Add wandb, more args, increase learning rate

train_val.py

@@ -2,27 +2,41 @@ import os
 import torch
 from model import exp_synph
 from model import exp_synphge
+from model import exp_synph_real
 from model import networks
 from co.args import parse_args
+import wandb
+
+wandb.init(project="connecting_the_dots", entity="cpt-captain")
+wandb.config.epochs = 100
+wandb.config.batch_size = 3
 
 # parse args
 args = parse_args()
+double_head = args.no_double_heads
+
+wandb.config.update(args, allow_val_change=True)
 
 # loss types
 if args.loss == 'ph':
     worker = exp_synph.Worker(args)
 elif args.loss == 'phge':
     worker = exp_synphge.Worker(args)
+elif args.loss == 'phirl':
+    worker = exp_synph_real.Worker(args)
+    # double_head = False
+
 
 # concatenation of original image and lcn image
 channels_in = 2
 
 # set up network
 net = networks.DispEdgeDecoders(channels_in=channels_in, max_disp=args.max_disp, imsizes=worker.imsizes,
-                                output_ms=worker.ms)
+                                output_ms=worker.ms, double_head=double_head)
 
 # optimizer
-optimizer = torch.optim.Adam(net.parameters(), lr=1e-4)
+# optimizer = torch.optim.Adam(net.parameters(), lr=1e-4)
+optimizer = torch.optim.Adam(net.parameters(), lr=5e-4)
 
 # start the work
 worker.do(net, optimizer)