Fallback is failing for parallel numpy function

[reazulhoque]

Reporting a bug

• I have tried using the latest released version of Numba (most recent is
  visible in the change log (https://github.com/numba/numba/blob/master/CHANGE_LOG).
• I have included below a minimal working reproducer (if you are unsure how
  to write one see http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports).

reproducer

import numpy as np
from numba import dppl, njit, prange
import dpctl

@njit
def fallback(a):
    return np.amax(a)


a = np.ones(10)
if dpctl.has_gpu_queues():
    with dpctl.device_context("opencl:gpu"):
        fallback_result = fallback(a)