clip_op_xpu.cc

/* 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/operators/clip_op.h"
#include "paddle/fluid/framework/op_registry.h"

namespace paddle {
namespace operators {

using Tensor = framework::Tensor;

template <typename DeviceContext, typename T>
class ClipXPUKernel : public framework::OpKernel<T> {
 public:
  void Compute(const framework::ExecutionContext& ctx) const override {
    auto* x = ctx.Input<Tensor>("X");
    auto* out = ctx.Output<Tensor>("Out");
    out->mutable_data<T>(ctx.GetPlace());

    auto max = static_cast<T>(ctx.Attr<float>("max"));
    if (ctx.HasInput("Max")) {
      Tensor max_cpu;
      auto* max_t = ctx.Input<Tensor>("Max");
      auto* max_data = max_t->data<T>();
      if (platform::is_xpu_place(max_t->place())) {
        TensorCopySync(*max_t, platform::CPUPlace(), &max_cpu);
        max_data = max_cpu.data<T>();
      }
      max = max_data[0];
    }

    auto min = ctx.Attr<float>("min");
    if (ctx.HasInput("Min")) {
      Tensor min_cpu;
      auto* min_t = ctx.Input<Tensor>("Min");
      auto* min_data = min_t->data<T>();
      if (platform::is_xpu_place(min_t->place())) {
        TensorCopySync(*min_t, platform::CPUPlace(), &min_cpu);
        min_data = min_cpu.data<T>();
      }
      min = min_data[0];
    }

    using XPUDataType = typename XPUTypeTrait<T>::Type;
    auto& dev_ctx = ctx.template device_context<DeviceContext>();
    auto x_data = reinterpret_cast<const XPUDataType*>(x->data<T>());
    auto out_data = reinterpret_cast<XPUDataType*>(out->data<T>());
    int r = xpu::clip_v2(dev_ctx.x_context(), x_data, out_data, x->numel(), min,
                         max);
    PADDLE_ENFORCE_EQ(r, XPU_SUCCESS, platform::errors::External(
                                          "XPU API(clip_v2) return wrong "
                                          "value[%d %s]",
                                          r, XPUAPIErrorMsg[r]));
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
namespace plat = paddle::platform;

REGISTER_OP_XPU_KERNEL(clip, ops::ClipXPUKernel<plat::XPUDeviceContext, float>);

#endif