There appears to be some issue regarding the interoperability between numpy and arrayfire-python regarding certain data types.
I did the conversion using the methods:

# numpy to arrayfireaf.interop.np_to_af_array# arrayfire to numpyaf.Array.__array__()

The only two data types which appear to work as intended arefloat anddouble (f32 andf64 in Arrayfire,np.float32 andnp.float64 in numpy).

64 bit integer values (signed and unsigned) and bool appear to be not supported (KeyError when trying to convert), but the data typesu8,u32 ands32 are not converted correctly.

An example:

nparr = np.array([5, 10, 15, 20, 25, 30], np.int)print(nparr)# Output: [ 5 10 15 20 25 30]afarr = af.interop.np_to_af_array(nparr)print(afarr)# Output:# arrayfire.Array()# Type: long int# [6 1 1 1]#42949672965 #85899345935 #128849018905 # -7780732514909268839 #0#0afarr += 10print(afarr.__array__())# Output: [25 10 35 20 45 30] instead of [25, 30, 35, 40, 45, 50]# Ten was only added to every second value!

I tried these conversions with all of the aforementioned datatypes

I am using ArrayFire v3.3.2 (buildf65dd97) with Python 3.5.2 on 64bit Windows