zhusuan
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The examples of ‘semi_supervised_vae’ cannot run successfully
There seems to be some little bugs in these examples. For example
for t in range(iters): labeled_indices = (np.random.randint(0, n_labeled, size=batch_size)) x_labeled_batch = x_labeled[labeled_indices]
It throws the error that
TypeError: Only integers, slices (
:), ellipsis (
...), tf.newaxis (
None) and scalar tf.int32/tf.int64 tensors are valid indices, got array([17, 13, 15, 32, 80, 63, 47, 90, 90, 15, 23, 75, 51, 82, 10, 77, 5, 56, 54, 4, 63, 21, 11, 82, 36, 46, 85, 59, 38, 28, 40, 8, 28, 56, 56, 28, 25, 56, 75, 39, 52, 12, 18, 24, 22, 61, 93, 74, 18, 39, 97, 84, 67, 70, 20, 83, 90, 10, 1, 4, 63, 13, 19, 98, 65, 74, 82, 39, 54, 79, 92, 19, 6, 56, 82, 20, 61, 82, 88, 85, 9, 80, 40, 6, 21, 85, 8, 74, 78, 23, 27, 72, 37, 31, 20, 76, 97, 91, 87, 25])
in in line 154, in main
labeled_indices = (np.random.randint(0, n_labeled, size=batch_size))
And I use
labeled_indices = (np.random.randint(0, n_labeled, size=batch_size)).tolist()
It throws the error that
ValueError: Value out of range: 1267650600228229401496703205375
in line 155, in main
x_labeled_batch = x_labeled[labeled_indices]
Hello! Sorry for the very late reply. The issue is fixed as in #127. Thank you for your comment!