def __init__(self,
channel_1_num,
channel_2_num,
conv_size,
hidden_size,
pool_size,
learning_rate,
x_dim=784,
y_dim=10):
self.channel_1_num = channel_1_num
self.channel_2_num = channel_2_num
self.conv_size = nni.choice(2, 3, 5, 7, name='self.conv_size')
self.hidden_size = nni.choice(124, 512, 1024, name='self.hidden_size')
self.pool_size = pool_size
self.learning_rate = nni.uniform(0.0001,
0.1,
name='self.learning_rate')
self.x_dim = x_dim
self.y_dim = y_dim
self.images = tf.placeholder(tf.float32, [None, self.x_dim],
name='input_x')
self.labels = tf.placeholder(tf.float32, [None, self.y_dim],
name='input_y')
self.keep_prob = tf.placeholder(tf.float32, name='keep_prob')
self.train_step = None
self.accuracy = None
def test_default_name(self):
val = nni.uniform(1, 10) # NOTE: assign this line number to lineno1
self.assertEqual(val, '5')
