I am trying to tune MobileNetV3-minmalistic TF Lite Model with TVM targeting arm_cpu. I tuned model for MobileNetV3 without error log with n_trial = 1500, early_stopping = 100. But when I set early_stopping to None, autotvm turn into debug mode with below log.
WARNING:autotvm:Too many errors happen in the tuning. Now is in debug mode
DEBUG:autotvm:No: 217 GFLOPS: 0.00/0.00 result: MeasureResult(costs=(TimeoutError(),), error_no=6, all_cost=10, timestamp=1581575643.881052) [('tile_co', [-1, 1]), ('tile_oh', [-1, 1]), ('tile_ow', [-1, 1]), ('reorder_conv', [0, 1, 2, 3, 7, 4, 5, 6, 8, 9]), ('ann_reduce'
, ['none', 'unroll']), ('ann_spatial', ['unroll', 'none', 'unroll']), ('compat', 1)],direct,None,3752
DEBUG:autotvm:No: 218 GFLOPS: 0.00/0.00 result: MeasureResult(costs=(InstantiationError(['Too large factor for unrolling', 'Too large factor for unrolling'],),), error_no=1, all_cost=0.024065017700195312, timestamp=1581575643.8814123) [('tile_co', [-1, 1001]), ('tile_o
h', [-1, 1]), ('tile_ow', [-1, 1]), ('reorder_conv', [0, 1, 2, 7, 3, 4, 5, 8, 6, 9]), ('ann_reduce', ['none', 'none']), ('ann_spatial', ['unroll', 'vec', 'unroll']), ('compat', 0)],direct,None,1951
DEBUG:autotvm:No: 219 GFLOPS: 0.00/0.00 result: MeasureResult(costs=(TimeoutError(),), error_no=6, all_cost=10, timestamp=1581575643.9419343) [('tile_co', [-1, 91]), ('tile_oh', [-1, 1]), ('tile_ow', [-1, 1]), ('reorder_conv', [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), ('ann_reduce
', ['none', 'unroll']), ('ann_spatial', ['vec', 'none', 'none']), ('compat', 2)],direct,None,7205
Since I see TimeoutError() in debug message, I tried to replace timeout from 10 to 1000 according to other issue, but still got same result. Although there are many error log, Some tasks have non-zero GFLOPS. Then does the tuning process work correctly?
To share my tuning script,
I use tune_and_evaluate same as tune_relay_arm.py. But for using my TF Lite model, I disable get_network and use mod, params, input_shape returns from from_tflite() like below code
tflite_model_buf = open(TFLITE_PATH, "rb").read()
tflite_model = tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0)
input_shape = (1,224,224,3)
mod, params = relay.frontend.from_tflite(tflite_model,
shape_dict={
"input": input_shape},
dtype_dict={"input": "float32"})
tune_and_evaluate(tuning_option, mod, params, input_shape)
And I use below tuning option
tuning_option = {
'log_filename': log_file,
'tuner': 'ga',
'n_trial': 1500,
'early_stopping': None,
'measure_option': autotvm.measure_option(
builder=autotvm.LocalBuilder(
build_func='ndk' if use_android else 'default'),
runner=autotvm.RPCRunner(
device_key, host='0.0.0.0', port=9190,
number=5,
timeout=1000,
),
)
}
(I used GATuner cause XGBTuner raised below error)
