chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/roll_kernel.cc

@@ -0,0 +1,94 @@
+// 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/core/dense_tensor.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
+#include "paddle/phi/kernels/cast_kernel.h"
+#include "paddle/phi/kernels/cpu/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;
+  }
+  using Type =
+      typename std::conditional<std::is_same<T, bool>::value, int16_t, T>::type;
+  std::vector<Type> out_vec;
+  if (std::is_same<T, bool>::value) {
+    DenseTensor tmp_int_tensor;
+    tmp_int_tensor = Cast<T, Context>(dev_ctx, x, DataType::INT16);
+    TensorToVector(tmp_int_tensor, dev_ctx, &out_vec);
+  } else {
+    TensorToVector(x, dev_ctx, &out_vec);
+  }
+
+  auto shifts_data = shifts.GetData();
+  size_t nums = shifts_data.size();
+  DDim input_dim = x.dims();
+  auto dims = axis;
+
+  // axis = none, reshape to 1-D tensor
+  if (dims.empty()) {
+    dims.push_back(0l);
+    input_dim = Dim<1>(out_vec.size());
+  }
+
+  for (size_t i = 0; i < nums; i++) {
+    PADDLE_ENFORCE_EQ(
+        dims[i] < input_dim.size() && dims[i] >= (0 - input_dim.size()),
+        true,
+        common::errors::OutOfRange(
+            "Attr(axis[%d]) is out of range, It's expected "
+            "to be in range of [-%d, %d]. But received Attr(axis[%d]) = %d.",
+            i,
+            input_dim.size(),
+            input_dim.size() - 1,
+            i,
+            dims[i]));
+    ShiftAlongDim(out_vec.data(), input_dim, dims[i], shifts_data[i]);
+  }
+  dev_ctx.template Alloc<T>(out);
+  if (std::is_same<T, bool>::value) {
+    DenseTensor tmp_bool_tensor;
+    TensorFromVector(out_vec, dev_ctx, &tmp_bool_tensor);
+    *out = Cast<Type, Context>(dev_ctx, tmp_bool_tensor, DataType::BOOL);
+  } else {
+    TensorFromVector(out_vec, dev_ctx, out);
+  }
+  out->Resize(x.dims());
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(roll,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::RollKernel,
+                   bool,
+                   float,
+                   double,
+                   int,
+                   int64_t,
+                   phi::complex64,
+                   phi::complex128) {}