[XPU][PHI] bind index_sample_grad xpu kernel (#53753)

paddle/phi/backends/xpu/xpu2_op_list.cc

@@ -420,6 +420,7 @@ XPUOpMap& get_kl2_ops() {
        XPUKernelSet({phi::DataType::FLOAT32,
                      phi::DataType::INT32,
                      phi::DataType::INT64})},
+      {"index_sample_grad", XPUKernelSet({phi::DataType::FLOAT32})},
       {"index_sample",
        XPUKernelSet({phi::DataType::INT8,
                      phi::DataType::INT16,

paddle/phi/kernels/xpu/index_sample_grad_kernel.cc

+// Copyright (c) 2023 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/index_sample_grad_kernel.h"
+
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/utils/data_type.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void IndexSampleGradKernel(const Context& ctx,
+                           const DenseTensor& x,
+                           const DenseTensor& index,
+                           const DenseTensor& out_grad,
+                           DenseTensor* in_grad) {
+  using XPUType = typename XPUTypeTrait<T>::Type;
+  const auto& index_type = index.dtype();
+  bool index_type_match =
+      index_type == phi::DataType::INT32 || index_type == phi::DataType::INT64;
+  PADDLE_ENFORCE_EQ(index_type_match,
+                    true,
+                    phi::errors::InvalidArgument(
+                        "Input(Index) holds the wrong type, it holds %s, but "
+                        "desires to be %s or %s",
+                        index_type,
+                        phi::DataType::INT32,
+                        phi::DataType::INT64));
+
+  XPUType* in_grad_data = ctx.template Alloc<XPUType>(in_grad);
+  const XPUType* out_grad_data = out_grad.data<XPUType>();
+  auto in_grad_shape = phi::vectorize<int64_t>(in_grad->dims());
+  auto out_grad_shape = phi::vectorize<int64_t>(out_grad.dims());
+  auto index_shape = phi::vectorize<int64_t>(index.dims());
+
+  int r = xpu::constant(
+      ctx.x_context(), in_grad_data, in_grad->numel(), static_cast<XPUType>(0));
+
+  if (index_type == phi::DataType::INT32) {
+    const int* index_data = index.data<int>();
+    r = xpu::scatter_element(ctx.x_context(),
+                             in_grad_data,
+                             out_grad_data,
+                             index_data,
+                             in_grad_data,
+                             in_grad_shape,
+                             out_grad_shape,
+                             index_shape,
+                             1,
+                             1);
+  } else if (index_type == phi::DataType::INT64) {
+    const int64_t* index_data = index.data<int64_t>();
+    r = xpu::scatter_element(ctx.x_context(),
+                             in_grad_data,
+                             out_grad_data,
+                             index_data,
+                             in_grad_data,
+                             in_grad_shape,
+                             out_grad_shape,
+                             index_shape,
+                             1,
+                             1);
+  }
+  PADDLE_ENFORCE_XDNN_SUCCESS(r, "scatter_element");
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    index_sample_grad, XPU, ALL_LAYOUT, phi::IndexSampleGradKernel, float) {}