chore: import upstream snapshot with attribution

paddle/phi/kernels/slice_kernel.h

@@ -0,0 +1,98 @@
+// 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/common/int_array.h"
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/core/tensor_array.h"
+#include "paddle/phi/infermeta/unary.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void SliceKernel(const Context& dev_ctx,
+                 const DenseTensor& input,
+                 const std::vector<int64_t>& axes,
+                 const IntArray& starts,
+                 const IntArray& ends,
+                 const std::vector<int64_t>& infer_flags,
+                 const std::vector<int64_t>& decrease_axis,
+                 DenseTensor* out);
+
+template <typename T, typename Context>
+void SliceArrayKernel(const Context& dev_ctx,
+                      const TensorArray& input,
+                      const IntArray& starts,
+                      const IntArray& ends,
+                      TensorArray* out);
+
+template <typename T, typename Context>
+void SliceArrayDenseKernel(const Context& dev_ctx,
+                           const TensorArray& input,
+                           const IntArray& starts,
+                           DenseTensor* out);
+
+template <typename Context>
+void SliceStridedKernel(const Context& dev_ctx,
+                        const DenseTensor& input,
+                        const std::vector<int64_t>& axes,
+                        const IntArray& starts,
+                        const IntArray& ends,
+                        const std::vector<int64_t>& infer_flags,
+                        const std::vector<int64_t>& decrease_axis,
+                        DenseTensor* out);
+
+template <typename T, typename Context>
+DenseTensor Slice(const Context& dev_ctx,
+                  const DenseTensor& input,
+                  const std::vector<int64_t>& axes,
+                  const IntArray& starts,
+                  const IntArray& ends) {
+  DenseTensor dense_out;
+  MetaTensor meta_out(&dense_out);
+  std::vector<int64_t> infer_flags = {1};
+  std::vector<int64_t> decrease_axis = {};
+  SliceRawInferMeta(
+      input, axes, starts, ends, infer_flags, decrease_axis, &meta_out);
+  SliceKernel<T, Context>(dev_ctx,
+                          input,
+                          axes,
+                          starts,
+                          ends,
+                          infer_flags,
+                          decrease_axis,
+                          &dense_out);
+  return dense_out;
+}
+
+template <typename T, typename Context>
+void Slice(const Context& dev_ctx,
+           const DenseTensor& input,
+           const std::vector<int64_t>& axes,
+           const IntArray& starts,
+           const IntArray& ends,
+           DenseTensor* out) {
+  MetaTensor meta_out(out);
+  std::vector<int64_t> infer_flags = {1};
+  std::vector<int64_t> decrease_axis = {};
+  SliceRawInferMeta(
+      input, axes, starts, ends, infer_flags, decrease_axis, &meta_out);
+  if (input.initialized()) {
+    SliceKernel<T, Context>(
+        dev_ctx, input, axes, starts, ends, infer_flags, decrease_axis, out);
+  }
+}
+
+}  // namespace phi