chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/tile_kernel_impl.h

@@ -0,0 +1,134 @@
+// 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.
+
+#pragma once
+#include <type_traits>
+#include <vector>
+
+#include "paddle/phi/kernels/funcs/eigen/common.h"
+#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
+#include "paddle/phi/kernels/tile_kernel.h"
+
+namespace phi {
+
+template <typename Context, typename T, int Rank>
+void Tile(const Context& dev_ctx,
+          const DenseTensor& x,
+          std::vector<int64_t> repeat_times,
+          DenseTensor* out) {
+  auto x_dims = x.dims();
+  for (size_t i = 0; i < repeat_times.size(); ++i) {
+    if (repeat_times[i] == 0) {
+      dev_ctx.template Alloc<T>(out);
+      return;
+    }
+    PADDLE_ENFORCE_GT(
+        repeat_times[i],
+        0,
+        errors::InvalidArgument(
+            "All elements of the input 'repeat_times' for tile op must "
+            "be positive integers, but the value received is %d.",
+            repeat_times[i]));
+  }
+  auto vec_x_dims = vectorize<int64_t>(x_dims);
+  if (repeat_times.size() < vec_x_dims.size()) {
+    int diff = vec_x_dims.size() - repeat_times.size();
+    repeat_times.insert(repeat_times.begin(), diff, 1);
+  } else {
+    int diff = repeat_times.size() - vec_x_dims.size();
+    vec_x_dims.insert(vec_x_dims.begin(), diff, 1);
+  }
+  PADDLE_ENFORCE_EQ(
+      repeat_times.size(),
+      vec_x_dims.size(),
+      errors::InvalidArgument(
+          "The rank (%d) of the input 'x' and the rank (%d) of the input "
+          "'repeat_times' for tile op must match after promotion.",
+          vec_x_dims.size(),
+          repeat_times.size()));
+
+  if (Rank == 0) {
+    Copy(dev_ctx, x, dev_ctx.GetPlace(), false, out);
+    return;
+  }
+  Eigen::DSizes<int64_t, Rank> bcast_dims;
+  for (size_t i = 0; i < repeat_times.size(); ++i) {
+    bcast_dims[i] = repeat_times[i];
+  }
+
+  DDim new_x_dims = make_ddim(vec_x_dims);
+  DDim out_dims(new_x_dims);
+  for (size_t i = 0; i < repeat_times.size(); ++i) {
+    out_dims[i] *= repeat_times[i];
+  }
+
+  out->Resize(out_dims);
+  auto eigen_x = EigenTensor<T, Rank>::From(x, new_x_dims);
+  dev_ctx.template Alloc<T>(out);
+
+  auto eigen_out = EigenTensor<T, Rank>::From(*out, out_dims);
+  auto& place = *dev_ctx.eigen_device();
+
+  funcs::EigenBroadcast<std::decay_t<decltype(place)>, T, Rank>::Eval(
+      place, eigen_out, eigen_x, bcast_dims);
+}
+
+template <typename T, typename Context>
+void TileKernel(const Context& dev_ctx,
+                const DenseTensor& x,
+                const IntArray& repeat_times,
+                DenseTensor* out) {
+  if (x.numel() == 0) {
+    dev_ctx.template Alloc<T>(out);
+    return;
+  }
+  auto rank = x.dims().size();
+  auto& repeat_times_data = repeat_times.GetData();
+  int repeat_times_size = repeat_times_data.size();
+  rank = std::max(rank, repeat_times_size);
+
+  switch (rank) {
+    case 0:
+      Tile<Context, T, 0>(dev_ctx, x, repeat_times_data, out);
+      break;
+    case 1:
+      Tile<Context, T, 1>(dev_ctx, x, repeat_times_data, out);
+      break;
+    case 2:
+      Tile<Context, T, 2>(dev_ctx, x, repeat_times_data, out);
+      break;
+    case 3:
+      Tile<Context, T, 3>(dev_ctx, x, repeat_times_data, out);
+      break;
+    case 4:
+      Tile<Context, T, 4>(dev_ctx, x, repeat_times_data, out);
+      break;
+    case 5:
+      Tile<Context, T, 5>(dev_ctx, x, repeat_times_data, out);
+      break;
+    case 6:
+      Tile<Context, T, 6>(dev_ctx, x, repeat_times_data, out);
+      break;
+    case 7:
+      Tile<Context, T, 7>(dev_ctx, x, repeat_times_data, out);
+      break;
+    default:
+      PADDLE_THROW(errors::InvalidArgument(
+          "Only support tensor with rank being between 0 and 7. But "
+          "received tensor's rank = %d.",
+          rank));
+  }
+}
+
+}  // namespace phi