The np.argsort function also only applies to a single dimension (axis), even with Numpy. The default of Numpy is to apply it to the last axis when unspecified, or on the flattened array with axis=None.
So you could implement that with Numba for example using the guvectorize decorator, which also adds the axis keyword with the same default as Numpy (axis=-1).
For example:
from numba import njit, guvectorize
import numpy as np
@guvectorize("void(float32[:], int64[:])", "(n)->(n)")
def foo(arr, out):
out[:] = np.argsort(arr)
That should match Numpy, for example sorting over the default last axis: