added default settings

optvaeutils/default_settings.pkl

@@ -0,0 +1,113 @@
+(dp1
+S'q_dim_hidden'
+p2
+I400
+sS'grad_noise'
+p3
+F0
+sS'opt_type'
+p4
+S'none'
+p5
+sS'dataset'
+p6
+S'binarized_mnist'
+p7
+sS'epochs'
+p8
+I500
+sS'seed'
+p9
+I1
+sS'n_steps'
+p10
+I200
+sS'q_layers'
+p11
+I2
+sS'init_weight'
+p12
+F0.10000000000000001
+sS'reg_spec'
+p13
+S'_'
+sS'reg_value'
+p14
+F0.01
+sS'input_type'
+p15
+S'normalize'
+p16
+sS'p_dim_hidden'
+p17
+I400
+sS'reloadFile'
+p18
+S'./NOSUCHFILE'
+p19
+sS'dim_stochastic'
+p20
+I100
+sS'lr'
+p21
+F0.00080000000000000004
+sS'p_layers'
+p22
+I2
+sS'init_scheme'
+p23
+S'uniform'
+p24
+sS'input_dropout'
+p25
+F0.0001
+sS'reg_type'
+p26
+S'l2'
+p27
+sS'optimizer'
+p28
+S'adam'
+p29
+sS'batch_size'
+p30
+I500
+sS'opt_method'
+p31
+g29
+sS'savedir'
+p32
+S'./chkpt'
+p33
+sS'param_lr'
+p34
+F0.01
+sS'likelihood'
+p35
+S'mult'
+p36
+sS'savefreq'
+p37
+I5
+sS'paramFile'
+p38
+g19
+sS'emission_type'
+p39
+S'mlp'
+p40
+sS'nonlinearity'
+p41
+S'relu'
+p42
+sS'anneal_rate'
+p43
+I0
+sS'unique_id'
+p44
+S'VAE_lr-8_0e-04-ph-400-qh-400-ds-100-pl-2-ql-2-nl-relu-bs-500-ep-500-plr-1_0e-02-ar-0-otype-none-ns-200-etype-mlp-ll-mult-itype-normalizel20_01_-uid'
+p45
+sS'leaky_param'
+p46
+F0
+s.

optvaeutils/parse_args.py

@@ -32,10 +32,8 @@
 # E] popt pre-optimizing variational parameters
 parser.add_argument('-plr','--param_lr', action = 'store', default=0.01, help='Learning rates used to update mu/cov', type=float)
 parser.add_argument('-ar','--anneal_rate', action = 'store', default=0, help='Number of steps before KL divergence stops being regularized', type=float)
-parser.add_argument('-otype','--opt_type', action='store', default='none', choices=['none','finopt','q_only','q_only_random','finopt_none','none_finopt'], 
-        help='none-standard training,\n finopt-optimize theta w/ optimized mu/logcov')
-parser.add_argument('-ns','--n_steps', action='store', default=200, help='Number of steps of optimization of variational parameters
-        to perform', type=int)
+parser.add_argument('-otype','--opt_type', action='store', default='none', choices=['none','finopt','q_only','q_only_random','finopt_none','none_finopt'], help='none-standard training, finopt-optimize theta w/ optimized mu/logcov')
+parser.add_argument('-ns','--n_steps', action='store', default=200, help='Number of steps of optimization of variational parameters to perform', type=int)
 parser.add_argument('-om','--opt_method', action='store', default='adam', help='Optimization',choices=['adam'])
 
 #Setup 
@@ -86,3 +84,4 @@
             combined+=hmap[k]+'-'+str(params[k])+'-'
 params['unique_id'] = combined[:-1]+str(params['reg_type'])+str(params['reg_value'])+str(params['reg_spec'])+'-'+params['unique_id']
 params['unique_id'] = 'VAE_'+params['unique_id'].replace('.','_')
+