def main():
logging.basicConfig(level=logging.INFO)
modules = load_config(MODULES_CONFIG_FILENAME)
arg_parser = build_arg_parser(modules['arg_parser'])
ote_args = vars(arg_parser.get_compression_parser(MODEL_TEMPLATE_FILENAME).parse_args())
if 'compression' not in modules:
raise RuntimeError(f'Cannot make compression for the template that'
f' does not have "compression" field in its modules'
f' file {MODULES_CONFIG_FILENAME}')
if not is_optimisation_enabled_in_template(MODEL_TEMPLATE_FILENAME):
raise RuntimeError(f'Cannot make compression for the template that'
f' does not enable any of compression flags')
arg_converter = build_arg_converter(modules['arg_converter_map'])
compress_args = arg_converter.convert_compress_args(ote_args)
compression_arg_transformer = build_compression_arg_transformer(modules['compression'])
compress_args, is_optimisation_enabled = \
compression_arg_transformer.process_args(MODEL_TEMPLATE_FILENAME, compress_args)
if not is_optimisation_enabled:
logging.warning('Optimization flags are not set -- compression is not made')
return
# Note that compression in this tool will be made by the same trainer,
# as in the tool train.py
# The difference is only in the argparser and in the NNCFConfigTransformer used to
# transform the configuration file.
trainer = build_trainer(modules['trainer'])
trainer(**compress_args)
def main():
modules = load_config(MODULES_CONFIG_FILENAME)
arg_parser = build_arg_parser(modules['arg_parser'])
ote_args = vars(arg_parser.get_test_parser(MODEL_TEMPLATE_FILENAME).parse_args())
arg_converter = build_arg_converter(modules['arg_converter_map'])
eval_args = arg_converter.convert_test_args(ote_args)
if modules.get('compression') and is_optimisation_enabled_in_template(MODEL_TEMPLATE_FILENAME):
compression_arg_transformer = build_compression_arg_transformer(modules['compression'])
eval_args, _ = compression_arg_transformer.process_args(MODEL_TEMPLATE_FILENAME, eval_args)
evaluator = build_evaluator(modules['evaluator'])
evaluator(**eval_args)
def main():
logging.basicConfig(level=logging.INFO)
modules = load_config(MODULES_CONFIG_FILENAME)
arg_parser = build_arg_parser(modules['arg_parser'])
ote_args = vars(
arg_parser.get_export_parser(MODEL_TEMPLATE_FILENAME).parse_args())
if modules.get('compression') and is_optimisation_enabled_in_template(
MODEL_TEMPLATE_FILENAME):
compression_arg_transformer = build_compression_arg_transformer(
modules['compression'])
ote_args, _ = compression_arg_transformer.process_args(
MODEL_TEMPLATE_FILENAME, ote_args)
exporter = build_exporter(modules['exporter'])
exporter(ote_args)
def apply_update_dict_params_to_template_file(template_file, template_update_dict, compression_cfg_update_dict):
template_data = mmcv.Config.fromfile(template_file)
template_data.dump(template_file + '.backup.yaml')
assert is_optimisation_enabled_in_template(template_data), \
f'Template {template_file} does not contain optimisation part'
if compression_cfg_update_dict:
compression_cfg_rel_path = get_optimisation_config_from_template(template_data)
compression_cfg_path = os.path.join(os.path.dirname(template_file), compression_cfg_rel_path)
backup_compression_cfg_path = compression_cfg_path + '.BACKUP_FROM_TEST.json'
compression_cfg = mmcv.Config.fromfile(compression_cfg_path)
compression_cfg.dump(backup_compression_cfg_path)
compression_cfg.merge_from_dict(compression_cfg_update_dict)
compression_cfg.dump(compression_cfg_path)
template_data.merge_from_dict(template_update_dict)
template_data.dump(template_file)
def _is_optimisation_enabled_in_template(*args, **kwargs):
from ote.modules.compression import is_optimisation_enabled_in_template
return is_optimisation_enabled_in_template(*args, **kwargs)