TypeError: only integer scalar arrays can be converted to a scalar index with 1D numpy indices array
Perhaps the error message is somewhat misleading, but the gist is that X_train
is a list, not a numpy array. You cannot use array indexing on it. Make it an array first:
out_images = np.array(X_train)[indices.astype(int)]
I get this error whenever I use np.concatenate
the wrong way:
>>> a = np.eye(2)
>>> np.concatenate(a, a)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<__array_function__ internals>", line 6, in concatenate
TypeError: only integer scalar arrays can be converted to a scalar index
The correct way is to input the two arrays as a tuple:
>>> np.concatenate((a, a))
array([[1., 0.],
[0., 1.],
[1., 0.],
[0., 1.]])
A simple case that generates this error message:
In [8]: [1,2,3,4,5][np.array([1])]
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-8-55def8e1923d> in <module>()
----> 1 [1,2,3,4,5][np.array([1])]
TypeError: only integer scalar arrays can be converted to a scalar index
Some variations that work:
In [9]: [1,2,3,4,5][np.array(1)] # this is a 0d array index
Out[9]: 2
In [10]: [1,2,3,4,5][np.array([1]).item()]
Out[10]: 2
In [11]: np.array([1,2,3,4,5])[np.array([1])]
Out[11]: array([2])
Basic python list indexing is more restrictive than numpy's:
In [12]: [1,2,3,4,5][[1]]
....
TypeError: list indices must be integers or slices, not list
edit
Looking again at
indices = np.random.choice(range(len(X_train)), replace=False, size=50000, p=train_probs)
indices
is a 1d array of integers - but it certainly isn't scalar. It's an array of 50000 integers. List's cannot be indexed with multiple indices at once, regardless of whether they are in a list or array.