def __init__(self, model):
model.eval()
self.model = model
self.correct = 0
class Stat:
def __init__(self, d, dnm):
self.domain = d
self.name = dnm
self.width = 0
self.max_eps = 0
self.safe = 0
self.proved = 0
self.time = 0
self.domains = [ Stat(h.parseValues(domains,d), h.catStrs(d)) for d in args.test_domain ]
nets += [(net, net_create)]
print("Name: ", net_create.__name__)
print("Number of Neurons (relus): ", net.neuronCount())
print("Number of Parameters: ",
sum([h.product(s.size()) for s in net.parameters()]))
print("Depth (relu layers): ", net.depth())
print()
net.showNet()
print()
if args.domain == []:
models = [createModel(net, goals.Box(args.width), "Box") for net in nets]
else:
models = h.flat([[
createModel(net, h.parseValues(d, goals, scheduling), h.catStrs(d))
for net in nets
] for d in args.domain])
patience = 30
last_best_origin = 0
best_origin = 1e10
last_best = 0
best = 1e10
decay = True
with h.mopen(args.dont_write, os.path.join(out_dir, "log.txt"), "w") as f:
startTime = timer()
for epoch in range(1, args.epochs + 1):
if f is not None:
f.flush()
if (epoch - 1) % args.test_freq == 0 and (epoch > 1
m = getattr(models,n)
net_create = (lambda m: lambda: buildNet(m))(m) # why doesn't python do scoping right? This is a thunk. It is bad.
net_create.__name__ = n
net = buildNet(m)
net.__name__ = n
nets += [ (net, net_create) ]
print("Name: ", net_create.__name__)
print("Number of Neurons (relus): ", net.neuronCount())
print("Number of Parameters: ", sum([h.product(s.size()) for s in net.parameters()]))
print()
if args.domain == []:
models = [ createModel(net, domains.Box(args.width), "Box") for net in nets]
else:
models = h.flat([[createModel(net, h.parseValues(domains,d), h.catStrs(d)) for net in nets] for d in args.domain])
with h.mopen(args.dont_write, os.path.join(out_dir, "log.txt"), "w") as f:
startTime = timer()
for epoch in range(1, args.epochs + 1):
if (epoch - 1) % args.test_freq == 0:
with Timer("test before epoch "+str(epoch),"sample", 10000):
test(models, epoch, f)
h.printBoth("Elapsed-Time: {:.2f}s\n".format(timer() - startTime), f = f)
if args.epochs <= args.test_freq:
break
with Timer("train","sample", 60000):
train(epoch, models)