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| #include <algorithm> |
| #include <cfloat> |
| #include <cmath> |
| #include <functional> |
| #include <random> |
| #include <vector> |
|
|
| #include <benchmark/benchmark.h> |
| #include <fp16/fp16.h> |
| #include "bench/dwconv.h" |
| #include "bench/utils.h" |
|
|
| #include <xnnpack.h> |
| #include <xnnpack/aligned-allocator.h> |
| #include <xnnpack/common.h> |
| #include <xnnpack/dwconv.h> |
| #include <xnnpack/indirection.h> |
| #include <xnnpack/microfnptr.h> |
| #include <xnnpack/microkernel-utils.h> |
| #include <xnnpack/microparams-init.h> |
| #include <xnnpack/operator.h> |
| #include <xnnpack/pack.h> |
|
|
|
|
| static void f16_dwconv(benchmark::State& state, |
| xnn_f16_dwconv_minmax_unipass_ukernel_fn dwconv, |
| xnn_init_f16_minmax_params_fn init_params, |
| uint32_t channel_tile, uint32_t primary_tile, |
| benchmark::utils::IsaCheckFunction isa_check = nullptr) |
| { |
| if (isa_check != nullptr && !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 > primary_tile) { |
| 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)); |
| auto f16rng = std::bind(fp16_ieee_from_fp32_value, f32rng); |
|
|
| 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 ? std::min(subsampling, kernel_width) : 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, channel_tile); |
|
|
| std::vector<uint16_t> a(channels * input_height * input_width + XNN_EXTRA_BYTES / sizeof(uint16_t)); |
| std::generate(a.begin(), a.end(), std::ref(f16rng)); |
| std::vector<uint16_t> k(channels * kernel_height * kernel_width); |
| std::generate(k.begin(), k.end(), std::ref(f16rng)); |
| std::vector<uint16_t> b(channels); |
| std::generate(b.begin(), b.end(), std::ref(f16rng)); |
|
|
| std::vector<uint16_t> z(channels + XNN_EXTRA_BYTES / sizeof(uint16_t)); |
|
|
| const size_t w_elements = (kernel_size + 1) * c_stride; |
| |
| const size_t i_elements = (primary_tile - kernel_size) + 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(uint16_t) * (w_elements + c_elements) + sizeof(void*) * i_elements); |
|
|
| std::vector<uint16_t, AlignedAllocator<uint16_t, 64>> w(w_elements * num_buffers); |
| std::fill(w.begin(), w.end(), UINT16_C(0)); |
| xnn_pack_f16_dwconv_ghw_w(primary_tile, 0, 0, kernel_height, kernel_width, channels, |
| channel_tile, channel_tile, 1, |
| k.data(), b.data(), w.data(), |
| 0, 0, 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 uint16_t*> 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, primary_tile, XNN_LOG2_SIZEOF_HALF); |
| for (size_t n = 1; n < num_buffers; n++) { |
| std::copy(i.cbegin(), i.cbegin() + i_elements, i.begin() + n * i_elements); |
| } |
|
|
| std::vector<uint16_t> c(c_elements * num_buffers); |
| std::fill(c.begin(), c.end(), UINT16_C(0x7E00) ); |
|
|
| xnn_f16_minmax_params params; |
| init_params(¶ms, UINT16_C(0xFC00) , UINT16_C(0x7C00) ); |
|
|
| size_t buffer_index = 0; |
| for (auto _ : state) { |
| state.PauseTiming(); |
| benchmark::utils::PrefetchToL1(a.data(), a.size() * sizeof(uint16_t)); |
| buffer_index = (buffer_index + 1) % num_buffers; |
| state.ResumeTiming(); |
|
|
| for (size_t y = 0; y < output_height; y++) { |
| dwconv(channels, output_width, |
| reinterpret_cast<const void**>(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(), ¶ms); |
| } |
| } |
|
|
| 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 ) * channels * sizeof(uint16_t), |
| benchmark::Counter::kIsRate); |
| } |
|
|
| static void f16_dwconv(benchmark::State& state, |
| xnn_f16_dwconv_minmax_multipass_ukernel_fn dwconv, |
| xnn_init_f16_minmax_params_fn init_params, |
| uint32_t first_pass_tile, |
| uint32_t middle_pass_tile, |
| uint32_t last_pass_tile, |
| uint32_t channel_tile, |
| uint32_t channel_subtile, |
| uint32_t channel_round, |
| benchmark::utils::IsaCheckFunction isa_check = nullptr) |
| { |
| if (isa_check != nullptr && !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 <= first_pass_tile) { |
| 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)); |
| auto f16rng = std::bind(fp16_ieee_from_fp32_value, f32rng); |
|
|
| 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 ? std::min(subsampling, kernel_width) : kernel_width; |
| const size_t step_height = kernel_size + (output_width - 1) * step_width * kernel_height; |
|
|
| std::vector<uint16_t> a(channels * input_height * input_width + XNN_EXTRA_BYTES / sizeof(uint16_t)); |
| std::generate(a.begin(), a.end(), std::ref(f16rng)); |
| std::vector<uint16_t> k(channels * kernel_size); |
| std::generate(k.begin(), k.end(), std::ref(f16rng)); |
| std::vector<uint16_t> b(channels); |
| std::generate(b.begin(), b.end(), std::ref(f16rng)); |
|
|
| std::vector<uint16_t> z(channels + XNN_EXTRA_BYTES / sizeof(uint16_t)); |
| std::vector<uint16_t, AlignedAllocator<uint16_t, 64>> buffer(channels + XNN_MULTIPASS_EXTRA_BYTES / sizeof(uint16_t)); |
|
|
| const size_t tile_size = xnn_dwconv_multipass_tile_size( |
| kernel_size, first_pass_tile, middle_pass_tile, last_pass_tile); |
| const size_t w_elements = |
| xnn_dwconv_multipass_weights_size( |
| tile_size, channels, channel_tile, channel_subtile, channel_round, sizeof(uint16_t), |
| 1, 0) / |
| sizeof(uint16_t); |
| |
| const size_t i_elements = tile_size - kernel_size + 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(uint16_t) * (w_elements + c_elements) + sizeof(void*) * i_elements); |
|
|
| std::vector<uint16_t, AlignedAllocator<uint16_t, 64>> w(w_elements * num_buffers); |
| std::fill(w.begin(), w.end(), UINT16_C(0)); |
| xnn_pack_f16_dwconv_ghw_w( |
| first_pass_tile, middle_pass_tile, last_pass_tile, |
| kernel_height, kernel_width, |
| channels, channel_tile, channel_subtile, channel_round, |
| k.data(), b.data(), w.data(), 0, 0, 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 uint16_t*> 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, tile_size, XNN_LOG2_SIZEOF_HALF); |
| for (size_t n = 1; n < num_buffers; n++) { |
| std::copy(i.cbegin(), i.cbegin() + i_elements, i.begin() + n * i_elements); |
| } |
|
|
| std::vector<uint16_t> c(c_elements * num_buffers); |
| std::fill(c.begin(), c.end(), UINT16_C(0x7E00) ); |
|
|
| xnn_f16_minmax_params params; |
| init_params(¶ms, UINT16_C(0xFC00) , UINT16_C(0x7C00) ); |
|
|
| const int input_advanced = tile_size - last_pass_tile; |
| const int input_stride_elements = kernel_height * step_width - input_advanced; |
| size_t buffer_index = 0; |
| for (auto _ : state) { |
| state.PauseTiming(); |
| benchmark::utils::PrefetchToL1(a.data(), a.size() * sizeof(uint16_t)); |
| buffer_index = (buffer_index + 1) % num_buffers; |
| state.ResumeTiming(); |
|
|
| for (size_t y = 0; y < output_height; y++) { |
| dwconv(channels, output_width, |
| reinterpret_cast<const void**>(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, |
| input_stride_elements * sizeof(void*), 0, |
| 0, z.data(), kernel_size, buffer.data(), ¶ms); |
| } |
| } |
|
|
| 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 ) * channels * sizeof(uint16_t), |
| benchmark::Counter::kIsRate); |
| } |
|
|
| #if XNN_ENABLE_ARM_FP16_VECTOR && (XNN_ARCH_ARM || XNN_ARCH_ARM64) |
| static void f16_dwconv_4p8c__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_4p8c__neonfp16arith_acc2, |
| xnn_init_f16_minmax_fp16arith_params, |
| 8, 4, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_4p8c__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_4p8c__neonfp16arith, |
| xnn_init_f16_minmax_fp16arith_params, |
| 8, 4, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_9p8c__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_9p8c__neonfp16arith_acc2, |
| xnn_init_f16_minmax_fp16arith_params, |
| 8, 9, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_9p8c__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_9p8c__neonfp16arith, |
| xnn_init_f16_minmax_fp16arith_params, |
| 8, 9, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_25p8c__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_25p8c__neonfp16arith_acc2, |
| xnn_init_f16_minmax_fp16arith_params, |
| 8, 25, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_25p8c__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_25p8c__neonfp16arith, |
| xnn_init_f16_minmax_fp16arith_params, |
| 8, 25, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_4p16c__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_4p16c__neonfp16arith_acc2, |
| xnn_init_f16_minmax_fp16arith_params, |
| 16, 4, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_4p16c__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_4p16c__neonfp16arith, |
| xnn_init_f16_minmax_fp16arith_params, |
| 16, 4, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_9p16c__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_9p16c__neonfp16arith_acc2, |
| xnn_init_f16_minmax_fp16arith_params, |
| 16, 9, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_9p16c__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_9p16c__neonfp16arith, |
| xnn_init_f16_minmax_fp16arith_params, |
| 16, 9, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_25p16c__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_25p16c__neonfp16arith_acc2, |
| xnn_init_f16_minmax_fp16arith_params, |
| 16, 25, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_25p16c__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_25p16c__neonfp16arith, |
| xnn_init_f16_minmax_fp16arith_params, |
| 16, 25, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_4p32c__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_4p32c__neonfp16arith_acc2, |
| xnn_init_f16_minmax_fp16arith_params, |
| 32, 4, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_4p32c__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_4p32c__neonfp16arith, |
| xnn_init_f16_minmax_fp16arith_params, |
| 32, 4, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_9p32c__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_9p32c__neonfp16arith_acc2, |
| xnn_init_f16_minmax_fp16arith_params, |
| 32, 9, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_9p32c__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_9p32c__neonfp16arith, |
| xnn_init_f16_minmax_fp16arith_params, |
| 32, 9, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_25p32c__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_25p32c__neonfp16arith_acc2, |
| xnn_init_f16_minmax_fp16arith_params, |
| 32, 25, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_25p32c__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv(state, |
| xnn_f16_dwconv_minmax_ukernel_25p32c__neonfp16arith, |
| xnn_init_f16_minmax_fp16arith_params, |
| 32, 25, benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_5f5m5l8c8s4r__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l8c8s4r__neonfp16arith, xnn_init_f16_minmax_fp16arith_params, |
| 5, 5, 5, |
| 8, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_5f5m5l8c8s4r__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l8c8s4r__neonfp16arith_acc2, xnn_init_f16_minmax_fp16arith_params, |
| 5, 5, 5, |
| 8, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_5f5m5l16c8s4r__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l16c8s4r__neonfp16arith, xnn_init_f16_minmax_fp16arith_params, |
| 5, 5, 5, |
| 16, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_5f5m5l16c8s4r__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l16c8s4r__neonfp16arith_acc2, xnn_init_f16_minmax_fp16arith_params, |
| 5, 5, 5, |
| 16, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_5f5m5l32c8s4r__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l32c8s4r__neonfp16arith, xnn_init_f16_minmax_fp16arith_params, |
| 5, 5, 5, |
| 32, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_5f5m5l32c8s4r__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l32c8s4r__neonfp16arith_acc2, xnn_init_f16_minmax_fp16arith_params, |
| 5, 5, 5, |
| 32, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_6f6m7l8c8s4r__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l8c8s4r__neonfp16arith, xnn_init_f16_minmax_fp16arith_params, |
| 6, 6, 7, |
| 8, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_6f6m7l8c8s4r__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l8c8s4r__neonfp16arith_acc2, xnn_init_f16_minmax_fp16arith_params, |
| 6, 6, 7, |
| 8, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_6f6m7l16c8s4r__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l16c8s4r__neonfp16arith, xnn_init_f16_minmax_fp16arith_params, |
| 6, 6, 7, |
| 16, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_6f6m7l16c8s4r__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l16c8s4r__neonfp16arith_acc2, xnn_init_f16_minmax_fp16arith_params, |
| 6, 6, 7, |
| 16, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_6f6m7l32c8s4r__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l32c8s4r__neonfp16arith, xnn_init_f16_minmax_fp16arith_params, |
| 6, 6, 7, |
| 32, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_6f6m7l32c8s4r__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l32c8s4r__neonfp16arith_acc2, xnn_init_f16_minmax_fp16arith_params, |
| 6, 6, 7, |
| 32, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| static void f16_dwconv_8f8m9l8c8s4r__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l8c8s4r__neonfp16arith, xnn_init_f16_minmax_fp16arith_params, |
| 8, 8, 9, |
| 8, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_8f8m9l8c8s4r__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l8c8s4r__neonfp16arith_acc2, xnn_init_f16_minmax_fp16arith_params, |
| 8, 8, 9, |
| 8, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_8f8m9l16c8s4r__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l16c8s4r__neonfp16arith, xnn_init_f16_minmax_fp16arith_params, |
| 8, 8, 9, |
| 16, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_8f8m9l16c8s4r__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l16c8s4r__neonfp16arith_acc2, xnn_init_f16_minmax_fp16arith_params, |
| 8, 8, 9, |
| 16, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_8f8m9l32c8s4r__neonfp16arith(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l32c8s4r__neonfp16arith, xnn_init_f16_minmax_fp16arith_params, |
| 8, 8, 9, |
| 32, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
| static void f16_dwconv_8f8m9l32c8s4r__neonfp16arith_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l32c8s4r__neonfp16arith_acc2, xnn_init_f16_minmax_fp16arith_params, |
| 8, 8, 9, |
| 32, 8, 4, |
| benchmark::utils::CheckNEONFP16ARITH); |
| } |
|
|
| BENCHMARK_DWCONV(f16_dwconv_4p8c__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_4p8c__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_9p8c__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_9p8c__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_25p8c__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_25p8c__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_4p16c__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_4p16c__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_9p16c__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_9p16c__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_25p16c__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_25p16c__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_4p32c__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_4p32c__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_9p32c__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_9p32c__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_25p32c__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_25p32c__neonfp16arith) |
|
|
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l8c8s4r__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l8c8s4r__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l16c8s4r__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l16c8s4r__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l32c8s4r__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l32c8s4r__neonfp16arith_acc2) |
|
|
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l8c8s4r__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l8c8s4r__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l16c8s4r__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l16c8s4r__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l32c8s4r__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l32c8s4r__neonfp16arith_acc2) |
|
|
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l8c8s4r__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l8c8s4r__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l16c8s4r__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l16c8s4r__neonfp16arith_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l32c8s4r__neonfp16arith) |
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l32c8s4r__neonfp16arith_acc2) |
| #endif |
|
|
|
|
| #if XNN_ARCH_X86 || XNN_ARCH_X86_64 |
| static void f16_dwconv_25p8c__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_25p8c__fma3, xnn_init_f16_minmax_avx_params, |
| 8, 25, benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_25p8c__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_25p8c__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 8, 25, benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_25p16c__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_25p16c__fma3, xnn_init_f16_minmax_avx_params, |
| 16, 25, benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_25p16c__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_25p16c__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 16, 25, benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_25p32c__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_25p32c__fma3, xnn_init_f16_minmax_avx_params, |
| 32, 25, benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_25p32c__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_25p32c__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 32, 25, benchmark::utils::CheckFMA3); |
| } |
|
|
| static void f16_dwconv_5f5m5l8c8s4r__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l8c8s4r__fma3, xnn_init_f16_minmax_avx_params, |
| 5, 5, 5, |
| 8, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_5f5m5l8c8s4r__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l8c8s4r__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 5, 5, 5, |
| 8, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_5f5m5l16c8s4r__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l16c8s4r__fma3, xnn_init_f16_minmax_avx_params, |
| 5, 5, 5, |
| 16, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_5f5m5l16c8s4r__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l16c8s4r__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 5, 5, 5, |
| 16, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_5f5m5l32c8s4r__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l32c8s4r__fma3, xnn_init_f16_minmax_avx_params, |
| 5, 5, 5, |
| 32, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_5f5m5l32c8s4r__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_5f5m5l32c8s4r__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 5, 5, 5, |
| 32, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
|
|
| static void f16_dwconv_6f6m7l8c8s4r__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l8c8s4r__fma3, xnn_init_f16_minmax_avx_params, |
| 6, 6, 7, |
| 8, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_6f6m7l8c8s4r__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l8c8s4r__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 6, 6, 7, |
| 8, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_6f6m7l16c8s4r__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l16c8s4r__fma3, xnn_init_f16_minmax_avx_params, |
| 6, 6, 7, |
| 16, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_6f6m7l16c8s4r__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l16c8s4r__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 6, 6, 7, |
| 16, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_6f6m7l32c8s4r__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l32c8s4r__fma3, xnn_init_f16_minmax_avx_params, |
| 6, 6, 7, |
| 32, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_6f6m7l32c8s4r__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_6f6m7l32c8s4r__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 6, 6, 7, |
| 32, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
|
|
| static void f16_dwconv_8f8m9l8c8s4r__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l8c8s4r__fma3, xnn_init_f16_minmax_avx_params, |
| 8, 8, 9, |
| 8, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_8f8m9l8c8s4r__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l8c8s4r__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 8, 8, 9, |
| 8, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_8f8m9l16c8s4r__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l16c8s4r__fma3, xnn_init_f16_minmax_avx_params, |
| 8, 8, 9, |
| 16, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_8f8m9l16c8s4r__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l16c8s4r__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 8, 8, 9, |
| 16, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_8f8m9l32c8s4r__fma3(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l32c8s4r__fma3, xnn_init_f16_minmax_avx_params, |
| 8, 8, 9, |
| 32, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
| static void f16_dwconv_8f8m9l32c8s4r__fma3_acc2(benchmark::State& state, const char* net) { |
| f16_dwconv( |
| state, xnn_f16_dwconv_minmax_ukernel_8f8m9l32c8s4r__fma3_acc2, xnn_init_f16_minmax_avx_params, |
| 8, 8, 9, |
| 32, 8, 4, |
| benchmark::utils::CheckFMA3); |
| } |
|
|
| BENCHMARK_DWCONV(f16_dwconv_25p8c__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_25p8c__fma3_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_25p16c__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_25p16c__fma3_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_25p32c__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_25p32c__fma3_acc2) |
|
|
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l8c8s4r__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l8c8s4r__fma3_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l16c8s4r__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l16c8s4r__fma3_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l32c8s4r__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_5f5m5l32c8s4r__fma3_acc2) |
|
|
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l8c8s4r__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l8c8s4r__fma3_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l16c8s4r__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l16c8s4r__fma3_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l32c8s4r__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_6f6m7l32c8s4r__fma3_acc2) |
|
|
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l8c8s4r__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l8c8s4r__fma3_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l16c8s4r__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l16c8s4r__fma3_acc2) |
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l32c8s4r__fma3) |
| BENCHMARK_DWCONV(f16_dwconv_8f8m9l32c8s4r__fma3_acc2) |
|
|
| #endif |
|
|
| #ifndef XNNPACK_BENCHMARK_NO_MAIN |
| BENCHMARK_MAIN(); |
| #endif |
|
|