Fix (#65256)

paddle/phi/kernels/xpu/log_loss_grad_kernel.cc

@@ -0,0 +1,50 @@
+// Copyright (c) 2024 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 <memory>
+
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/core/kernel_registry.h"
+namespace phi {
+
+template <typename T, typename Context>
+void LogLossGradXPUKernel(const Context& dev_ctx,
+                          const DenseTensor& input,
+                          const DenseTensor& label,
+                          const DenseTensor& out_grad,
+                          float epsilon_in,
+                          DenseTensor* in_grad) {
+  auto* predict = &input;
+  auto* labels = &label;
+  auto* dloss = &out_grad;
+  auto* dpred = in_grad;
+  if (dpred == nullptr) {
+    return;
+  }
+  auto epsilon = static_cast<T>(epsilon_in);
+  dev_ctx.template Alloc<T>(dpred);
+  int n = predict->numel();
+  int r = xpu::log_loss_grad(dev_ctx.x_context(),
+                             predict->data<T>(),
+                             labels->data<T>(),
+                             dloss->data<T>(),
+                             dpred->data<T>(),
+                             n,
+                             epsilon);
+  PADDLE_ENFORCE_XDNN_SUCCESS(r, "log_loss_grad");
+}
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    log_loss_grad, XPU, ALL_LAYOUT, phi::LogLossGradXPUKernel, float) {}

paddle/phi/kernels/xpu/log_loss_kernel.cc

@@ -0,0 +1,43 @@
+// Copyright (c) 2024 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 <memory>
+
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/core/kernel_registry.h"
+namespace phi {
+
+template <typename T, typename Context>
+void LogLossXPUKernel(const Context& dev_ctx,
+                      const DenseTensor& input,
+                      const DenseTensor& label,
+                      float epsilon_in,
+                      DenseTensor* out) {
+  auto* predict = &input;
+  auto* labels = &label;
+  auto* loss = out;
+  auto epsilon = static_cast<T>(epsilon_in);
+  dev_ctx.template Alloc<T>(loss);
+  int n = predict->numel();
+  int r = xpu::log_loss(dev_ctx.x_context(),
+                        predict->data<T>(),
+                        labels->data<T>(),
+                        loss->data<T>(),
+                        n,
+                        epsilon);
+  PADDLE_ENFORCE_XDNN_SUCCESS(r, "log_loss");
+}
+}  // namespace phi
+
+PD_REGISTER_KERNEL(log_loss, XPU, ALL_LAYOUT, phi::LogLossXPUKernel, float) {}