text: // Copyright 2019 Google LLC
  //
  // This source code is licensed under the BSD-style license found in the
  // LICENSE file in the root directory of this source tree.
  
  #include <algorithm>
  #include <cfloat>
  #include <cmath>
  #include <functional>
  #include <random>
  #include <vector>
  
  #include <benchmark/benchmark.h>
  #include "bench/dwconv.h"
  #include "bench/utils.h"
  #include <xnnpack/AlignedAllocator.h>
  #include <xnnpack/common.h>
  #include <xnnpack/dwconv.h>
  #include <xnnpack/indirection.h>
  #include <xnnpack/operator.h>
  #include <xnnpack/pack.h>
  #include <xnnpack/params-init.h>
  #include <xnnpack/params.h>
  
  
  static void DWConvBenchmark(benchmark::State& state,
    xnn_f32_dwconv_minmax_unipass_ukernel_function dwconv,
    uint32_t cr, uint32_t kr,
    benchmark::utils::IsaCheckFunction isa_check = nullptr)
  {
    if (isa_check && !isa_check(state)) {
      return;
    }
  
    const size_t input_height = state.range(0);
    const size_t input_width = state.range(1);
    const size_t kernel_height = state.range(2);
    const size_t kernel_width = state.range(3);
    const size_t padding_height = state.range(4);
    const size_t padding_width = state.range(5);
    const size_t subsampling = state.range(6);
    const size_t dilation = state.range(7);
    const size_t channels = state.range(8);
  
    const size_t kernel_size = kernel_height * kernel_width;
    if (kernel_size != kr) {
      state.SkipWithError("kernel size mismatch");
      return;
    }
  
    std::random_device random_device;
    auto rng = std::mt19937(random_device());
    auto f32rng = std::bind(std::uniform_real_distribution<float>(0.0f, 1.0f), std::ref(rng));
  
    const size_t effective_kernel_height = (kernel_height - 1) * dilation + 1;
    const size_t effective_kernel_width = (kernel_width - 1) * dilation + 1;
    const size_t padding_left = padding_width / 2;
    const size_t padding_top = padding_height / 2;
    const size_t output_height = (input_height + padding_height - effective_kernel_height) / subsampling + 1;
    const size_t output_width = (input_width + padding_width - effective_kernel_width) / subsampling + 1;
    const size_t output_size = output_height * output_width;
    const size_t step_width = dilation == 1 ? subsampling : kernel_width;
    const size_t step_height = kernel_size + (output_width - 1) * step_width * kernel_height;
  
    const size_t c_stride = benchmark::utils::RoundUp<size_t>(channels, cr);
  
    std::vector<float> a(channels * input_height * input_width + XNN_EXTRA_BYTES / sizeof(float));
    std::generate(a.begin(), a.end(), std::ref(f32rng));
    std::vector<float> k(channels * kernel_height * kernel_width);
    std::generate(k.begin(), k.end(), std::ref(f32rng));
    std::vector<float> b(channels);
    std::generate(b.begin(), b.end(), std::ref(f32rng));
  
    std::vector<float> z(channels + XNN_EXTRA_BYTES / sizeof(float));
  
    const size_t w_elements = (kernel_size + 1) * c_stride;
    const size_t i_elements = output_height * step_height;
    const size_t c_elements = output_size * channels;
    const size_t num_buffers = 1 +
      benchmark::utils::DivideRoundUp<size_t>(benchmark::utils::GetMaxCacheSize(),
        sizeof(float) * (w_elements + c_elements) + sizeof(void*) * i_elements);
  
    std::vector<float, AlignedAllocator<float, 32>> w(w_elements * num_buffers);
    std::fill(w.begin(), w.end(), 0.0f);
    xnn_pack_f32_dwconv_ghw_w(kernel_height, kernel_width, channels, cr,
        k.data(), b.data(), w.data(), nullptr);
    for (size_t n = 1; n < num_buffers; n++) {
      std::copy(w.cbegin(), w.cbegin() + w_elements, w.begin() + n * w_elements);
    }
  
    std::vector<const float*> i(i_elements * num_buffers);
    xnn_operator convolution_op = { };
    convolution_op.indirection_buffer = reinterpret_cast<const void**>(i.data());
    convolution_op.input              = a.data();
    convolution_op.input_pixel_stride = channels;
    convolution_op.zero_buffer        = z.data();
    convolution_op.input_height       = input_height;
    convolution_op.input_width        = input_width;
    convolution_op.output_height      = output_height;
    convolution_op.output_width       = output_width;
    convolution_op.kernel_height      = kernel_height;
    convolution_op.kernel_width       = kernel_width;
    convolution_op.stride_height      = subsampling;
    convolution_op.stride_width       = subsampling;
    convolution_op.dilation_height    = dilation;
    convolution_op.dilation_width     = dilation;
    convolution_op.padding_top        = padding_top;
    convolution_op.padding_left       = padding_left;
  
    xnn_indirection_init_dwconv2d(&convolution_op, step_height, step_width, 2 /* log2(sizeof(float)) */);
    for (size_t n = 1; n < num_buffers; n++) {
      std::copy(i.cbegin(), i.cbegin() + i_elements, i.begin() + n * i_elements);
    }
  
    std::vector<float> c(c_elements * num_buffers);
    std::fill(c.begin(), c.end(), std::nanf(""));
  
    xnn_f32_minmax_params params;
    xnn_init_f32_minmax_params(
      &params, -std::numeric_limits<float>::infinity(), +std::numeric_limits<float>::infinity());
  
    size_t buffer_index = 0;
    for (auto _ : state) {
      state.PauseTiming();
      benchmark::utils::PrefetchToL1(a.data(), a.size() * sizeof(float));
      buffer_index = (buffer_index + 1) % num_buffers;
      state.ResumeTiming();
  
      for (size_t y = 0; y < output_height; y++) {
        dwconv(channels, output_width,
          i.data() + buffer_index * i_elements + step_height * y,
          w.data() + buffer_index * w_elements,
          c.data() + buffer_index * c_elements + y * output_width * channels,
          kernel_height * step_width * sizeof(void*), 0,
          0, z.data(), &params);
      }
    }
  
    const uint64_t cpu_frequency = benchmark::utils::GetCurrentCpuFrequency();
    if (cpu_frequency != 0) {
      state.counters["cpufreq"] = cpu_frequency;
    }
  
    state.counters["FLOPS"] = benchmark::Counter(
      uint64_t(state.iterations()) * 2 * output_size * channels * kernel_size,
      benchmark::Counter::kIsRate);
  
    state.counters["bytes"] = benchmark::Counter(
      uint64_t(state.iterations()) * (output_size + input_height * input_width + kernel_size + 1 /* bias */) * channels * sizeof(float),
      benchmark::Counter::kIsRate);
  }
  
  
  #if XNN_ARCH_ARM64 && XNN_ENABLE_ASSEMBLY
    static void f32_dwconv_4x9__aarch64_neonfma(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x9__neon, 4, 9);
    }
    static void f32_dwconv_4x9__aarch64_neonfma_cortex_a55(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x9__neonfma, 4, 9);
    }
  
    BENCHMARK_DWCONV(f32_dwconv_4x9__aarch64_neonfma)
    BENCHMARK_DWCONV(f32_dwconv_4x9__aarch64_neonfma_cortex_a55)
  #endif  // XNN_ARCH_ARM64
  
  
  #if XNN_ARCH_ARM || XNN_ARCH_ARM64
    static void f32_dwconv_4x25__neon_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x25__neon_acc2, 4, 25,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_4x25__neon(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x25__neon, 4, 25,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_4x25__neonfma_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x25__neonfma_acc2, 4, 25,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_4x25__neonfma(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x25__neonfma, 4, 25,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_4x4__neon_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x4__neon_acc2, 4, 4,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_4x4__neon(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x4__neon, 4, 4,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_4x4__neonfma_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x4__neonfma_acc2, 4, 4,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_4x4__neonfma(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x4__neonfma, 4, 4,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_4x9__neon_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x9__neon_acc2, 4, 9,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_4x9__neon(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x9__neon, 4, 9,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_4x9__neonfma_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x9__neonfma_acc2, 4, 9,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_4x9__neonfma(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x9__neonfma, 4, 9,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_8x25__neon_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x25__neon_acc2, 8, 25,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_8x25__neon(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x25__neon, 8, 25,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_8x25__neonfma_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x25__neonfma_acc2, 8, 25,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_8x25__neonfma(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x25__neonfma, 8, 25,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_8x4__neon_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x4__neon_acc2, 8, 4,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_8x4__neon(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x4__neon, 8, 4,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_8x4__neonfma_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x4__neonfma_acc2, 8, 4,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_8x4__neonfma(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x4__neonfma, 8, 4,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_8x9__neon_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x9__neon_acc2, 8, 9,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_8x9__neon(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x9__neon, 8, 9,
      benchmark::utils::CheckNEON);
    }
    static void f32_dwconv_8x9__neonfma_acc2(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x9__neonfma_acc2, 8, 9,
      benchmark::utils::CheckNEONFMA);
    }
    static void f32_dwconv_8x9__neonfma(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up8x9__neonfma, 8, 9,
      benchmark::utils::CheckNEONFMA);
    }
  
    BENCHMARK_DWCONV(f32_dwconv_4x25__neon_acc2)
    BENCHMARK_DWCONV(f32_dwconv_4x25__neon)
    BENCHMARK_DWCONV(f32_dwconv_4x25__neonfma_acc2)
    BENCHMARK_DWCONV(f32_dwconv_4x25__neonfma)
    BENCHMARK_DWCONV(f32_dwconv_4x4__neon_acc2)
    BENCHMARK_DWCONV(f32_dwconv_4x4__neon)
    BENCHMARK_DWCONV(f32_dwconv_4x4__neonfma_acc2)
    BENCHMARK_DWCONV(f32_dwconv_4x4__neonfma)
    BENCHMARK_DWCONV(f32_dwconv_4x9__neon_acc2)
    BENCHMARK_DWCONV(f32_dwconv_4x9__neon)
    BENCHMARK_DWCONV(f32_dwconv_4x9__neonfma_acc2)
    BENCHMARK_DWCONV(f32_dwconv_4x9__neonfma)
    BENCHMARK_DWCONV(f32_dwconv_8x25__neon_acc2)
    BENCHMARK_DWCONV(f32_dwconv_8x25__neon)
    BENCHMARK_DWCONV(f32_dwconv_8x25__neonfma_acc2)
    BENCHMARK_DWCONV(f32_dwconv_8x25__neonfma)
    BENCHMARK_DWCONV(f32_dwconv_8x4__neon_acc2)
    BENCHMARK_DWCONV(f32_dwconv_8x4__neon)
    BENCHMARK_DWCONV(f32_dwconv_8x4__neonfma_acc2)
    BENCHMARK_DWCONV(f32_dwconv_8x4__neonfma)
    BENCHMARK_DWCONV(f32_dwconv_8x9__neon_acc2)
    BENCHMARK_DWCONV(f32_dwconv_8x9__neon)
    BENCHMARK_DWCONV(f32_dwconv_8x9__neonfma_acc2)
    BENCHMARK_DWCONV(f32_dwconv_8x9__neonfma)
  #endif  // XNN_ARCH_ARM || XNN_ARCH_ARM64
  
  
  #if XNN_ARCH_X86 || XNN_ARCH_X86_64
    static void f32_dwconv_4x4__sse(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x4__sse, 4, 4);
    }
    static void f32_dwconv_4x9__sse(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x9__sse, 4, 9);
    }
    static void f32_dwconv_4x25__sse(benchmark::State& state, const char* net) {
      DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up4x25__sse, 4, 25);
    }
  
    BENCHMARK_DWCONV(f32_dwconv_4x4__sse)
    BENCHMARK_DWCONV(f32_dwconv_4x9__sse)
    BENCHMARK_DWCONV(f32_dwconv_4x25__sse)
  #endif  // XNN_ARCH_X86 || XNN_ARCH_X86_64
  
  
  static void f32_dwconv_1x4__scalar(benchmark::State& state, const char* net) {
    DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up1x4__scalar, 1, 4);
  }
  static void f32_dwconv_1x9__scalar(benchmark::State& state, const char* net) {
    DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up1x9__scalar, 1, 9);
  }
  static void f32_dwconv_1x25__scalar(benchmark::State& state, const char* net) {
    DWConvBenchmark(state, xnn_f32_dwconv_minmax_ukernel_up1x25__scalar, 1, 25);
  }
  
  BENCHMARK_DWCONV(f32_dwconv_1x4__scalar)
  BENCHMARK_DWCONV(f32_dwconv_1x9__scalar)
  BENCHMARK_DWCONV(f32_dwconv_1x25__scalar)
  
  
  #ifndef XNNPACK_BENCHMARK_NO_MAIN
  BENCHMARK_MAIN();
  #endif
  