def main(args):
with open(os.path.join(args.model, 'params.json'), 'r') as f:
params = json.loads(f.read())
params.update(vars(args))
params = namedtuple('Params', params.keys())(*params.values())
dataset = data.Dataset(args.dataset)
x = tf.placeholder(tf.int32, shape=(None, None), name='x')
seq_lengths = tf.placeholder(tf.int32, shape=(None), name='seq_lengths')
model = m.DocNADE(x, seq_lengths, params)
evaluate(model, dataset, params)
def main(args):
if not os.path.isdir(args.model):
os.mkdir(args.model)
with open(os.path.join(args.model, 'params.json'), 'w') as f:
f.write(json.dumps(vars(args)))
dataset = data.Dataset(args.dataset)
x = tf.placeholder(tf.int32, shape=(None, None), name='x')
seq_lengths = tf.placeholder(tf.int32, shape=(None), name='seq_lengths')
model = m.DocNADE(x, seq_lengths, args)
train(model, dataset, args)