import sys
sys.path.append('/home/annal/Izzy/vision_amt/')
from Net.tensor import net3
from Net.tensor import net4
from Net.tensor import net6,net6_c,net8
from Net.tensor import inputdata
from options import AMTOptions
import numpy as np
from scripts import compile_supervisor, merge_supervised
if __name__ == "__main__":
num_nets = 2
net_paths = []
for _ in range(num_nets):
clean = False
rand = False
outfile = open(AMTOptions.amt_dir + 'deltas.txt', 'w+')
merge_supervised.load_rollouts(clean, rand, (0,20), (0,-1), outfile)
outfile.close()
compile_supervisor.compile_reg()
data = inputdata.AMTData(AMTOptions.train_file, AMTOptions.test_file,channels=3)
#net = net6_c.NetSix_C()
net = net6.NetSix()
net_paths.append(net.optimize(50,data, batch_size=200))
train_writer = open(AMTOptions.amt_dir + 'net_cluster.txt', 'w+')
for path in net_paths:
train_writer.write(path + ' \n')
train_writer.close()
last = args.last
else:
print "please enter a last value with -l (not inclusive)"
sys.exit()
sup = True
if args.DAgger:
sup = False
elif args.supervisor:
sup = True
else:
print "specify type"
sys.exit()
outfile = open(AMTOptions.amt_dir + 'deltas.txt', 'w+')
if sup:
failure = merge_supervised.load_rollouts(False, False, (first,last), (0,-1), outfile, name = person)
if failure:
print "did not have the sufficient rollouts specified"
outfile.close()
else:
failure = merge_supervised.load_rollouts(False, False, (0,20), (0,-1), outfile, name = person)
if failure:
print "did not have the sufficient rollouts specified... Do you have at least 20 supervised rollouts"
sys.exit()
f = []
for (dirpath, dirnames, filenames) in os.walk(AMTOptions.rollouts_dir + person + "_rollouts/"):
f.extend(filenames)
for filename in f:
read_path = AMTOptions.rollouts_dir + person + "_rollouts/" + filename
if read_path.find("retroactive_feedback") != -1 and read_path.find("~") == -1:
print filename