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