[Phi] Migrate lable_smooth_op into Phi (#39796)

* [Phi] Migrate lable_smooth_op into Phi

* fix PT->PD

paddle/fluid/framework/operator.cc

@@ -2040,7 +2040,7 @@ void OperatorWithKernel::BuildPtenKernelContext(
         (i == 0 ? 0 : pt_kernel_context->InputRangeAt(i - 1).second);
 
     // deal with optional here
-    if ((it == ctx.inputs.end()) &&
+    if ((it == ctx.inputs.end() || it->second.size() == 0) &&
         (input_defs[i].type_index ==
          std::type_index(typeid(paddle::optional<const phi::DenseTensor&>)))) {
       pt_kernel_context->EmplaceBackInputWithoutSetRange(nullptr);

paddle/fluid/operators/label_smooth_op.cc

@@ -12,9 +12,8 @@ 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/fluid/operators/label_smooth_op.h"
-
 #include <string>
+#include "paddle/fluid/framework/op_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -152,11 +151,3 @@ REGISTER_OPERATOR(label_smooth, ops::LabelSmoothOp, ops::LabelSmoothOpMaker,
                   ops::LabelSmoothGradMaker<paddle::framework::OpDesc>,
                   ops::LabelSmoothGradMaker<paddle::imperative::OpBase>);
 REGISTER_OPERATOR(label_smooth_grad, ops::LabelSmoothGradOp);
-REGISTER_OP_CPU_KERNEL(
-    label_smooth,
-    ops::LabelSmoothKernel<paddle::platform::CPUDeviceContext, float>,
-    ops::LabelSmoothKernel<paddle::platform::CPUDeviceContext, double>);
-REGISTER_OP_CPU_KERNEL(
-    label_smooth_grad,
-    ops::LabelSmoothGradKernel<paddle::platform::CPUDeviceContext, float>,
-    ops::LabelSmoothGradKernel<paddle::platform::CPUDeviceContext, double>);

paddle/fluid/operators/label_smooth_op.cu

-/* 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. */
-
-#include "paddle/fluid/framework/tensor.h"
-#include "paddle/fluid/operators/elementwise/elementwise_op_impl.cu.h"
-#include "paddle/fluid/operators/label_smooth_op.h"
-namespace paddle {
-namespace operators {
-
-template <typename T>
-struct LabelSmoothFunctor {
-  T epsilon;
-  T label_dim;
-
-  __forceinline__ LabelSmoothFunctor(float epsilon_data, int label_dim_data) {
-    epsilon = static_cast<T>(epsilon_data);
-    label_dim = static_cast<T>(label_dim_data);
-  }
-
-  __device__ __forceinline__ T operator()(const T x) const {
-    return (static_cast<T>(1 - epsilon) * x +
-            static_cast<T>(epsilon / label_dim));
-  }
-};
-
-template <typename T>
-struct LabelSmoothGradFunctor {
-  T epsilon;
-
-  __forceinline__ LabelSmoothGradFunctor(float epsilon_data) {
-    epsilon = static_cast<T>(epsilon_data);
-  }
-
-  __device__ __forceinline__ T operator()(const T x) const {
-    return static_cast<T>(1 - epsilon) * x;
-  }
-};
-
-template <typename T>
-__global__ void LabelSmoothRunDistKernel(const int N, const float epsilon,
-                                         const int dist_numel, const T* src,
-                                         const T* dist_data, T* dst) {
-  CUDA_KERNEL_LOOP(idx, N) {
-    int dist_idx = idx % dist_numel;
-    dst[idx] = static_cast<T>(1 - epsilon) * src[idx] +
-               static_cast<T>(epsilon) * dist_data[dist_idx];
-  }
-}
-
-template <typename DeviceContext, typename T>
-class LabelSmoothGPUKernel : public framework::OpKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext& ctx) const {
-    auto* out_t = ctx.Output<framework::LoDTensor>("Out");
-    auto* in_t = ctx.Input<framework::LoDTensor>("X");
-    auto* dist_t = ctx.Input<framework::Tensor>("PriorDist");
-    auto label_dim = in_t->dims()[in_t->dims().size() - 1];
-    auto epsilon = ctx.Attr<float>("epsilon");
-    auto& dev = *ctx.template device_context<DeviceContext>().eigen_device();
-    auto size_prob = in_t->numel();
-    const T* in_data = in_t->data<T>();
-    T* out_data = out_t->mutable_data<T>(ctx.GetPlace());
-    int threads = 512;
-    int grid = (size_prob + threads - 1) / threads;
-    auto stream = ctx.cuda_device_context().stream();
-    if (dist_t) {
-      auto dist_numel = dist_t->numel();
-      const T* dist_data = dist_t->data<T>();
-      LabelSmoothRunDistKernel<T><<<grid, threads, 0, stream>>>(
-          size_prob, epsilon, dist_numel, in_data, dist_data, out_data);
-
-    } else {
-      auto& dev_ctx =
-          ctx.template device_context<platform::CUDADeviceContext>();
-
-      std::vector<const framework::Tensor*> ins = {in_t};
-      std::vector<framework::Tensor*> outs = {out_t};
-      auto functor = LabelSmoothFunctor<T>(epsilon, label_dim);
-      paddle::operators::LaunchSameDimsElementwiseCudaKernel<T>(dev_ctx, ins,
-                                                                &outs, functor);
-    }
-  }
-};
-
-template <typename DeviceContext, typename T>
-class LabelSmoothGradGPUKernel : public framework::OpKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext& ctx) const {
-    auto* d_out_t = ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
-    auto* d_in_t = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
-    d_in_t->mutable_data<T>(ctx.GetPlace());
-
-    auto epsilon = ctx.Attr<float>("epsilon");
-    auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
-
-    std::vector<const framework::Tensor*> ins = {d_out_t};
-    std::vector<framework::Tensor*> outs = {d_in_t};
-    auto functor = LabelSmoothGradFunctor<T>(epsilon);
-    paddle::operators::LaunchSameDimsElementwiseCudaKernel<T>(dev_ctx, ins,
-                                                              &outs, functor);
-  }
-};
-}  // namespace operators
-}  // namespace paddle
-namespace ops = paddle::operators;
-
-REGISTER_OP_CUDA_KERNEL(
-    label_smooth,
-    ops::LabelSmoothGPUKernel<paddle::platform::CUDADeviceContext, float>,
-    ops::LabelSmoothGPUKernel<paddle::platform::CUDADeviceContext, double>);
-REGISTER_OP_CUDA_KERNEL(
-    label_smooth_grad,
-    ops::LabelSmoothGradGPUKernel<paddle::platform::CUDADeviceContext, float>,
-    ops::LabelSmoothGradGPUKernel<paddle::platform::CUDADeviceContext, double>);

paddle/fluid/operators/label_smooth_op.h

-/* 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. */
-
-#pragma once
-
-#include "paddle/fluid/framework/eigen.h"
-#include "paddle/fluid/framework/op_registry.h"
-
-namespace paddle {
-namespace operators {
-
-template <typename DeviceContext, typename T>
-class LabelSmoothKernel : public framework::OpKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext& ctx) const {
-    auto* out_t = ctx.Output<framework::LoDTensor>("Out");
-    auto* in_t = ctx.Input<framework::LoDTensor>("X");
-    auto* dist_t = ctx.Input<framework::Tensor>("PriorDist");
-    auto label_dim = in_t->dims()[in_t->dims().size() - 1];
-    out_t->mutable_data<T>(ctx.GetPlace());
-    if (label_dim != 0) {
-      auto epsilon = ctx.Attr<float>("epsilon");
-      auto out = framework::EigenVector<T>::Flatten(*out_t);
-      auto in = framework::EigenVector<T>::Flatten(*in_t);
-      auto& dev = *ctx.template device_context<DeviceContext>().eigen_device();
-      if (dist_t) {
-        auto dist = framework::EigenVector<T>::Flatten(*dist_t);
-        out.device(dev) = static_cast<T>(1 - epsilon) * in +
-                          static_cast<T>(epsilon) *
-                              dist.broadcast(Eigen::DSizes<int, 1>(
-                                  in_t->numel() / label_dim));
-      } else {
-        out.device(dev) = static_cast<T>(1 - epsilon) * in +
-                          static_cast<T>(epsilon / label_dim);
-      }
-    }
-  }
-};
-
-template <typename DeviceContext, typename T>
-class LabelSmoothGradKernel : public framework::OpKernel<T> {
- public:
-  void Compute(const framework::ExecutionContext& ctx) const {
-    auto* d_out_t = ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
-    auto* d_in_t = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
-    d_in_t->mutable_data<T>(ctx.GetPlace());
-    auto d_out_dim = d_out_t->dims()[d_out_t->dims().size() - 1];
-    if (d_out_dim != 0) {
-      auto d_out = framework::EigenVector<T>::Flatten(*d_out_t);
-      auto d_in = framework::EigenVector<T>::Flatten(*d_in_t);
-
-      auto epsilon = ctx.Attr<float>("epsilon");
-      auto& dev = *ctx.template device_context<DeviceContext>().eigen_device();
-      d_in.device(dev) = static_cast<T>(1 - epsilon) * d_out;
-    }
-  }
-};
-}  // namespace operators
-}  // namespace paddle

paddle/fluid/operators/label_smooth_op_npu.cc

@@ -12,7 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/fluid/operators/label_smooth_op.h"
+#include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/platform/device/npu/npu_op_runner.h"
 
 namespace paddle {

paddle/fluid/operators/label_smooth_op_xpu.cc

@@ -13,7 +13,6 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #ifdef PADDLE_WITH_XPU
-#include "paddle/fluid/operators/label_smooth_op.h"
 #include "paddle/fluid/framework/op_registry.h"
 
 namespace paddle {

paddle/phi/kernels/cpu/label_smooth_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/label_smooth_grad_kernel.h"
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/eigen/common.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void LabelSmoothGradKernel(const Context& ctx,
+                           const DenseTensor& out_grad,
+                           float epsilon,
+                           DenseTensor* label_grad) {
+  ctx.template Alloc<T>(label_grad);
+  auto d_out_dim = out_grad.dims()[out_grad.dims().size() - 1];
+  if (d_out_dim != 0) {
+    auto d_out = EigenVector<T>::Flatten(out_grad);
+    auto d_in = EigenVector<T>::Flatten(*label_grad);
+
+    auto& dev = *ctx.eigen_device();
+    d_in.device(dev) = static_cast<T>(1 - epsilon) * d_out;
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(label_smooth_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::LabelSmoothGradKernel,
+                   float,
+                   double) {}

paddle/phi/kernels/cpu/label_smooth_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/label_smooth_kernel.h"
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/eigen/common.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void LabelSmoothKernel(const Context& ctx,
+                       const DenseTensor& label,
+                       paddle::optional<const DenseTensor&> prior_dist,
+                       float epsilon,
+                       DenseTensor* out) {
+  auto label_dim = label.dims()[label.dims().size() - 1];
+  ctx.template Alloc<T>(out);
+  auto& dev = *ctx.eigen_device();
+  if (label_dim != 0) {
+    auto eigen_out = EigenVector<T>::Flatten(*out);
+    auto eigen_in = EigenVector<T>::Flatten(label);
+    if (prior_dist.is_initialized()) {
+      auto dist = EigenVector<T>::Flatten(*prior_dist.get_ptr());
+      eigen_out.device(dev) =
+          static_cast<T>(1 - epsilon) * eigen_in +
+          static_cast<T>(epsilon) *
+              dist.broadcast(Eigen::DSizes<int, 1>(label.numel() / label_dim));
+    } else {
+      eigen_out.device(dev) = static_cast<T>(1 - epsilon) * eigen_in +
+                              static_cast<T>(epsilon / label_dim);
+    }
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    label_smooth, CPU, ALL_LAYOUT, phi::LabelSmoothKernel, float, double) {}

paddle/phi/kernels/gpu/label_smooth_grad_kernel.cu

+// 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/fluid/operators/elementwise/elementwise_op_impl.cu.h"
+#include "paddle/phi/backends/gpu/gpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/label_smooth_grad_kernel.h"
+
+namespace phi {
+template <typename T>
+struct LabelSmoothGradFunctor {
+  T epsilon;
+
+  __forceinline__ LabelSmoothGradFunctor(float epsilon_data) {
+    epsilon = static_cast<T>(epsilon_data);
+  }
+
+  __device__ __forceinline__ T operator()(const T x) const {
+    return static_cast<T>(1 - epsilon) * x;
+  }
+};
+
+template <typename T, typename Context>
+void LabelSmoothGradKernel(const Context& ctx,
+                           const DenseTensor& out_grad,
+                           float epsilon,
+                           DenseTensor* label_grad) {
+  ctx.template Alloc<T>(label_grad);
+
+  std::vector<const DenseTensor*> ins = {&out_grad};
+  std::vector<DenseTensor*> outs = {label_grad};
+  auto functor = LabelSmoothGradFunctor<T>(epsilon);
+  paddle::operators::LaunchSameDimsElementwiseCudaKernel<T>(
+      ctx, ins, &outs, functor);
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(label_smooth_grad,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::LabelSmoothGradKernel,
+                   float,
+                   double) {}

paddle/phi/kernels/gpu/label_smooth_kernel.cu

+// 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 <vector>
+#include "paddle/fluid/operators/elementwise/elementwise_op_impl.cu.h"
+#include "paddle/phi/backends/gpu/gpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/label_smooth_kernel.h"
+
+namespace phi {
+
+template <typename T>
+struct LabelSmoothFunctor {
+  T epsilon;
+  T label_dim;
+
+  __forceinline__ LabelSmoothFunctor(float epsilon_data, int label_dim_data) {
+    epsilon = static_cast<T>(epsilon_data);
+    label_dim = static_cast<T>(label_dim_data);
+  }
+
+  __device__ __forceinline__ T operator()(const T x) const {
+    return (static_cast<T>(1 - epsilon) * x +
+            static_cast<T>(epsilon / label_dim));
+  }
+};
+
+template <typename T>
+__global__ void LabelSmoothRunDistKernel(const int N,
+                                         const float epsilon,
+                                         const int dist_numel,
+                                         const T* src,
+                                         const T* dist_data,
+                                         T* dst) {
+  CUDA_KERNEL_LOOP(idx, N) {
+    int dist_idx = idx % dist_numel;
+    dst[idx] = static_cast<T>(1 - epsilon) * src[idx] +
+               static_cast<T>(epsilon) * dist_data[dist_idx];
+  }
+}
+
+template <typename T, typename Context>
+void LabelSmoothKernel(const Context& ctx,
+                       const DenseTensor& label,
+                       paddle::optional<const DenseTensor&> prior_dist,
+                       float epsilon,
+                       DenseTensor* out) {
+  auto label_dim = label.dims()[label.dims().size() - 1];
+  auto size_prob = label.numel();
+  const T* in_data = label.data<T>();
+  T* out_data = ctx.template Alloc<T>(out);
+
+  if (prior_dist.get_ptr()) {
+    int threads = 512;
+    int grid = (size_prob + threads - 1) / threads;
+    auto stream = ctx.stream();
+    const auto* dist_t = prior_dist.get_ptr();
+    auto dist_numel = dist_t->numel();
+    const T* dist_data = dist_t->data<T>();
+    LabelSmoothRunDistKernel<T><<<grid, threads, 0, stream>>>(
+        size_prob, epsilon, dist_numel, in_data, dist_data, out_data);
+
+  } else {
+    std::vector<const DenseTensor*> ins = {&label};
+    std::vector<DenseTensor*> outs = {out};
+    auto functor = LabelSmoothFunctor<T>(epsilon, label_dim);
+    paddle::operators::LaunchSameDimsElementwiseCudaKernel<T>(
+        ctx, ins, &outs, functor);
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    label_smooth, GPU, ALL_LAYOUT, phi::LabelSmoothKernel, float, double) {}

paddle/phi/kernels/label_smooth_grad_kernel.h

+// 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.
+
+#pragma once
+
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/core/device_context.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void LabelSmoothGradKernel(const Context& ctx,
+                           const DenseTensor& out_grad,
+                           float epsilon,
+                           DenseTensor* label_grad);
+
+}  // namespace phi

paddle/phi/kernels/label_smooth_kernel.h

+// 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.
+
+#pragma once
+
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/core/device_context.h"
+#include "paddle/utils/optional.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void LabelSmoothKernel(const Context& ctx,
+                       const DenseTensor& label,
+                       paddle::optional<const DenseTensor&> prior_dist,
+                       float epsilon,
+                       DenseTensor* out);
+
+}  // namespace phi

paddle/phi/ops/compat/label_smooth_sig.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/core/compat/op_utils.h"
+
+namespace phi {
+
+KernelSignature LabelSmoothOpArgumentMapping(
+    const ArgumentMappingContext& ctx) {
+  return KernelSignature(
+      "label_smooth", {"X", "PriorDist"}, {"epsilon"}, {"Out"});
+}
+
+KernelSignature LabelSmoothGradOpArgumentMapping(
+    const ArgumentMappingContext& ctx) {
+  return KernelSignature("label_smooth_grad",
+                         {GradVarName("Out")},
+                         {"epsilon"},
+                         {GradVarName("X")});
+}
+
+}  // namespace phi
+
+PD_REGISTER_ARG_MAPPING_FN(label_smooth, phi::LabelSmoothOpArgumentMapping);
+PD_REGISTER_ARG_MAPPING_FN(label_smooth_grad,
+                           phi::LabelSmoothGradOpArgumentMapping);