未验证 提交 9310e56a 编写于 作者: Z zhangyikun02 提交者: GitHub

move range kernel to phi, test=kunlun (#45602)

上级 663ebd5f
......@@ -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.cdn.bcebos.com/KL-SDK/klsdk-dev")
set(XPU_BASE_URL "${XPU_BASE_URL_WITHOUT_DATE}/20220812")
set(XPU_BASE_URL "${XPU_BASE_URL_WITHOUT_DATE}/20220820")
else()
set(XPU_BASE_URL "${XPU_BASE_URL}")
endif()
......@@ -19,7 +19,7 @@ endif()
if(NOT DEFINED XPU_XDNN_BASE_URL)
set(XPU_XDNN_BASE_URL_WITHOUT_DATE
"https://klx-sdk-release-public.su.bcebos.com/xdnn/dev")
set(XPU_XDNN_BASE_URL "${XPU_XDNN_BASE_URL_WITHOUT_DATE}/20220812")
set(XPU_XDNN_BASE_URL "${XPU_XDNN_BASE_URL_WITHOUT_DATE}/20220820")
else()
set(XPU_XDNN_BASE_URL "${XPU_XDNN_BASE_URL}")
endif()
......
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
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. */
#ifdef PADDLE_WITH_XPU
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/range_op.h"
namespace paddle {
namespace operators {
template <typename T>
class XPURangeKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
auto* start_t = context.Input<framework::Tensor>("Start");
auto* end_t = context.Input<framework::Tensor>("End");
auto* step_t = context.Input<framework::Tensor>("Step");
auto* out = context.Output<framework::Tensor>("Out");
framework::Tensor n;
framework::TensorCopySync(*start_t, platform::CPUPlace(), &n);
T start = n.data<T>()[0];
framework::TensorCopySync(*end_t, platform::CPUPlace(), &n);
T end = n.data<T>()[0];
framework::TensorCopySync(*step_t, platform::CPUPlace(), &n);
T step = n.data<T>()[0];
int64_t size = 0;
GetSize(start, end, step, &size);
out->Resize(phi::make_ddim({size}));
T* out_data = out->mutable_data<T>(context.GetPlace());
framework::Tensor out_cpu;
T* out_cpu_data_ptr =
out_cpu.mutable_data<T>(platform::CPUPlace(), out->numel() * sizeof(T));
T value = start;
for (int64_t i = 0; i < size; ++i) {
out_cpu_data_ptr[i] = value;
value += step;
}
memory::Copy(context.GetPlace(),
static_cast<void*>(out_data),
platform::CPUPlace(),
static_cast<void*>(out_cpu_data_ptr),
out->numel() * sizeof(T));
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OP_XPU_KERNEL(range,
ops::XPURangeKernel<int>,
ops::XPURangeKernel<int64_t>,
ops::XPURangeKernel<float>,
ops::XPURangeKernel<double>);
#endif // PADDLE_WITH_XPU
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
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 "paddle/phi/kernels/arange_kernel.h"
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/range_function.h"
namespace phi {
template <typename T, typename Context>
void ArangeKernel(const Context& dev_ctx,
const DenseTensor& start,
const DenseTensor& end,
const DenseTensor& step,
DenseTensor* out) {
auto place = dev_ctx.GetPlace();
auto cpu_place = phi::CPUPlace();
DenseTensor n_cpu;
n_cpu.Resize({start.numel()});
T* n_cpu_data = dev_ctx.template HostAlloc<T>(&n_cpu);
paddle::memory::Copy(
cpu_place, n_cpu_data, place, start.data<T>(), sizeof(T) * start.numel());
T start_value = n_cpu_data[0];
paddle::memory::Copy(
cpu_place, n_cpu_data, place, end.data<T>(), sizeof(T) * end.numel());
T end_value = n_cpu_data[0];
paddle::memory::Copy(
cpu_place, n_cpu_data, place, step.data<T>(), sizeof(T) * step.numel());
T step_value = n_cpu_data[0];
int64_t size = 0;
phi::funcs::GetSize(start_value, end_value, step_value, &size);
out->Resize(phi::make_ddim({size}));
T* out_data = dev_ctx.template Alloc<T>(out);
DenseTensor out_cpu;
out_cpu.Resize({out->numel()});
T* out_cpu_data = dev_ctx.template HostAlloc<T>(&out_cpu);
T value = start_value;
for (int64_t i = 0; i < size; ++i) {
out_cpu_data[i] = value;
value += step_value;
}
paddle::memory::Copy(
place, out_data, cpu_place, out_cpu_data, out->numel() * sizeof(T));
}
} // namespace phi
PD_REGISTER_KERNEL(
arange, XPU, ALL_LAYOUT, phi::ArangeKernel, float, double, int, int64_t) {}
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