openvino/model-optimizer/mo/back/offline_transformations.py

56 lines
2.2 KiB
Python

# Copyright (C) 2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import argparse
from mo.utils.error import Error
from mo.utils.cli_parser import parse_transform
def get_available_transformations():
try:
from openvino.offline_transformations import ApplyLowLatencyTransformation # pylint: disable=import-error,no-name-in-module
return {
'LowLatency2': ApplyLowLatencyTransformation,
}
except Exception as e:
return {}
# net should be openvino.inference_engine.IENetwork type, but IE Engine is still optional dependency
def apply_moc_transformations(net: object, transforms: list):
from openvino.offline_transformations import ApplyMOCTransformations # pylint: disable=import-error,no-name-in-module
available_transformations = get_available_transformations()
for name, args in transforms:
if name not in available_transformations.keys():
raise Error("Transformation {} is not available.".format(name))
available_transformations[name](net, **args)
ApplyMOCTransformations(net, False)
def apply_offline_transformations(input_model: str, framework: str, transforms: list):
# This variable is only needed by GenerateMappingFile transformation
# to produce correct mapping
extract_names = framework in ['tf', 'mxnet', 'kaldi']
from openvino.inference_engine import read_network # pylint: disable=import-error,no-name-in-module
from openvino.offline_transformations import GenerateMappingFile # pylint: disable=import-error,no-name-in-module
net = read_network(input_model + "_tmp.xml", input_model + "_tmp.bin")
apply_moc_transformations(net, transforms)
net.serialize(input_model + ".xml", input_model + ".bin")
path_to_mapping = input_model + ".mapping"
GenerateMappingFile(net, path_to_mapping.encode('utf-8'), extract_names)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--input_model")
parser.add_argument("--framework")
parser.add_argument("--transform")
args = parser.parse_args()
apply_offline_transformations(args.input_model, args.framework, parse_transform(args.transform))