chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/split_kernel_impl.h

@@ -0,0 +1,63 @@
+// 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/kernels/split_kernel.h"
+
+#include "paddle/phi/common/int_array.h"
+#include "paddle/phi/common/scalar.h"
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/kernels/funcs/concat_and_split_functor.h"
+#include "paddle/phi/kernels/funcs/strided_memcpy.h"
+
+namespace phi {
+template <typename T, typename Context>
+void SplitKernel(const Context& dev_ctx,
+                 const DenseTensor& x,
+                 const IntArray& sections UNUSED,
+                 const Scalar& axis_scalar,
+                 std::vector<DenseTensor*> outs) {
+  std::vector<const DenseTensor*> shape_refer;
+  for (size_t j = 0; j < outs.size(); ++j) {
+    dev_ctx.template Alloc<T>(outs[j]);
+    shape_refer.emplace_back(outs[j]);
+  }
+
+  int axis = axis_scalar.to<int>();
+  // Sometimes direct copies will be faster, this maybe need deeply analysis.
+  if (axis == 0 && outs.size() < 10) {
+    funcs::StridedMemcpyWithAxis0<T, Context>(dev_ctx, x, shape_refer, &outs);
+  } else {
+    funcs::SplitFunctor<Context, T> functor;
+    functor(dev_ctx, x, shape_refer, axis, &outs);
+  }
+}
+
+template <typename T, typename Context>
+void SplitWithNumKernel(const Context& dev_ctx,
+                        const DenseTensor& x,
+                        int num,
+                        const Scalar& axis_scalar,
+                        std::vector<DenseTensor*> outs) {
+  int axis_value = axis_scalar.to<int>();
+  auto input_axis_dim = x.dims().at(axis_value);
+  std::vector<int64_t> sections_vec;
+  for (int i = 0; i < num; ++i) {
+    sections_vec.push_back(input_axis_dim / num);
+  }
+  IntArray sections(sections_vec);
+  SplitKernel<T, Context>(dev_ctx, x, sections, axis_scalar, outs);
+}
+
+}  // namespace phi