1d array to one hot

One hot encoding numpy

  labels = (np.arange(num_labels) == labels[:,None]).astype(np.float32)

1d array to one hot

>>> a = np.array([1, 0, 3])
>>> b = np.zeros((a.size, a.max()+1))
>>> b[np.arange(a.size),a] = 1
>>> b
array([[ 0.,  1.,  0.,  0.],
       [ 1.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  1.]])

Source: stackoverflow.com

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