numpy.take fails with int64 dtype on i386 architecture

Reproducing code example:

import numpy as np
x = np.arange(10, dtype='int64')
index = np.arange(3, dtype='int64')
x.take(index)

Expected output:

array([0, 1, 2])

is obtained on 64 bit architecture

Error message:

On 32 bit Debian Linux, I get,

>>> x.take(index)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: Cannot cast array data from dtype('int64') to dtype('int32') according to the rule 'safe'

On 32 bit windows, the same result was indirectly illustrated in scikit-learn/scikit-learn#11295 (comment)

Numpy/Python version information:

>>> import sys, numpy; print(numpy.__version__, sys.version)
1.14.5 3.6.6 (default, Jun 27 2018, 14:44:17) 
[GCC 8.1.0]

Generally this was run in the debian unstable i386 Docker image, with the following setup,

FROM i386/debian:unstable

RUN apt-get update && apt-get install -y build-essential git make

RUN apt-get install -y python3 python3-scipy python3-numpy python3-setuptools python3-pkg-resources python3-pip