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// Copyright (c) 2020-2022, ARM Limited.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include <cxxopts.hpp>
#include <ctype.h>
#include <signal.h>
#include <stdarg.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <sys/types.h>
#include "func_config.h"
#include "func_debug.h"
// Read the command line arguments
int func_model_parse_cmd_line(
func_config_t& func_config, func_debug_t& func_debug, int argc, char** argv, const char* version)
{
try
{
cxxopts::Options options("tosa_reference_model", "The TOSA reference model");
// clang-format off
options.add_options()
("operator_fbs", "Flat buffer schema file", cxxopts::value<std::string>(func_config.operator_fbs), "<schema>")
("test_desc", "Json test descriptor", cxxopts::value<std::string>(func_config.test_desc), "<descriptor>")
("flatbuffer_dir", "Flatbuffer directory to load. If not specified, it will be overwritten by dirname(test_desc)",
cxxopts::value<std::string>(func_config.flatbuffer_dir))
("output_dir", "Output directory to write. If not specified, it will be overwritten by dirname(test_desc)",
cxxopts::value<std::string>(func_config.output_dir))
("tosa_file", "Flatbuffer file. Support .json or .tosa. Specifying this will overwrite the one initialized by --test_desc.",
cxxopts::value<std::string>(func_config.tosa_file))
("ifm_name", "Input tensor name. Comma(,) separated. Specifying this will overwrite the one initialized by --test_desc.",
cxxopts::value<std::string>(func_config.ifm_name))
("ifm_file", "Input tensor numpy Comma(,) separated. file to initialize with placeholder. Specifying this will overwrite the one initialized by --test_desc.",
cxxopts::value<std::string>(func_config.ifm_file))
("ofm_name", "Output tensor name. Comma(,) seperated. Specifying this will overwrite the one initialized by --test_desc.",
cxxopts::value<std::string>(func_config.ofm_name))
("ofm_file", "Output tensor numpy file to be generated. Comma(,) seperated. Specifying this will overwrite the one initialized by --test_desc.",
cxxopts::value<std::string>(func_config.ofm_file))
("eval", "Evaluate the network (0/1)", cxxopts::value<uint32_t>(func_config.eval))
("fp_format", "Floating-point number dump format string (printf-style format, e.g. 0.5)",
cxxopts::value<std::string>(func_config.fp_format))
("validate_only", "Validate the network, but do not read inputs or evaluate (0/1)",
cxxopts::value<uint32_t>(func_config.validate_only))
("output_tensors", "Output tensors to a file (0/1)", cxxopts::value<uint32_t>(func_config.output_tensors))
("tosa_profile", "Set TOSA profile (0 = Base Inference, 1 = Main Inference, 2 = Main Training)",
cxxopts::value<uint32_t>(func_config.tosa_profile))
("dump_intermediates", "Dump intermediate tensors (0/1)", cxxopts::value<uint32_t>(func_config.dump_intermediates))
("v,version", "print model version")
("i,input_tensor_file", "specify input tensor files", cxxopts::value<std::vector<std::string>>())
("l,loglevel", func_debug.get_debug_verbosity_help_string(), cxxopts::value<std::string>())
("o,logfile", "output log file", cxxopts::value<std::string>())
("d,debugmask", func_debug.get_debug_mask_help_string(), cxxopts::value<std::vector<std::string>>())
("h,help", "print help");
// clang-format on
auto result = options.parse(argc, argv);
if (result.count("help")) {
std::cout << options.help() << std::endl;
return 1;
}
if (result.count("debugmask")) {
auto& v = result["debugmask"].as<std::vector<std::string>>();
for (const std::string& s : v)
func_debug.set_mask(s);
}
if (result.count("loglevel")) {
const std::string& levelstr = result["loglevel"].as<std::string>();
func_debug.set_verbosity(levelstr);
}
if (result.count("logfile")) {
func_debug.set_file(result["logfile"].as<std::string>());
}
if (result.count("input_tensor_file")) {
func_config.ifm_name = result["input_tensor_file"].as<std::string>();
}
if (result.count("version")) {
std::cout << "Model version " << version << std::endl;
}
}
catch(const std::exception& e)
{
std::cerr << e.what() << '\n';
return 1;
}
return 0;
}
void func_model_print_help()
{
}
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