65 lines
2.0 KiB
Python
65 lines
2.0 KiB
Python
# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
|
|
#
|
|
# 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.
|
|
# ==============================================================================
|
|
r"""Randomize all weights in a tflite file.
|
|
|
|
Example usage:
|
|
python randomize_weights.py \
|
|
--input_tflite_file=foo.tflite \
|
|
--output_tflite_file=foo_randomized.tflite
|
|
"""
|
|
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
|
|
import argparse
|
|
import sys
|
|
|
|
from tensorflow.lite.tools import flatbuffer_utils
|
|
from tensorflow.python.platform import app
|
|
|
|
|
|
def main(_):
|
|
parser = argparse.ArgumentParser(
|
|
description='Randomize weights in a tflite file.')
|
|
parser.add_argument(
|
|
'--input_tflite_file',
|
|
type=str,
|
|
required=True,
|
|
help='Full path name to the input tflite file.')
|
|
parser.add_argument(
|
|
'--output_tflite_file',
|
|
type=str,
|
|
required=True,
|
|
help='Full path name to the output randomized tflite file.')
|
|
parser.add_argument(
|
|
'--random_seed',
|
|
type=str,
|
|
required=False,
|
|
default=0,
|
|
help='Input to the random number generator. The default value is 0.')
|
|
args = parser.parse_args()
|
|
|
|
# Read the model
|
|
model = flatbuffer_utils.read_model(args.input_tflite_file)
|
|
# Invoke the randomize weights function
|
|
flatbuffer_utils.randomize_weights(model, args.random_seed)
|
|
# Write the model
|
|
flatbuffer_utils.write_model(model, args.output_tflite_file)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
app.run(main=main, argv=sys.argv[:1])
|