chore: import upstream snapshot with attribution

paddle/phi/kernels/xpu/roll_kernel.cc

@@ -0,0 +1,74 @@
+// 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/roll_kernel.h"
+
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+namespace phi {
+template <typename T, typename Context>
+void RollKernel(const Context& dev_ctx,
+                const DenseTensor& x,
+                const IntArray& shifts,
+                const std::vector<int64_t>& axis,
+                DenseTensor* out) {
+  using XPUType = typename XPUTypeTrait<T>::Type;
+  auto shifts_data = shifts.GetData();
+  if (out && out->numel() == 0) {
+    dev_ctx.template Alloc<T>(out);
+    return;
+  }
+  dev_ctx.template Alloc<T>(out);
+  DDim input_dim = x.dims();
+  std::vector<int64_t> xshape;
+  size_t nums = shifts_data.size();
+  for (int i = 0; i < input_dim.size(); ++i) {
+    xshape.emplace_back(input_dim[i]);
+  }
+
+  auto dims = axis;
+
+  // axis = none, reshape to 1-D tensor
+  if (dims.size() == 0) {
+    dims.push_back(0l);
+    input_dim = Dim<1>(x.numel());
+  }
+  std::vector<int64_t> shifts_in;
+  std::vector<int64_t> axis_in;
+
+  for (size_t i = 0; i < nums; ++i) {
+    int64_t a = dims[i];
+    if (a < 0) {
+      a += (input_dim.size());
+    }
+    axis_in.emplace_back(a);
+    int64_t sh = shifts_data[i] % input_dim[a];
+    if (sh < 0) {
+      sh += input_dim[a];
+    }
+    shifts_in.emplace_back(sh);
+  }
+  int r = xpu::roll(dev_ctx.x_context(),
+                    reinterpret_cast<const XPUType*>(x.data<T>()),
+                    reinterpret_cast<XPUType*>(out->data<T>()),
+                    xshape,
+                    shifts_in,
+                    axis_in);
+  PADDLE_ENFORCE_XDNN_SUCCESS(r, "roll");
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(roll, XPU, ALL_LAYOUT, phi::RollKernel, float) {}