You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
99 lines
3.4 KiB
99 lines
3.4 KiB
/* Copyright (c) 2020 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/operators/softmax_op.h"
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
using Tensor = framework::Tensor;
|
|
using DDim = framework::DDim;
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class SoftmaxXPUKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
auto* x = context.Input<Tensor>("X");
|
|
auto* out = context.Output<Tensor>("Out");
|
|
const int rank = x->dims().size();
|
|
int axis = CanonicalAxis(context.Attr<int>("axis"), rank);
|
|
|
|
// allocate memory on device.
|
|
out->mutable_data<T>(context.GetPlace());
|
|
|
|
std::vector<int> x_dims;
|
|
for (int i = 0; i < rank; i++) {
|
|
x_dims.push_back(x->dims()[i]);
|
|
}
|
|
if (axis < 0) {
|
|
axis += rank;
|
|
}
|
|
|
|
auto& dev_ctx = context.template device_context<DeviceContext>();
|
|
int r = xpu::softmax<T>(dev_ctx.x_context(), x->data<float>(),
|
|
out->data<float>(), x_dims, axis);
|
|
PADDLE_ENFORCE_EQ(
|
|
r, XPU_SUCCESS,
|
|
platform::errors::External("XPU API(softmax2d_forward) return wrong "
|
|
"value[%d %s]",
|
|
r, XPUAPIErrorMsg[r]));
|
|
}
|
|
};
|
|
|
|
template <typename DeviceContext, typename T>
|
|
class SoftmaxGradXPUKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
auto* out = context.Input<Tensor>("Out");
|
|
auto* dout = context.Input<Tensor>(framework::GradVarName("Out"));
|
|
auto* dx = context.Output<Tensor>(framework::GradVarName("X"));
|
|
const int rank = dx->dims().size();
|
|
int axis = CanonicalAxis(context.Attr<int>("axis"), rank);
|
|
|
|
// allocate memory on device.
|
|
dx->mutable_data<T>(context.GetPlace());
|
|
|
|
std::vector<int> x_dims;
|
|
for (int i = 0; i < rank; i++) {
|
|
x_dims.push_back(dx->dims()[i]);
|
|
}
|
|
if (axis < 0) {
|
|
axis += rank;
|
|
}
|
|
|
|
auto& dev_ctx = context.template device_context<DeviceContext>();
|
|
int r = xpu::softmax_grad<T>(dev_ctx.x_context(), out->data<float>(),
|
|
dout->data<float>(), dx->data<float>(), x_dims,
|
|
axis);
|
|
PADDLE_ENFORCE_EQ(
|
|
r, XPU_SUCCESS,
|
|
platform::errors::External("XPU API(softmax2d_backward) return wrong "
|
|
"value[%d %s]",
|
|
r, XPUAPIErrorMsg[r]));
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|
|
|
|
namespace ops = paddle::operators;
|
|
|
|
REGISTER_OP_XPU_KERNEL(
|
|
softmax, ops::SoftmaxXPUKernel<paddle::platform::XPUDeviceContext, float>);
|
|
REGISTER_OP_XPU_KERNEL(
|
|
softmax_grad,
|
|
ops::SoftmaxGradXPUKernel<paddle::platform::XPUDeviceContext, float>);
|
|
|
|
#endif // PADDLE_WITH_XPU
|