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, double_head=double_head)

# optimizer
# 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)