[FIXED] Getting {ValueError} 'a' must be 1-dimensoinal for list of lists from np.random.choice

Issue

I want to create a toy training set from the XOR function:

xor = [[0, 0, 0],
       [0, 1, 1],
       [1, 0, 1],
       [1, 1, 0]]

input_x = np.random.choice(a=xor, size=200)

However, this is giving me

{ValueError} 'a' must be 1-dimensoinal

But, if I add e.g. a number to this list:

xor = [[0, 0, 0],
       [0, 1, 1],
       [1, 0, 1],
       [1, 1, 0],
       1337]       # With this it will work

input_x = np.random.choice(a=xor, size=200)

it starts to work. Why is this the case and how can I make this work without having to add another primitive to the xor list?

Solution

In case of an array I would do the following:

xor = np.array([[0,0,0],
       [0,1,1],
       [1,0,1],
       [1,1,0]])
rnd_indices = np.random.choice(len(xor), size=200)

xor_data = xor[rnd_indices]

Answered By - BloodyD