chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/stack_kernel.cc

@@ -0,0 +1,86 @@
+/* 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_kernel.h"
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void StackKernel(const Context& dev_ctx,
+                 const std::vector<const DenseTensor*>& x,
+                 int axis,
+                 DenseTensor* out) {
+  if (axis < 0) axis += (x[0]->dims().size() + 1);
+
+  auto x_dims = x[0]->dims();
+  for (int i = 0; i < x_dims.size(); i++) {
+    PADDLE_ENFORCE_GE(
+        x_dims[i],
+        0,
+        common::errors::InvalidArgument(
+            "The dims of Input(X) should be greater than or equal to 0"));
+  }
+  // zero sized tensor case
+  if (x[0]->numel() == 0) {
+    dev_ctx.template Alloc<T>(out);
+    auto out_dims = out->dims();
+    out->Resize(out_dims);
+    return;
+  }
+
+  int n = static_cast<int>(x.size());
+  T* y_data = dev_ctx.template Alloc<T>(out);
+  std::vector<const T*> x_datas(n);
+  for (int i = 0; i < n; i++) x_datas[i] = x[i]->data<T>();
+
+  int pre = 1, post = 1;
+  auto& dim = x[0]->dims();
+  for (auto i = 0; i < axis; ++i) pre *= static_cast<int>(dim[i]);
+  for (auto i = axis; i < dim.size(); ++i) post *= static_cast<int>(dim[i]);
+
+  auto x_data_arr = x_datas.data();
+
+  size_t x_offset = 0;
+  size_t y_offset = 0;
+  for (int i = 0; i < pre; i++) {
+    for (int j = 0; j < n; j++) {
+      std::memcpy(
+          y_data + y_offset, x_data_arr[j] + x_offset, post * sizeof(T));
+      y_offset += post;
+    }
+    x_offset += post;
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(stack,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::StackKernel,
+                   bool,
+                   float,
+                   double,
+                   int,
+                   int8_t,
+                   int64_t,
+                   int16_t,
+                   uint8_t,
+                   phi::float16,
+                   phi::bfloat16,
+                   phi::complex64,
+                   phi::complex128) {}