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checksum_caffe2.py
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checksum_caffe2.py
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"""
Copyright (C) 2017, 申瑞珉 (Ruimin Shen)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
"""
import os
import argparse
import configparser
import logging
import logging.config
import hashlib
import yaml
import torch
from caffe2.proto import caffe2_pb2
from caffe2.python import workspace
import utils
def main():
args = make_args()
config = configparser.ConfigParser()
utils.load_config(config, args.config)
for cmd in args.modify:
utils.modify_config(config, cmd)
with open(os.path.expanduser(os.path.expandvars(args.logging)), 'r') as f:
logging.config.dictConfig(yaml.load(f))
torch.manual_seed(args.seed)
model_dir = utils.get_model_dir(config)
init_net = caffe2_pb2.NetDef()
with open(os.path.join(model_dir, 'init_net.pb'), 'rb') as f:
init_net.ParseFromString(f.read())
predict_net = caffe2_pb2.NetDef()
with open(os.path.join(model_dir, 'predict_net.pb'), 'rb') as f:
predict_net.ParseFromString(f.read())
p = workspace.Predictor(init_net, predict_net)
height, width = tuple(map(int, config.get('image', 'size').split()))
tensor = torch.randn(1, 3, height, width)
# Checksum
output = p.run([tensor.numpy()])
for key, a in [
('tensor', tensor.cpu().numpy()),
('output', output[0]),
]:
print('\t'.join(map(str, [key, a.shape, utils.abs_mean(a), hashlib.md5(a.tostring()).hexdigest()])))
def make_args():
parser = argparse.ArgumentParser()
parser.add_argument('-c', '--config', nargs='+', default=['config.ini'], help='config file')
parser.add_argument('-m', '--modify', nargs='+', default=[], help='modify config')
parser.add_argument('--logging', default='logging.yml', help='logging config')
parser.add_argument('-s', '--seed', default=0, type=int, help='a seed to create a random image tensor')
return parser.parse_args()
if __name__ == '__main__':
main()