Lint cleanup benchmark_kelvin.cc Change-Id: I1f0ec9d3499d54101dc1325d8ac5a0842952d450
diff --git a/benchmarks/benchmark_kelvin.cc b/benchmarks/benchmark_kelvin.cc index 9c3eabb..079f567 100644 --- a/benchmarks/benchmark_kelvin.cc +++ b/benchmarks/benchmark_kelvin.cc
@@ -16,10 +16,10 @@ #include <memory> -#include "crt/kelvin.h" -#include "crt/log.h" #include "benchmarks/benchmark.h" #include "benchmarks/cycle_count.h" +#include "crt/kelvin.h" +#include "crt/log.h" #include "tensorflow/lite/micro/micro_interpreter.h" #include "tensorflow/lite/micro/micro_log.h" #include "tensorflow/lite/micro/micro_mutable_op_resolver.h" @@ -34,20 +34,23 @@ // In order to include the model data generate from Bazel, include the header // using the name passed as a macro. -#define MODEL_HEADER_DIRECTORY BENCHMARK_PATH/ +#define MODEL_HEADER_DIRECTORY BENCHMARK_PATH #define MODEL_HEADER_TYPE _model.h -#define MODEL_HEADER STR(MODEL_HEADER_DIRECTORY BENCHMARK_NAME MODEL_HEADER_TYPE) +#define MODEL_HEADER \ + STR(MODEL_HEADER_DIRECTORY BENCHMARK_NAME MODEL_HEADER_TYPE) #include MODEL_HEADER #if (TEST_DATA_INPUT == 1) #define TEST_DATA_INPUT_HEADER_TYPE _input.h -#define TEST_DATA_INPUT_HEADER STR(MODEL_HEADER_DIRECTORY BENCHMARK_NAME TEST_DATA_INPUT_HEADER_TYPE) +#define TEST_DATA_INPUT_HEADER \ + STR(MODEL_HEADER_DIRECTORY BENCHMARK_NAME TEST_DATA_INPUT_HEADER_TYPE) #include TEST_DATA_INPUT_HEADER #endif #if (TEST_DATA_OUTPUT == 1) #define TEST_DATA_OUTPUT_HEADER_TYPE _output.h -#define TEST_DATA_OUTPUT_HEADER STR(MODEL_HEADER_DIRECTORY BENCHMARK_NAME TEST_DATA_OUTPUT_HEADER_TYPE) +#define TEST_DATA_OUTPUT_HEADER \ + STR(MODEL_HEADER_DIRECTORY BENCHMARK_NAME TEST_DATA_OUTPUT_HEADER_TYPE) #include TEST_DATA_OUTPUT_HEADER #endif @@ -59,16 +62,19 @@ #endif uint8_t g_tensor_arena[kTensorArenaSize] __attribute__((aligned(64))); -__attribute__((section(".model_output_header"))) BenchmarkOutputHeader output_header = { - .return_code = 0, // Set by kelvin_start based on return value in main. +__attribute__(( + section(".model_output_header"))) BenchmarkOutputHeader output_header = { + .return_code = 0, // Set by kelvin_start based on return value in main. .iterations = 0, .cycles = 0, .mismatch_count = 0, }; -// This includes all ops currently used in the Kelvin model suite. More can be added. +// This includes all ops currently used in the Kelvin model suite. More can be +// added. constexpr int kAllOpsNum = 28; -std::unique_ptr<tflite::MicroMutableOpResolver<kAllOpsNum>> GetAllOpsResolver() { +std::unique_ptr<tflite::MicroMutableOpResolver<kAllOpsNum>> +GetAllOpsResolver() { tflite::MicroMutableOpResolver<kAllOpsNum> resolver; resolver.AddAveragePool2D(); resolver.AddMaxPool2D(); @@ -110,28 +116,32 @@ constexpr int kSuccess = 0; constexpr int kAllocatonFailed = -1; constexpr int kInvokeFailed = -2; -} // namespace +} // namespace - -int main(int argc, char **argv) { - std::unique_ptr<tflite::MicroMutableOpResolver<kAllOpsNum>> resolver = GetAllOpsResolver(); +int main(int argc, char** argv) { + std::unique_ptr<tflite::MicroMutableOpResolver<kAllOpsNum>> resolver = + GetAllOpsResolver(); const auto* model = tflite::GetModel(g_benchmark_model_data); uint8_t variable_arena[2048]; - tflite::MicroAllocator *variable_allocator = + tflite::MicroAllocator* variable_allocator = tflite::MicroAllocator::Create(variable_arena, 1024); - tflite::MicroResourceVariables *resource_variables = + tflite::MicroResourceVariables* resource_variables = tflite::MicroResourceVariables::Create(variable_allocator, 20); #if (PROFILE == 1) tflite::MicroProfiler profiler; - std::unique_ptr<tflite::MicroInterpreter> interpreter = std::make_unique<tflite::MicroInterpreter>( - model, *resolver.get(), g_tensor_arena, kTensorArenaSize, resource_variables, &profiler); + std::unique_ptr<tflite::MicroInterpreter> interpreter = + std::make_unique<tflite::MicroInterpreter>( + model, *resolver.get(), g_tensor_arena, kTensorArenaSize, + resource_variables, &profiler); // For a profiled model, just run a single iteration const int iterations = 1; #else - std::unique_ptr<tflite::MicroInterpreter> interpreter = std::make_unique<tflite::MicroInterpreter>( - model, *resolver.get(), g_tensor_arena, kTensorArenaSize, resource_variables); + std::unique_ptr<tflite::MicroInterpreter> interpreter = + std::make_unique<tflite::MicroInterpreter>( + model, *resolver.get(), g_tensor_arena, kTensorArenaSize, + resource_variables); const int iterations = ITERATIONS; #endif @@ -142,7 +152,8 @@ TfLiteTensor* input = interpreter->input(0); #if (TEST_DATA_INPUT == 1) - memcpy(tflite::GetTensorData<uint8_t>(input), g_benchmark_input, input->bytes); + memcpy(tflite::GetTensorData<uint8_t>(input), g_benchmark_input, + input->bytes); #else memset(tflite::GetTensorData<uint8_t>(input), 0, input->bytes); #endif @@ -157,9 +168,10 @@ // TODO(michaelbrooks): Possibly set/verify test data? for (int i = 0; i < iterations; ++i) { #if (TEST_DATA_INPUT == 1) - memcpy(tflite::GetTensorData<uint8_t>(input), g_benchmark_input, input->bytes); + memcpy(tflite::GetTensorData<uint8_t>(input), g_benchmark_input, + input->bytes); #else - memset(tflite::GetTensorData<uint8_t>(input), 0, input->bytes); + memset(tflite::GetTensorData<uint8_t>(input), 0, input->bytes); #endif interpreter->Invoke(); }
diff --git a/benchmarks/benchmarks.bzl b/benchmarks/benchmarks.bzl index 8ad5f0a..c622c99 100644 --- a/benchmarks/benchmarks.bzl +++ b/benchmarks/benchmarks.bzl
@@ -25,7 +25,7 @@ test_data_output = None, profile = False, kelvin_binary_info = None, - benchmark_path = "benchmarks", + benchmark_path = "benchmarks/", hw_test_size = "medium", hw_test_tags = [], iss_test_size = "small", @@ -103,7 +103,7 @@ test_data = None, profile = False, kelvin_binary_info = None, - benchmark_path = "benchmarks", + benchmark_path = "benchmarks/", **kwargs): _kelvin_benchmark_device( name = name, @@ -124,7 +124,7 @@ test_data = None, profile = False, kelvin_binary_info = None, - benchmark_path = "benchmarks", + benchmark_path = "benchmarks/", **kwargs): _kelvin_benchmark_device( name = name, @@ -145,7 +145,7 @@ test_data = None, profile = False, kelvin_binary_info = None, - benchmark_path = "benchmarks", + benchmark_path = "benchmarks/", **kwargs): kelvin_benchmark_asic( name = "{}_asic".format(name), @@ -188,7 +188,7 @@ test_data_output = None, profile = False, kelvin_binary_info = None, - benchmark_path = "benchmarks", + benchmark_path = "benchmarks/", arena_size_bytes = 1536 * 1024, # 1.5MB tags = [], **kwargs):