chore: import upstream snapshot with attribution

paddle/phi/kernels/gpu/index_select_kernel.cu

@@ -0,0 +1,96 @@
+// 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/index_select_kernel.h"
+
+#include "paddle/common/enforce.h"
+#include "paddle/phi/backends/gpu/gpu_info.h"
+#include "paddle/phi/backends/gpu/gpu_launch_config.h"
+#include "paddle/phi/backends/gpu/gpu_primitives.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/utils/data_type.h"
+#include "paddle/phi/kernels/gpu/index_select_impl.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void IndexSelectKernel(const Context& dev_ctx,
+                       const DenseTensor& x,
+                       const DenseTensor& index,
+                       int dim,
+                       DenseTensor* output) {
+  if (output && output->numel() == 0) {
+    dev_ctx.template Alloc<T>(output);
+    return;
+  }
+  auto input_dim = x.dims();
+  auto output_dim = output->dims();
+  dim = dim >= 0 ? dim : dim + input_dim.size();
+  auto stride_dim = common::stride(input_dim);
+  int64_t stride = stride_dim[dim];
+  int64_t size = output_dim[dim];
+  int64_t delta = input_dim[dim] - size;
+  int64_t dim_size = input_dim[dim];
+  const auto& index_type = index.dtype();
+
+  bool index_type_match =
+      index_type == DataType::INT64 || index_type == DataType::INT32;
+  PADDLE_ENFORCE_EQ(index_type_match,
+                    true,
+                    common::errors::InvalidArgument(
+                        "Input(Index) holds the wrong type, it holds %s, but "
+                        "desires to be %s or %s",
+                        index_type,
+                        DataType::INT32,
+                        DataType::INT64));
+
+  auto* in_data = x.data<T>();
+  T* out_data = dev_ctx.template Alloc<T>(output);
+
+  int64_t numel = output->numel();
+  auto stream = dev_ctx.stream();
+
+  unsigned int block_dim = PADDLE_CUDA_NUM_THREADS;
+  const uint64_t grid_x = (numel + block_dim - 1) / block_dim;
+  PADDLE_ENFORCE_LE_UINT32_MAX(grid_x, "grid.x");
+  dim3 grid_dim = dim3(static_cast<uint32_t>(grid_x));
+  backends::gpu::LimitGridDim(dev_ctx, &grid_dim);
+
+  if (index_type == DataType::INT64) {
+    const int64_t* index_data = index.data<int64_t>();
+    index_select_cuda_kernel<T, int64_t><<<grid_dim, block_dim, 0, stream>>>(
+        in_data, out_data, index_data, numel, stride, size, delta, dim_size);
+  } else {
+    const int* index_data = index.data<int>();
+    index_select_cuda_kernel<T, int><<<grid_dim, block_dim, 0, stream>>>(
+        in_data, out_data, index_data, numel, stride, size, delta, dim_size);
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(index_select,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::IndexSelectKernel,
+                   float,
+                   double,
+                   phi::float8_e4m3fn,
+                   phi::float16,
+                   phi::bfloat16,
+                   phi::complex64,
+                   phi::complex128,
+                   int,
+                   int64_t,
+                   bool) {}