chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/unstack_kernel_impl.h

@@ -0,0 +1,72 @@
+// 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/core/dense_tensor.h"
+#include "paddle/phi/kernels/funcs/stack_functor.h"
+#if defined(__NVCC__) || defined(__HIPCC__)
+#include <thrust/device_vector.h>
+#endif
+
+namespace phi {
+
+template <typename T, typename Context>
+void UnStackKernel(const Context &dev_ctx,
+                   const DenseTensor &x,
+                   int axis,
+                   int num UNUSED,
+                   std::vector<DenseTensor *> outs) {
+  auto *dy = &x;
+  auto dx = outs;
+  if (axis < 0) axis += dy->dims().size();
+
+  int64_t n = dy->dims()[axis];
+
+  std::vector<T *> dx_datas(n);  // NOLINT
+  for (int64_t i = 0; i < n; i++) {
+    dx_datas[i] = dev_ctx.template Alloc<T>(dx[i]);
+  }
+  auto dy_data = dy->data<T>();
+  if (dy->numel() == 0) {
+    for (int64_t i = 0; i < n; i++) {
+      dev_ctx.template Alloc<T>((outs)[i]);
+      (outs)[i]->Resize((outs)[i]->dims());
+    }
+    return;
+  }
+  int64_t pre = 1;
+  for (int i = 0; i < axis; ++i) pre *= dy->dims()[i];
+  int64_t total_num = dy->numel();
+  int64_t post = total_num / (n * pre);
+
+  // TODO(large-tensor): StackGradFunctorForRange not support int64
+  PADDLE_ENFORCE_LE_INT_MAX(total_num, "total_num");
+
+#if defined(__NVCC__) || defined(__HIPCC__)
+  thrust::device_vector<T *> device_dx_vec(dx_datas);
+  auto dx_data_arr = device_dx_vec.data().get();
+#else
+  auto dx_data_arr = dx_datas.data();
+#endif
+  funcs::StackGradFunctorForRange(
+      dev_ctx, dx_data_arr, dy_data, total_num, n, post);
+#if defined(__NVCC__) || defined(__HIPCC__)
+  // Wait() must be called because device_dx_vec may be destructed before
+  // kernel ends
+  dev_ctx.Wait();
+#endif
+}
+
+}  // namespace phi