bench/f32-dwconv.cc - platform/external/XNNPACK - Gitiles

 // 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(-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
	// 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(-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