chore: import upstream snapshot with attribution

paddle/phi/kernels/gpu/roll_kernel.cu

@@ -0,0 +1,79 @@
+// 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/common/array.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/gpu/roll_kernel_impl.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) {
+  if (x.numel() == 0) {
+    dev_ctx.template Alloc<T>(out);
+    return;
+  }
+  auto* in_data = x.data<T>();
+  T* out_data = dev_ctx.template Alloc<T>(out);
+
+  auto shifts_data = shifts.GetData();
+  int rank = shifts_data.size();
+
+  int64_t numel = x.numel();
+  auto input_dim = x.dims();
+  auto stride_dim = common::stride(input_dim);
+
+  std::vector<int64_t> strides(rank), sizes(rank);
+  if (axis.size() == 0) {
+    strides[0] = 1;
+    sizes[0] = numel;
+    shifts_data[0] = (shifts_data[0] % numel + numel) % numel;
+  } else {
+    for (int i = 0; i < rank; i++) {
+      int dim = axis[i] >= 0 ? axis[i] : axis[i] + input_dim.size();
+      int64_t size = input_dim[dim];
+
+      if (size != 0) {
+        shifts_data[i] = (shifts_data[i] % size + size) % size;
+        strides[i] = stride_dim[dim];
+        sizes[i] = size;
+      }
+    }
+  }
+
+  LaunchRollKernel<T, Context>(
+      dev_ctx, in_data, out_data, rank, numel, shifts_data, strides, sizes);
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(roll,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::RollKernel,
+                   phi::float16,
+                   phi::bfloat16,
+                   bool,
+                   float,
+                   double,
+                   int,
+                   int64_t,
+                   phi::complex64,
+                   phi::complex128) {}