[XPU] migrate bce_loss to phi;test=kunlun (#45459)

paddle/fluid/operators/bce_loss_op_xpu.cc

-/* 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. */
-
-#ifdef PADDLE_WITH_XPU
-#include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/platform/device/device_wrapper.h"
-
-namespace paddle {
-namespace operators {
-
-using Tensor = framework::Tensor;
-
-template <typename DeviceContext, typename T>
-class XPUBCELossKernel : public framework::OpKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext& context) const override {
-    auto* x = context.Input<Tensor>("X");
-    auto* labels = context.Input<Tensor>("Label");
-    auto* out = context.Output<Tensor>("Out");
-    out->mutable_data<T>(context.GetPlace());
-
-    auto x_numel = x->numel();
-    auto& dev_ctx = context.template device_context<DeviceContext>();
-    int r = xpu::bce_loss<T>(dev_ctx.x_context(),
-                             x->data<T>(),
-                             labels->data<T>(),
-                             out->data<T>(),
-                             x_numel);
-    PADDLE_ENFORCE_XDNN_SUCCESS(r, "bce_loss");
-  }
-};
-
-template <typename DeviceContext, typename T>
-class XPUBCELossGradKernel : public framework::OpKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext& context) const override {
-    auto* x = context.Input<Tensor>("X");
-    auto* labels = context.Input<Tensor>("Label");
-    auto* dout = context.Input<Tensor>(framework::GradVarName("Out"));
-    auto* dx = context.Output<Tensor>(framework::GradVarName("X"));
-    dx->mutable_data<T>(context.GetPlace());
-
-    auto x_numel = x->numel();
-    auto& dev_ctx = context.template device_context<DeviceContext>();
-    int r = xpu::bce_loss_grad<T>(dev_ctx.x_context(),
-                                  x->data<T>(),
-                                  labels->data<T>(),
-                                  dout->data<T>(),
-                                  dx->data<T>(),
-                                  x_numel);
-    PADDLE_ENFORCE_XDNN_SUCCESS(r, "bce_loss_grad");
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle
-
-namespace ops = paddle::operators;
-REGISTER_OP_XPU_KERNEL(
-    bce_loss, ops::XPUBCELossKernel<paddle::platform::XPUDeviceContext, float>);
-REGISTER_OP_XPU_KERNEL(
-    bce_loss_grad,
-    ops::XPUBCELossGradKernel<paddle::platform::XPUDeviceContext, float>);
-
-#endif  // PADDLE_WITH_XPU

paddle/phi/kernels/xpu/bce_loss_grad_kernel.cc

+// 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/bce_loss_grad_kernel.h"
+
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void BCELossGradKernel(const Context& dev_ctx,
+                       const DenseTensor& input,
+                       const DenseTensor& label,
+                       const DenseTensor& out_grad,
+                       DenseTensor* input_grad) {
+  using XPUType = typename XPUTypeTrait<T>::Type;
+
+  dev_ctx.template Alloc<T>(input_grad);
+
+  auto x_numel = input.numel();
+  int r = xpu::bce_loss_grad<XPUType>(
+      dev_ctx.x_context(),
+      reinterpret_cast<const XPUType*>(input.data<T>()),
+      reinterpret_cast<const XPUType*>(label.data<T>()),
+      reinterpret_cast<const XPUType*>(out_grad.data<T>()),
+      reinterpret_cast<XPUType*>(input_grad->data<T>()),
+      x_numel);
+  PADDLE_ENFORCE_XDNN_SUCCESS(r, "bce_loss_grad");
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    bce_loss_grad, XPU, ALL_LAYOUT, phi::BCELossGradKernel, float) {}

paddle/phi/kernels/xpu/bce_loss_kernel.cc

+// 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/bce_loss_kernel.h"
+
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void BCELossKernel(const Context& dev_ctx,
+                   const DenseTensor& input,
+                   const DenseTensor& label,
+                   DenseTensor* out) {
+  using XPUType = typename XPUTypeTrait<T>::Type;
+  dev_ctx.template Alloc<T>(out);
+
+  auto x_numel = input.numel();
+  int r =
+      xpu::bce_loss<XPUType>(dev_ctx.x_context(),
+                             reinterpret_cast<const XPUType*>(input.data<T>()),
+                             reinterpret_cast<const XPUType*>(label.data<T>()),
+                             reinterpret_cast<XPUType*>(out->data<T>()),
+                             x_numel);
+  PADDLE_ENFORCE_XDNN_SUCCESS(r, "bce_loss");
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(bce_loss, XPU, ALL_LAYOUT, phi::BCELossKernel, float) {}