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convert.py
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convert.py
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#!/usr/bin/env python
import os
import sys
import numpy as np
import argparse
from kaffe import KaffeError, print_stderr
from kaffe.tensorflow import TensorFlowTransformer
def fatal_error(msg):
print_stderr(msg)
exit(-1)
def validate_arguments(args):
if (args.data_output_path is not None) and (args.caffemodel is None):
fatal_error('No input data path provided.')
if (args.caffemodel is not None) and (args.data_output_path is None):
fatal_error('No output data path provided.')
if (args.code_output_path is None) and (args.data_output_path is None):
fatal_error('No output path specified.')
def convert(def_path, caffemodel_path, data_output_path, code_output_path, phase):
try:
transformer = TensorFlowTransformer(def_path, caffemodel_path, phase=phase)
print_stderr('Converting data...')
if caffemodel_path is not None:
data = transformer.transform_data()
print_stderr('Saving data...')
with open(data_output_path, 'wb') as data_out:
np.save(data_out, data)
if code_output_path:
print_stderr('Saving source...')
with open(code_output_path, 'wb') as src_out:
src_out.write(transformer.transform_source())
print_stderr('Done.')
except KaffeError as err:
fatal_error('Error encountered: {}'.format(err))
def main():
parser = argparse.ArgumentParser()
parser.add_argument('def_path', help='Model definition (.prototxt) path')
parser.add_argument('--caffemodel', help='Model data (.caffemodel) path')
parser.add_argument('--data-output-path', help='Converted data output path')
parser.add_argument('--code-output-path', help='Save generated source to this path')
parser.add_argument('-p',
'--phase',
default='test',
help='The phase to convert: test (default) or train')
args = parser.parse_args()
validate_arguments(args)
convert(args.def_path, args.caffemodel, args.data_output_path, args.code_output_path,
args.phase)
if __name__ == '__main__':
main()