chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/stack_grad_kernel.cc

@@ -0,0 +1,76 @@
+/* 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/stack_grad_kernel.h"
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/stack_functor.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void StackGradKernel(const Context& dev_ctx,
+                     const DenseTensor& out,
+                     int axis,
+                     std::vector<DenseTensor*> x_grad) {
+  if (axis < 0) axis += out.dims().size();
+  int n = static_cast<int>(out.dims()[axis]);
+  std::vector<T*> dx_datas(n);  // NOLINT
+
+  for (int i = 0; i < n; i++) {
+    if (x_grad[i] == nullptr) {
+      dx_datas[i] = nullptr;
+    } else {
+      dx_datas[i] = dev_ctx.template Alloc<T>(x_grad[i]);
+    }
+  }
+  auto dy_data = out.data<T>();
+
+  // zero sized tensor case
+  if (out.numel() == 0) {
+    for (int i = 0; i < n; i++) {
+      auto x_grad_dim = x_grad[i]->dims();
+      x_grad[i]->Resize(x_grad_dim);
+    }
+    return;
+  }
+
+  int pre = 1;
+  for (int i = 0; i < axis; ++i) pre *= static_cast<int>(out.dims()[i]);
+  int total_num = static_cast<int>(out.numel());
+  int post = total_num / (n * pre);
+  auto dx_data_arr = dx_datas.data();
+  funcs::StackGradFunctorForRange(
+      dev_ctx, dx_data_arr, dy_data, total_num, n, post);
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(stack_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::StackGradKernel,
+                   bool,
+                   float,
+                   double,
+                   int,
+                   int8_t,
+                   int16_t,
+                   int64_t,
+                   uint8_t,
+                   phi::float16,
+                   phi::bfloat16,
+                   phi::complex64,
+                   phi::complex128) {}