text: /* ************************************************************************
   * Copyright 2018-2019 Advanced Micro Devices, Inc.
   * ************************************************************************ */
  
  #include "cblas_interface.hpp"
  #include "near.hpp"
  #include "rocblas.hpp"
  #include "rocblas_init.hpp"
  #include "rocblas_math.hpp"
  #include "rocblas_random.hpp"
  #include "rocblas_test.hpp"
  #include "rocblas_vector.hpp"
  #include "unit.hpp"
  #include "utility.hpp"
  
  template <typename T1, typename T2 = T1>
  void testing_asum_strided_batched_bad_arg_template(const Arguments& arg)
  {
      rocblas_int    N           = 100;
      rocblas_int    incx        = 1;
      rocblas_stride stridex     = 1;
      rocblas_int    batch_count = 5;
  
      static const size_t safe_size        = 100;
      T2                  rocblas_result   = 10;
      T2*                 h_rocblas_result = &rocblas_result;
  
      rocblas_local_handle handle;
      device_vector<T1>    dx(safe_size);
      if(!dx)
      {
          CHECK_HIP_ERROR(hipErrorOutOfMemory);
          return;
      }
  
      CHECK_ROCBLAS_ERROR(rocblas_set_pointer_mode(handle, rocblas_pointer_mode_host));
  
      EXPECT_ROCBLAS_STATUS((rocblas_asum_strided_batched<T1, T2>(
                                handle, N, nullptr, incx, stridex, batch_count, h_rocblas_result)),
                            rocblas_status_invalid_pointer);
      EXPECT_ROCBLAS_STATUS(
          (rocblas_asum_strided_batched<T1, T2>(handle, N, dx, incx, stridex, batch_count, nullptr)),
          rocblas_status_invalid_pointer);
      EXPECT_ROCBLAS_STATUS((rocblas_asum_strided_batched<T1, T2>(
                                nullptr, N, dx, incx, stridex, batch_count, h_rocblas_result)),
                            rocblas_status_invalid_handle);
  }
  
  template <typename T1, typename T2 = T1>
  void testing_asum_strided_batched_template(const Arguments& arg)
  {
      rocblas_int    N           = arg.N;
      rocblas_int    incx        = arg.incx;
      rocblas_stride stridex     = arg.stride_x;
      rocblas_int    batch_count = arg.batch_count;
  
      double rocblas_error_1;
      double rocblas_error_2;
  
      rocblas_local_handle handle;
  
      if(batch_count < 0)
      {
          static const size_t safe_size = 100; //  arbitrarily set to zero
          device_vector<T1>   dx(safe_size);
          device_vector<T2>   d_rocblas_result(std::max(batch_count, 1));
          if(!dx || !d_rocblas_result)
          {
              CHECK_HIP_ERROR(hipErrorOutOfMemory);
              return;
          }
  
          CHECK_ROCBLAS_ERROR(rocblas_set_pointer_mode(handle, rocblas_pointer_mode_device));
          EXPECT_ROCBLAS_STATUS((rocblas_asum_strided_batched<T1, T2>(
                                    handle, N, dx, incx, stridex, batch_count, d_rocblas_result)),
                                rocblas_status_invalid_size);
          return;
      }
  
      // check to prevent undefined memory allocation error
      if(N <= 0 || incx <= 0 || batch_count == 0)
      {
          static const size_t safe_size = 100; // arbitrarily set to 100
          device_vector<T1>   dx(safe_size);
          device_vector<T2>   d_rocblas_result(std::max(batch_count, 1));
          if(!dx || !d_rocblas_result)
          {
              CHECK_HIP_ERROR(hipErrorOutOfMemory);
              return;
          }
  
          CHECK_ROCBLAS_ERROR(rocblas_set_pointer_mode(handle, rocblas_pointer_mode_device));
          CHECK_ROCBLAS_ERROR((rocblas_asum_strided_batched<T1, T2>(
              handle, N, dx, incx, stridex, batch_count, d_rocblas_result)));
          return;
      }
  
      T2 rocblas_result_1[batch_count];
      T2 rocblas_result_2[batch_count];
      T2 cpu_result[batch_count];
  
      size_t size_x = (size_t)stridex;
  
      // allocate memory on device
      device_vector<T1> dx(batch_count * size_x);
      device_vector<T2> d_rocblas_result_2(batch_count);
      if(!dx || !d_rocblas_result_2)
      {
          CHECK_HIP_ERROR(hipErrorOutOfMemory);
          return;
      }
  
      // Naming: dx is in GPU (device) memory. hx is in CPU (host) memory, plz follow this practice
      host_vector<T1> hx(batch_count * size_x);
  
      // Initial Data on CPU
      rocblas_seedrand();
      rocblas_init<T1>(hx, 1, N, incx, stridex, batch_count);
  
      // copy data from CPU to device, does not work for incx != 1
      CHECK_HIP_ERROR(hipMemcpy(dx, hx, sizeof(T1) * size_x * batch_count, hipMemcpyHostToDevice));
  
      double gpu_time_used, cpu_time_used;
  
      if(arg.unit_check || arg.norm_check)
      {
          // GPU BLAS rocblas_pointer_mode_host
          CHECK_ROCBLAS_ERROR(rocblas_set_pointer_mode(handle, rocblas_pointer_mode_host));
          CHECK_ROCBLAS_ERROR((rocblas_asum_strided_batched<T1, T2>(
              handle, N, dx, incx, stridex, batch_count, rocblas_result_1)));
  
          // GPU BgdLAS rocblas_pointer_mode_device
          CHECK_ROCBLAS_ERROR(rocblas_set_pointer_mode(handle, rocblas_pointer_mode_device));
          CHECK_ROCBLAS_ERROR((rocblas_asum_strided_batched<T1, T2>(
              handle, N, dx, incx, stridex, batch_count, d_rocblas_result_2)));
          CHECK_HIP_ERROR(hipMemcpy(
              rocblas_result_2, d_rocblas_result_2, batch_count * sizeof(T2), hipMemcpyDeviceToHost));
  
          // CPU BLAS
          cpu_time_used = get_time_us();
          for(int i = 0; i < batch_count; i++)
          {
              cblas_asum<T1, T2>(N, hx + i * stridex, incx, cpu_result + i);
          }
          cpu_time_used = get_time_us() - cpu_time_used;
  
          if(arg.unit_check)
          {
              unit_check_general<T2>(batch_count, 1, 1, cpu_result, rocblas_result_1);
              unit_check_general<T2>(batch_count, 1, 1, cpu_result, rocblas_result_2);
          }
  
          if(arg.norm_check)
          {
              std::cout << "cpu=" << std::scientific << cpu_result[0]
                        << ", gpu_host_ptr=" << rocblas_result_1[0]
                        << ", gpu_dev_ptr=" << rocblas_result_2[0] << "\n";
  
              rocblas_error_1 = std::abs((cpu_result[0] - rocblas_result_1[0]) / cpu_result[0]);
              rocblas_error_2 = std::abs((cpu_result[0] - rocblas_result_2[0]) / cpu_result[0]);
          }
      }
  
      if(arg.timing)
      {
          int number_cold_calls = 2;
          int number_hot_calls  = 100;
          CHECK_ROCBLAS_ERROR(rocblas_set_pointer_mode(handle, rocblas_pointer_mode_host));
  
          for(int iter = 0; iter < number_cold_calls; iter++)
          {
              rocblas_asum_strided_batched<T1, T2>(
                  handle, N, dx, incx, stridex, batch_count, rocblas_result_2);
          }
  
          gpu_time_used = get_time_us(); // in microseconds
  
          for(int iter = 0; iter < number_hot_calls; iter++)
          {
              rocblas_asum_strided_batched<T1, T2>(
                  handle, N, dx, incx, stridex, batch_count, rocblas_result_2);
          }
  
          gpu_time_used = (get_time_us() - gpu_time_used) / number_hot_calls;
  
          std::cout << "N,incx,stridex,batch_count,rocblas(us)";
  
          if(arg.norm_check)
              std::cout << ",CPU(us),error_host_ptr,error_dev_ptr";
  
          std::cout << std::endl;
          std::cout << N << "," << incx << "," << stridex << "," << batch_count << ","
                    << gpu_time_used;
  
          if(arg.norm_check)
              std::cout << "," << cpu_time_used << "," << rocblas_error_1 << "," << rocblas_error_2;
  
          std::cout << std::endl;
      }
  }
  
  template <typename T>
  void testing_asum_strided_batched_bad_arg(const Arguments& arg)
  {
      testing_asum_strided_batched_bad_arg_template<T>(arg);
  }
  
  template <>
  void testing_asum_strided_batched_bad_arg<rocblas_float_complex>(const Arguments& arg)
  {
      testing_asum_strided_batched_bad_arg_template<rocblas_float_complex, float>(arg);
  }
  
  template <>
  void testing_asum_strided_batched_bad_arg<rocblas_double_complex>(const Arguments& arg)
  {
      testing_asum_strided_batched_bad_arg_template<rocblas_double_complex, double>(arg);
  }
  
  template <typename T>
  void testing_asum_strided_batched(const Arguments& arg)
  {
      return testing_asum_strided_batched_template<T>(arg);
  }
  
  template <>
  void testing_asum_strided_batched<rocblas_float_complex>(const Arguments& arg)
  {
      return testing_asum_strided_batched_template<rocblas_float_complex, float>(arg);
  }
  
  template <>
  void testing_asum_strided_batched<rocblas_double_complex>(const Arguments& arg)
  {
      return testing_asum_strided_batched_template<rocblas_double_complex, double>(arg);
  }
  