def create_obj_func(params):
if choice_default == 0:
default_params = {
'w_regular': 0.1,
'rf_dim': 400,
'step_size': 0.5,
'x_kernel_width': 0.0001,
'params_kernel_width': 15,
'num_iters': 500,
'num_samples_params': 100,
'batch_size': 100,
'freq_calc_metrics': 1,
}
else:
default_params = {
'cache_size': 50,
'freq_update_full_model': 100,
'num_epochs': 3,
}
default_params = resolve_conflict_params(params, default_params)
# print('Default params:', default_params)
learner = DualSVRG(
**params,
**default_params,
)
return learner
def create_obj_func(params):
if choice_default == 0:
default_params = {
'w_regular': 0.1,
'rf_dim': 400,
'step_size': 0.5,
'x_kernel_width': 0.0001,
'params_kernel_width': 15,
'num_iters': 500,
'num_samples_params': 100,
'batch_size': 100,
'freq_calc_metrics': 1,
}
else:
default_params = {
'regular_param': 3.7747016475817751e-07,
'learning_rate_scale': 0.8,
'gamma': 2.0,
'rf_dim': 1600,
'num_epochs': 1,
'cache_size': 5,
'freq_update_full_model': 20,
'oracle': 'coverage',
'core_max': 100,
'coverage_radius': 1.0,
'loss_func': 'logistic',
'smooth_hinge_theta': 0.5,
'smooth_hinge_tau': 0.5,
}
# default_params = {
# 'regular_param': 1e-2,
# 'learning_rate_scale': 0.7,
# 'gamma': 2.0,
# 'rf_dim': 400,
# 'num_epochs': 1,
# 'cache_size': 50,
# 'freq_update_full_model': 100,
# 'oracle': 'coverage',
# 'core_max': 100,
# 'coverage_radius': 0.9,
# 'loss_func': 'logistic',
# 'smooth_hinge_theta': 0.5,
# 'smooth_hinge_tau': 0.5,
# 'batch_size': 200,
# 'freq_calc_metrics': 300,
# }
default_params = resolve_conflict_params(params, default_params)
print('Default params:', default_params)
learner = OnlineDualSVRG(
**params,
**default_params,
)
return learner
