加载config文件方式

从开源项目学来的，

config.ini

[strings]
# Mode : train, test, serve
mode = train
train_enc = data/train.enc
train_dec = data/train.dec
test_enc = data/test.enc
test_dec = data/test.dec
# folder where checkpoints, vocabulary, temporary data will be stored
working_directory = working_dir/
[ints]
# vocabulary size
#  20,000 is a reasonable size
enc_vocab_size = 20000
dec_vocab_size = 20000
# number of LSTM layers : 1/2/3
num_layers = 3
# typical options : 128, 256, 512, 1024
layer_size = 256
# dataset size limit; typically none : no limit
max_train_data_size = 0
batch_size = 64
# steps per checkpoint
#  Note : At a checkpoint, models parameters are saved, model is evaluated
#        and results are printed
steps_per_checkpoint = 300
[floats]
learning_rate = 0.5
learning_rate_decay_factor = 0.99
max_gradient_norm = 5.0

from configparser import SafeConfigParser


def get_config(config_file='seq2seq.ini'):
    parser = SafeConfigParser()
    parser.read(config_file)
    # get the ints, floats and strings
    _conf_ints = [ (key, int(value)) for key,value in parser.items('ints') ]
    _conf_floats = [ (key, float(value)) for key,value in parser.items('floats') ]
    _conf_strings = [ (key, str(value)) for key,value in parser.items('strings') ]
    return dict(_conf_ints + _conf_floats + _conf_strings)

mydict=get_config()
print(mydict)