| import os |
| import argparse |
| import logging |
| logging.basicConfig(level=logging.DEBUG) |
| from common import find_mxnet, data, fit |
| from common.util import download_file |
| import mxnet as mx |
| |
| def download_cifar10(): |
| data_dir="data" |
| fnames = (os.path.join(data_dir, "cifar10_train.rec"), |
| os.path.join(data_dir, "cifar10_val.rec")) |
| download_file('http://data.mxnet.io/data/cifar10/cifar10_val.rec', fnames[1]) |
| download_file('http://data.mxnet.io/data/cifar10/cifar10_train.rec', fnames[0]) |
| return fnames |
| |
| if __name__ == '__main__': |
| # download data |
| (train_fname, val_fname) = download_cifar10() |
| |
| # parse args |
| parser = argparse.ArgumentParser(description="train cifar10", |
| formatter_class=argparse.ArgumentDefaultsHelpFormatter) |
| fit.add_fit_args(parser) |
| data.add_data_args(parser) |
| data.add_data_aug_args(parser) |
| data.set_data_aug_level(parser, 2) |
| parser.set_defaults( |
| # network |
| network = 'resnet', |
| num_layers = 110, |
| # data |
| data_train = train_fname, |
| data_val = val_fname, |
| num_classes = 10, |
| num_examples = 50000, |
| image_shape = '3,28,28', |
| pad_size = 4, |
| # train |
| batch_size = 128, |
| num_epochs = 300, |
| lr = .05, |
| lr_step_epochs = '200,250', |
| ) |
| args = parser.parse_args() |
| |
| # load network |
| from importlib import import_module |
| net = import_module('symbols.'+args.network) |
| sym = net.get_symbol(**vars(args)) |
| |
| # train |
| fit.fit(args, sym, data.get_rec_iter) |