Down
48 changes: 30 additions & 18 deletions paddle/phi/kernels/xpu/elementwise_grad_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -29,15 +29,21 @@ void MaximumGradKernel(const Context& dev_ctx,
DenseTensor* dx,
DenseTensor* dy) {
using XPUType = typename XPUTypeTrait<T>::Type;
XPUElementwiseGrad<T, XPUType>(dev_ctx,
x,
y,
dout,
axis,
dx,
dy,
xpu::broadcast_max_grad<XPUType>,
true);

auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
const XPUType* z,
const XPUType* dz,
XPUType* dy,
XPUType* dx,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_max_grad<XPUType>(
ctx, x, y, z, dz, dy, dx, xshape, yshape);
};

XPUElementwiseGrad<T, XPUType>(dev_ctx, x, y, dout, axis, dx, dy, f, true);
}

template <typename T, typename Context>
Expand All @@ -49,15 +55,21 @@ void MinimumGradKernel(const Context& dev_ctx,
DenseTensor* dx,
DenseTensor* dy) {
using XPUType = typename XPUTypeTrait<T>::Type;
XPUElementwiseGrad<T, XPUType>(dev_ctx,
x,
y,
dout,
axis,
dx,
dy,
xpu::broadcast_min_grad<XPUType>,
true);

auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
const XPUType* z,
const XPUType* dz,
XPUType* dy,
XPUType* dx,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_min_grad<XPUType>(
ctx, x, y, z, dz, dy, dx, xshape, yshape);
};

XPUElementwiseGrad<T, XPUType>(dev_ctx, x, y, dout, axis, dx, dy, f, true);
}

} // namespace phi
Expand Down
60 changes: 50 additions & 10 deletions paddle/phi/kernels/xpu/elementwise_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -27,8 +27,16 @@ void FloorDivideRawKernel(const Context& dev_ctx,
int axis,
DenseTensor* out) {
using XPUType = typename XPUTypeTrait<T>::Type;
XPUElementwise<T, XPUType>(
dev_ctx, x, y, axis, out, xpu::broadcast_floordiv<XPUType>);
auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
XPUType* z,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_floordiv<XPUType>(ctx, x, y, z, xshape, yshape);
};

XPUElementwise<T, XPUType>(dev_ctx, x, y, axis, out, f);
}

template <typename T, typename Context>
Expand All @@ -38,8 +46,16 @@ void MaximumRawKernel(const Context& dev_ctx,
int axis,
DenseTensor* out) {
using XPUType = typename XPUTypeTrait<T>::Type;
XPUElementwise<T, XPUType>(
dev_ctx, x, y, axis, out, xpu::broadcast_max<XPUType>);
auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
XPUType* z,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_max<XPUType>(ctx, x, y, z, xshape, yshape);
};

XPUElementwise<T, XPUType>(dev_ctx, x, y, axis, out, f);
}

template <typename T, typename Context>
Expand All @@ -49,8 +65,16 @@ void MinimumRawKernel(const Context& dev_ctx,
int axis,
DenseTensor* out) {
using XPUType = typename XPUTypeTrait<T>::Type;
XPUElementwise<T, XPUType>(
dev_ctx, x, y, axis, out, xpu::broadcast_min<XPUType>);
auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
XPUType* z,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_min<XPUType>(ctx, x, y, z, xshape, yshape);
};

XPUElementwise<T, XPUType>(dev_ctx, x, y, axis, out, f);
}

template <typename T, typename Context>
Expand All @@ -60,8 +84,16 @@ void RemainderRawKernel(const Context& dev_ctx,
int axis,
DenseTensor* out) {
using XPUType = typename XPUTypeTrait<T>::Type;
XPUElementwise<T, XPUType>(
dev_ctx, x, y, axis, out, xpu::broadcast_mod<XPUType>);
auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
XPUType* z,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_mod<XPUType>(ctx, x, y, z, xshape, yshape);
};

XPUElementwise<T, XPUType>(dev_ctx, x, y, axis, out, f);
}

template <typename T, typename Context>
Expand All @@ -71,8 +103,16 @@ void ElementwisePowRawKernel(const Context& dev_ctx,
int axis,
DenseTensor* out) {
using XPUType = typename XPUTypeTrait<T>::Type;
XPUElementwise<T, XPUType>(
dev_ctx, x, y, axis, out, xpu::broadcast_pow<XPUType>);
auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
XPUType* z,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_pow<XPUType>(ctx, x, y, z, xshape, yshape);
};

XPUElementwise<T, XPUType>(dev_ctx, x, y, axis, out, f);
}

} // namespace phi
Expand Down
23 changes: 14 additions & 9 deletions paddle/phi/kernels/xpu/elementwise_multiply_grad_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -34,15 +34,20 @@ void MultiplyGradKernel(const Context& dev_ctx,
DenseTensor* dy) {
using XPUType = typename XPUTypeTrait<T>::Type;
funcs::ElementwiseGradPreProcess(dout, dx);
XPUElementwiseGrad<T, XPUType>(dev_ctx,
x,
y,
dout,
axis,
dx,
dy,
xpu::broadcast_mul_grad<XPUType>,
true);
auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
const XPUType* z,
const XPUType* dz,
XPUType* dy,
XPUType* dx,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_mul_grad<XPUType>(
ctx, x, y, z, dz, dy, dx, xshape, yshape);
};

XPUElementwiseGrad<T, XPUType>(dev_ctx, x, y, dout, axis, dx, dy, f, true);
}

} // namespace phi
Expand Down
12 changes: 10 additions & 2 deletions paddle/phi/kernels/xpu/elementwise_multiply_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -31,8 +31,16 @@ void MultiplyRawKernel(const Context& dev_ctx,
int axis,
DenseTensor* out) {
using XPUType = typename XPUTypeTrait<T>::Type;
XPUElementwise<T, XPUType>(
dev_ctx, x, y, axis, out, xpu::broadcast_mul<XPUType>);
auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
XPUType* z,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_mul<XPUType>(ctx, x, y, z, xshape, yshape);
};

XPUElementwise<T, XPUType>(dev_ctx, x, y, axis, out, f);
}

} // namespace phi
Expand Down
25 changes: 16 additions & 9 deletions paddle/phi/kernels/xpu/elementwise_subtract_grad_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -28,15 +28,22 @@ void SubtractGradKernel(const Context& dev_ctx,
DenseTensor* dx,
DenseTensor* dy) {
using XPUType = typename XPUTypeTrait<T>::Type;
phi::XPUElementwiseGrad<T, XPUType>(dev_ctx,
x,
y,
dout,
axis,
dx,
dy,
xpu::broadcast_sub_grad<XPUType>,
false);

auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
const XPUType* z,
const XPUType* dz,
XPUType* dy,
XPUType* dx,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_sub_grad<XPUType>(
ctx, x, y, z, dz, dy, dx, xshape, yshape);
};

phi::XPUElementwiseGrad<T, XPUType>(
dev_ctx, x, y, dout, axis, dx, dy, f, false);
}

} // namespace phi
Expand Down
12 changes: 10 additions & 2 deletions paddle/phi/kernels/xpu/elementwise_subtract_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -26,8 +26,16 @@ void SubtractRawKernel(const Context& dev_ctx,
int axis,
DenseTensor* out) {
using XPUType = typename XPUTypeTrait<T>::Type;
phi::XPUElementwise<T, XPUType>(
dev_ctx, x, y, axis, out, xpu::broadcast_sub<XPUType>);
auto f = [](xpu::Context* ctx,
const XPUType* x,
const XPUType* y,
XPUType* z,
const std::vector<int>& xshape,
const std::vector<int>& yshape) {
return xpu::broadcast_sub<XPUType>(ctx, x, y, z, xshape, yshape);
};

phi::XPUElementwise<T, XPUType>(dev_ctx, x, y, axis, out, f);
}

} // namespace phi
Expand Down
Loading