import numpy as np
import datetime
from lasagne.regularization import *
from collections import OrderedDict
import sys
script_path = '/home/rootcs412/wangchen/work/Indoor/code'
sys.path.append(script_path)
from loadData import *
from net_vggWithSTN import *
from function import *
from Conf import *
# Hyperparamters && global Variant
configFileURL = '/home/rootcs412/wangchen/work/Indoor/config/0117train_1.conf'
config = Conf(configFileURL)
learning_rate = config.getKeyValue('learning_rate')
batch_size = config.getKeyValue('batch_size')
test_batch_size = config.getKeyValue('test_batch_size')
num_epoches = config.getKeyValue('num_epoches')
learning_decay_step = config.getKeyValue('learning_decay_step')
learning_decay_mul = config.getKeyValue('learning_decay_mul')
stn_lr_mul = config.getKeyValue('stn_lr_mul')
weight_decay = config.getKeyValue('weight_decay')
extra = config.getKeyValue('extra')
model_url = config.getKeyValue('model_url')
resultFile_url = config.getKeyValue('resultFile_url')
matrixTable_url = config.getKeyValue('matrixTable_url')
reload_image_url = '/home/rootcs412/wangchen/work/Indoor/models/caffe_vgg16_image.pkl'
reload_places_url = '/home/rootcs412/wangchen/work/Indoor/models/caffe_vgg16_places.pkl'
import Conf;
import SeqGen;
from Conf import *;
from SeqGen import *;
import generateYaml;
from generateYaml import *;
from SeqGenUtils import *;
import sys;
directory = sys.argv[1]
CreateConfFiles(directory);
for confFile in findFiles(directory, '*.yml'):
conf = Conf(confFile);
seqGen = SeqGen(conf);
filename = os.path.splitext(os.path.basename(confFile))[0]
negFastaFile = directory + "/" + filename + "_neg.fa";
seqGen.SetNegFileName(negFastaFile)
seqGen.GenerateRandomSequences("negative", 0);
#seqGen.embedMotifInSequence();
# print "Positive Set: "
# for seq in seqGen.GetPositiveSet():
# print seq;
