text: // 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) {
      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 = phi::vectorize<int>(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()));
  
    Eigen::DSizes<Eigen::DenseIndex, 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();
    // use 32-bit index to speed up
    bool use_32bit_index = eigen_out.size() < Eigen::NumTraits<int>::highest();
    if (use_32bit_index) {
      funcs::EigenBroadcast<std::decay_t<decltype(place)>, T, Rank>::Eval(
          place, To32BitIndex(eigen_out), To32BitIndex(eigen_x), bcast_dims);
    } else {
      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) {
    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 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;
    }
  }
  
  }  // namespace phi
  