D = int(sys.argv[2]);
give_inverse_hint = int(sys.argv[3]) == 1;
random_seed = int(sys.argv[4]);
if (exp_fam == 'inv_wishart'):
sqrtD = int(np.sqrt(D));
planar_layers = int(sqrtD*(sqrtD+1)/2);
else:
planar_layers = D;
if (planar_layers < 20):
planar_layers = 20;
flow_dict = get_flowdict(0, planar_layers, 0, 0);
flow_ids = flow_dict['flow_ids'];
flow_repeats = flow_dict['flow_repeats'];
print_flowdict(flow_dict);
if (exp_fam == 'dir_dir'):
model_info = {'Ndrawtype':'stochastic', 'subclass':'EFN1', 'extrastr':''}
else:
model_info = {'subclass':'EFN1', 'extrastr':''};
cost_type = 'KL';
K_eta = 1;
M_eta = 1000;
stochastic_eta = False;
lr_order = -4;
max_iters = 50000;
check_rate = 100;
X, train_KLs, it = train_efn(exp_fam, D, flow_dict, cost_type, K_eta, M_eta, model_info, stochastic_eta, \
D = int(sys.argv[2])
give_inverse_hint = int(sys.argv[3]) == 1
random_seed = int(sys.argv[4])
if (exp_fam == 'inv_wishart'):
sqrtD = int(np.sqrt(D))
planar_layers = int(sqrtD * (sqrtD + 1) / 2)
else:
planar_layers = D
if (planar_layers < 20):
planar_layers = 20
flow_dict = get_flowdict(0, planar_layers, 0, 0)
flow_ids = flow_dict['flow_ids']
flow_repeats = flow_dict['flow_repeats']
print_flowdict(flow_dict)
cost_type = 'KL'
M_eta = 1000
stochastic_eta = True
lr_order = -4
max_iters = 50000
check_rate = 100
if (exp_fam == 'dir_dir'):
model_info = {'Ndrawtype': '1', 'subclass': 'NF1', 'extrastr': ''}
else:
model_info = {
'subclass': 'NF1',
'extrastr': ''
}