#ifndef EIGEN_TEST_GPU_COMMON_H
#define EIGEN_TEST_GPU_COMMON_H

#ifdef EIGEN_USE_HIP
#include <hip/hip_runtime.h>
#include <hip/hip_runtime_api.h>
#else
#include <cuda.h>
#include <cuda_runtime.h>
#include <cuda_runtime_api.h>
#endif

#include <iostream>

#if !defined(__CUDACC__) && !defined(__HIPCC__)
dim3 threadIdx, blockDim, blockIdx;
#endif

template <typename Kernel, typename Input, typename Output>
void run_on_cpu(const Kernel& ker, int n, const Input& in, Output& out) {
  for (int i = 0; i < n; i++) ker(i, in.data(), out.data());
}

template <typename Kernel, typename Input, typename Output>
__global__ EIGEN_HIP_LAUNCH_BOUNDS_1024 void run_on_gpu_meta_kernel(const Kernel ker, int n, const Input* in,
                                                                    Output* out) {
  int i = threadIdx.x + blockIdx.x * blockDim.x;
  if (i < n) {
    ker(i, in, out);
  }
}

template <typename Kernel, typename Input, typename Output>
void run_on_gpu(const Kernel& ker, int n, const Input& in, Output& out) {
  typename Input::Scalar* d_in;
  typename Output::Scalar* d_out;
  std::ptrdiff_t in_bytes = in.size() * sizeof(typename Input::Scalar);
  std::ptrdiff_t out_bytes = out.size() * sizeof(typename Output::Scalar);

  gpuMalloc((void**)(&d_in), in_bytes);
  gpuMalloc((void**)(&d_out), out_bytes);

  gpuMemcpy(d_in, in.data(), in_bytes, gpuMemcpyHostToDevice);
  gpuMemcpy(d_out, out.data(), out_bytes, gpuMemcpyHostToDevice);

  // Simple and non-optimal 1D mapping assuming n is not too large
  // That's only for unit testing!
  dim3 Blocks(128);
  dim3 Grids((n + int(Blocks.x) - 1) / int(Blocks.x));

  gpuDeviceSynchronize();

#ifdef EIGEN_USE_HIP
  hipLaunchKernelGGL(HIP_KERNEL_NAME(run_on_gpu_meta_kernel<Kernel, typename std::decay<decltype(*d_in)>::type,
                                                            typename std::decay<decltype(*d_out)>::type>),
                     dim3(Grids), dim3(Blocks), 0, 0, ker, n, d_in, d_out);
#else
  // Various versions of clang-format incorrectly add spaces to the kernel launch brackets.
  // clang-format off
  run_on_gpu_meta_kernel<<<Grids, Blocks>>>(ker, n, d_in, d_out);
  // clang-format on
#endif
  // Pre-launch errors.
  gpuError_t err = gpuGetLastError();
  if (err != gpuSuccess) {
    printf("%s: %s\n", gpuGetErrorName(err), gpuGetErrorString(err));
    gpu_assert(false);
  }

  // Kernel execution errors.
  err = gpuDeviceSynchronize();
  if (err != gpuSuccess) {
    printf("%s: %s\n", gpuGetErrorName(err), gpuGetErrorString(err));
    gpu_assert(false);
  }

  // check inputs have not been modified
  gpuMemcpy(const_cast<typename Input::Scalar*>(in.data()), d_in, in_bytes, gpuMemcpyDeviceToHost);
  gpuMemcpy(out.data(), d_out, out_bytes, gpuMemcpyDeviceToHost);

  gpuFree(d_in);
  gpuFree(d_out);
}

template <typename Kernel, typename Input, typename Output>
void run_and_compare_to_gpu(const Kernel& ker, int n, const Input& in, Output& out) {
  Input in_ref, in_gpu;
  Output out_ref, out_gpu;
#if !defined(EIGEN_GPU_COMPILE_PHASE)
  in_ref = in_gpu = in;
  out_ref = out_gpu = out;
#else
  EIGEN_UNUSED_VARIABLE(in);
  EIGEN_UNUSED_VARIABLE(out);
#endif
  run_on_cpu(ker, n, in_ref, out_ref);
  run_on_gpu(ker, n, in_gpu, out_gpu);
#if !defined(EIGEN_GPU_COMPILE_PHASE)
  VERIFY_IS_APPROX(in_ref, in_gpu);
  VERIFY_IS_APPROX(out_ref, out_gpu);
#endif
}

struct compile_time_device_info {
  EIGEN_DEVICE_FUNC void operator()(int i, const int* /*in*/, int* info) const {
    if (i == 0) {
      EIGEN_UNUSED_VARIABLE(info)
#if defined(__CUDA_ARCH__)
      info[0] = int(__CUDA_ARCH__ + 0);
#endif
#if defined(EIGEN_HIP_DEVICE_COMPILE)
      info[1] = int(EIGEN_HIP_DEVICE_COMPILE + 0);
#endif
    }
  }
};

void ei_test_init_gpu() {
  int device = 0;
  gpuDeviceProp_t deviceProp;
  gpuGetDeviceProperties(&deviceProp, device);

  ArrayXi dummy(1), info(10);
  info = -1;
  run_on_gpu(compile_time_device_info(), 10, dummy, info);

  std::cout << "GPU compile-time info:\n";

#ifdef EIGEN_CUDACC
  std::cout << "  EIGEN_CUDACC:                 " << int(EIGEN_CUDACC) << "\n";
#endif

#ifdef EIGEN_CUDA_SDK_VER
  std::cout << "  EIGEN_CUDA_SDK_VER:             " << int(EIGEN_CUDA_SDK_VER) << "\n";
#endif

#if EIGEN_COMP_NVCC
  std::cout << "  EIGEN_COMP_NVCC:             " << int(EIGEN_COMP_NVCC) << "\n";
#endif

#ifdef EIGEN_HIPCC
  std::cout << "  EIGEN_HIPCC:                 " << int(EIGEN_HIPCC) << "\n";
#endif

  std::cout << "  EIGEN_CUDA_ARCH:             " << info[0] << "\n";
  std::cout << "  EIGEN_HIP_DEVICE_COMPILE:    " << info[1] << "\n";

  std::cout << "GPU device info:\n";
  std::cout << "  name:                        " << deviceProp.name << "\n";
  std::cout << "  capability:                  " << deviceProp.major << "." << deviceProp.minor << "\n";
  std::cout << "  multiProcessorCount:         " << deviceProp.multiProcessorCount << "\n";
  std::cout << "  maxThreadsPerMultiProcessor: " << deviceProp.maxThreadsPerMultiProcessor << "\n";
  std::cout << "  warpSize:                    " << deviceProp.warpSize << "\n";
  std::cout << "  regsPerBlock:                " << deviceProp.regsPerBlock << "\n";
  std::cout << "  concurrentKernels:           " << deviceProp.concurrentKernels << "\n";
  std::cout << "  clockRate:                   " << deviceProp.clockRate << "\n";
  std::cout << "  canMapHostMemory:            " << deviceProp.canMapHostMemory << "\n";
  std::cout << "  computeMode:                 " << deviceProp.computeMode << "\n";
}

#endif  // EIGEN_TEST_GPU_COMMON_H