ValueError: 'axis' entry is out of bounds in acgan_unsw.py

[deepakkuk]

alueError Traceback (most recent call last) in () 120 121 # Generate fake attacking data using GAN --> 122 fake_dataset, fake_labels = generate_fake_data(train_dataset, train_labels) 123 # Mix fake and real data to do supervised learning 124 mixed_dataset = np.concatenate((train_dataset, fake_dataset), axis=0)

in generate_fake_data(dataset, labels) 39 # Plot 100 samples of real/fake data 40 plot_traffic_as_image(dataset, labels, attack_signature, ---> 41 'real_attack', 100, gan.dirname) 42 plot_traffic_as_image(dataset, labels, normal_signature, 43 'real_normal', 100, gan.dirname)

/workspace/text2/netlearner/utils.pyc in plot_traffic_as_image(dataset, labels, signiture, name, num_samples, dirname) 335 def plot_traffic_as_image(dataset, labels, signiture, 336 name, num_samples, dirname='UNSW'): --> 337 index = np.where(np.all(labels == signiture, axis=1))[0] 338 matches = dataset[index, :] 339 print('Real %s set' % name, matches.shape)

/usr/local/lib/python2.7/dist-packages/numpy/core/fromnumeric.pyc in all(a, axis, out, keepdims) 2040 2041 try: -> 2042 return arr.all(axis=axis, out=out, keepdims=keepdims) 2043 except TypeError: 2044 return arr.all(axis=axis, out=out)

/usr/local/lib/python2.7/dist-packages/numpy/core/_methods.pyc in _all(a, axis, dtype, out, keepdims) 39 40 def _all(a, axis=None, dtype=None, out=None, keepdims=False): ---> 41 return umr_all(a, axis, dtype, out, keepdims) 42 43 def _count_reduce_items(arr, axis):

ValueError: 'axis' entry is out of bounds