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I have developed a code for searching different CNN models with a specific number of parameters, however after an architecture sampled during the optimization that exceeds the number of parameters, it stops searching by raising an error of "Oversized model: 180376 parameters. Skip model."
Expected behavior
It should skip that specific model and takes the second sample until it finishes the maximum number of trials.
The text was updated successfully, but these errors were encountered:
I am not familiar with Github, but basically this is what I made, it worked fine :)
I made a small variable outside get_model.
__run_once = True
This is the code, hope it will help!
__run_once = True # set this True, if the code suddenly stops after at least one tuning you need to edit it and set it to False
def get_model(args, hp):
global __run_once
trial_param1 = hp.Int("num_layers", 1, 30, step=1)
trial_param2 = hp.Choice("num_filters", [16, 32, 64])
trial_param3 = hp.Choice("dp_rate1", [0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
trial_param4 = hp.Choice("dp_rate2", [0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
trial_param5 = hp.Boolean("use_bias")
m = build_model_with_params(args, trial_param1, trial_param2, trial_param3, trial_param4, trial_param5)
if __run_once:
__run_once = False
return None
return m
Describe the bug
I have developed a code for searching different CNN models with a specific number of parameters, however after an architecture sampled during the optimization that exceeds the number of parameters, it stops searching by raising an error of "Oversized model: 180376 parameters. Skip model."
Expected behavior
It should skip that specific model and takes the second sample until it finishes the maximum number of trials.
The text was updated successfully, but these errors were encountered: