AutoScheduler fails to generate sketches for operator net

I am trying to use AutoScheduler to tune a net of TOPI operators, but the tuning seems to fail to generate any sketches.

I have defined the net as follows:

@auto_scheduler.register_workload
def func():
    IB = te.placeholder((768,), dtype='float32')
    IB_2 = topi.power(IB, 2)  # Square
    IB_6 = 0.0010000000474974513  # Const
    IB_4 = 0.9990000128746033  # Const
    IB_2 = topi.multiply(IB_6, IB_2)
    IB_5 = te.placeholder((768,), dtype='float32')
    IB_4 = topi.multiply(IB_4, IB_5)
    IB = topi.add(IB_4, IB_2)
    IB_5 = 0.10000000149011612  # Const
    IB_4 = 0.8999999761581421  # Const
    IB_2 = 9.999999974752427e-07  # Const
    IB_6 = topi.sqrt(IB)
    IB_8 = te.placeholder((768,), dtype='float32')
    IB_5 = topi.multiply(IB_5, IB_8)
    IB_7 = te.placeholder((768,), dtype='float32')
    IB_4 = topi.multiply(IB_4, IB_7)
    IB_2 = topi.add(IB_6, IB_2)
    IB_4 = topi.add(IB_4, IB_5)
    IB_2 = topi.divide(IB_4, IB_2)
    IB_3 = te.var(dtype='float32')
    IB_2 = topi.multiply(IB_3, IB_2)
    IB_1 = te.placeholder((768,), dtype='float32')
    OB = topi.subtract(IB_1, IB_2)
    return [IB_1,IB_7,IB_8,IB_5,IB , OB]

I am calling AutoScheduler like this:

target = tvm.target.Target('opencl')
task = auto_scheduler.SearchTask(func=func, target=target, hardware_params=hardware_params)
measure_ctx = auto_scheduler.LocalRPCMeasureContext(min_repeat_ms=300, timeout=600)
tune_option = auto_scheduler.TuningOptions(
    num_measure_trials=trials,
    measure_callbacks=[auto_scheduler.RecordToFile(logfile)],
    verbose=1,
    runner=measure_ctx.runner
)
task.tune(tune_option)

This is the tuner’s output

----------------------------------------------------------------------
------------------------------  [ Search ]
----------------------------------------------------------------------
Generate Sketches               #s: 1
Sample Iter: 5  #Pop: 0 #Target: 50     fail_ct: 10240  Time elapsed: 22.54
#Target has been reduced to 25 due to too many failures or duplications
Sample Iter: 10 #Pop: 0 #Target: 25     fail_ct: 20480  Time elapsed: 42.35
#Target has been reduced to 12 due to too many failures or duplications
Sample Iter: 15 #Pop: 0 #Target: 12     fail_ct: 30720  Time elapsed: 62.17
#Target has been reduced to 6 due to too many failures or duplications
Sample Iter: 20 #Pop: 0 #Target: 6      fail_ct: 40960  Time elapsed: 81.98
#Target has been reduced to 3 due to too many failures or duplications
Sample Iter: 25 #Pop: 0 #Target: 3      fail_ct: 51200  Time elapsed: 101.80
#Target has been reduced to 1 due to too many failures or duplications
Sample Iter: 30 #Pop: 0 #Target: 1      fail_ct: 61440  Time elapsed: 121.61
Sample Iter: 35 #Pop: 0 #Target: 1      fail_ct: 71680  Time elapsed: 141.42
Sample Iter: 40 #Pop: 0 #Target: 1      fail_ct: 81920  Time elapsed: 161.23
Sample Iter: 45 #Pop: 0 #Target: 1      fail_ct: 92160  Time elapsed: 181.06
Sample Iter: 50 #Pop: 0 #Target: 1      fail_ct: 102400 Time elapsed: 200.87
Sample Iter: 55 #Pop: 0 #Target: 1      fail_ct: 112640 Time elapsed: 220.66
Sample Iter: 60 #Pop: 0 #Target: 1      fail_ct: 122880 Time elapsed: 240.46
Sample Iter: 65 #Pop: 0 #Target: 1      fail_ct: 133120 Time elapsed: 260.26
Sample Iter: 70 #Pop: 0 #Target: 1      fail_ct: 143360 Time elapsed: 280.07
Sample Iter: 75 #Pop: 0 #Target: 1      fail_ct: 153600 Time elapsed: 299.87
Sample Iter: 80 #Pop: 0 #Target: 1      fail_ct: 163840 Time elapsed: 319.67
Sample Iter: 85 #Pop: 0 #Target: 1      fail_ct: 174080 Time elapsed: 339.48
Sample Iter: 90 #Pop: 0 #Target: 1      fail_ct: 184320 Time elapsed: 359.29
Sample Iter: 95 #Pop: 0 #Target: 1      fail_ct: 194560 Time elapsed: 379.10
Sample Iter: 100        #Pop: 0 #Target: 1      fail_ct: 204800 Time elapsed: 398.90

...

Sample Iter: 3345       #Pop: 0 #Target: 1      fail_ct: 6850560        Time elapsed: 13263.46
Sample Iter: 3350       #Pop: 0 #Target: 1      fail_ct: 6860800        Time elapsed: 13283.27
Sample Iter: 3355       #Pop: 0 #Target: 1      fail_ct: 6871040        Time elapsed: 13303.08

As you can see it is still generating sketches after more than 3h. Is this expected and can I expect that this will be finished some time or is AutoScheduler not able to find anything for my specific net? I have used AutoScheduler for single operators without a problem.

Many thanks in advance!

The tuning did not find any valid schedules even after 24h. Do you have any suggestions how to solve this? Would using schedules provided in TOPI be the best alternative to get the best performance out of TVM?