def main():
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument('read_path')
arg_parser.add_argument('write_path')
args = arg_parser.parse_args()
with open(args.read_path, 'r') as source:
text = source.read()
lexer = Lexer(text)
tokens = lexer.lex()
parser = Parser(tokens)
ast = parser.parse()
symbolizer = Symbolizer(ast)
symbolizer.symbolize()
optimizer = Optimizer(ast)
optimizer.optimize()
grapher = Grapher(ast)
grapher.graph()
generator = Generator(ast)
generator.generate(args.write_path)
runner = Runner(ast)
runner.run()
def main():
try:
config = Config.load()
init_logging(config)
runner = Runner(config)
runner.run()
return 0
except KeyboardInterrupt:
_logger.info("aborted.")
return 0
except MessageException as ex:
_logger.error(ex)
_logger.error("aborted!")
return 1
except Exception as ex:
_logger.exception(ex)
_logger.error("aborted!")
# no runner.close() to signal abnormal termination!
return 1
def main(is_debug):
""" Training Pipeline
"""
with open("./config.yaml") as yf:
config = yaml.safe_load(yf)
# run single models
for config_ in config["models"]:
pprint.pprint(config_)
runner = Runner(settings, AttrDict(config_))
runner.run(is_debug=args.debug, multi_gpu=args.multi_gpu)
import sys import os from src.runner import Runner runner = Runner() runner.run()
