'beta_2': 0.999,
'decay': 0,
'amsgrad': False
}
short_opt = {k: [v] for k, v in default_opt.items() if k != 'opt'}
Opt_dict = {'Adam': [Adam, short_opt]}
SO = Hyperparameters.Optimizers(Opt_dict)
default_parameters = {
'opt': default_opt,
'augment': default_IDG,
'arch': default_UNET
}
# plan = [{'arch':M},{'opt':O}]
# plan = [{'arch':SM},{'opt':O}]
# plan = [{'opt':O}]
plan = [{'arch': M}]
t = Testing.Trainer(default_parameters)
print('Variables intialized')
t.execute(plan,
ds,
directory='gridsearch7/',
update_best_para=True,
resume=True,
n_splits=3)
