print("Please input learning rate. ex. 0.0001")
sys.exit(0)
LR = float(args.learning_rate)
print("Learning rate is:", LR)
LR_ANLP = LR
RUNNING_MODEL = BASE_RNN(EMB_DIM=args.EMB_DIM,
FEATURE_SIZE=args.FEATURE_SIZE,
BATCH_SIZE=args.BATCH_SIZE,
MAX_DEN=args.MAX_DEN,
MAX_SEQ_LEN=args.MAX_SEQ_LEN,
TRAING_STEPS=args.TRAING_STEPS,
STATE_SIZE=args.STATE_SIZE,
LR=LR,
GRAD_CLIP=args.GRAD_CLIP,
L2_NORM=args.L2_NORM,
INPUT_FILE=args.input_file,
ALPHA=args.ALPHA,
BETA=args.BETA,
ADD_TIME_FEATURE=args.ADD_TIME,
FIND_PARAMETER=False,
ANLP_LR=LR,
DNN_MODEL=False,
DISCOUNT=1,
ONLY_TRAIN_ANLP=False,
LOG_PREFIX="drsa")
print("Start of CREATE_GRAPH")
RUNNING_MODEL.create_graph()
print("END OF CREATE_GRAPH")
print("Start of RUN_MODEL")
RUNNING_MODEL.run_model()
print("END OF RUN_MODEL")
BETA = 0.2 # coefficient for anlp
input_file = "2259" #toy dataset
if len(sys.argv) < 2:
print "Please input learning rate. ex. 0.0001"
sys.exit(0)
LR = float(sys.argv[1])
LR_ANLP = LR
RUNNING_MODEL = BASE_RNN(EMB_DIM=EMB_DIM,
FEATURE_SIZE=FEATURE_SIZE,
BATCH_SIZE=BATCH_SIZE,
MAX_DEN=MAX_DEN,
MAX_SEQ_LEN=MAX_SEQ_LEN,
TRAING_STEPS=TRAING_STEPS,
STATE_SIZE=STATE_SIZE,
LR=LR,
GRAD_CLIP=GRAD_CLIP,
L2_NORM=L2_NORM,
INPUT_FILE=input_file,
ALPHA=ALPHA,
BETA=BETA,
ADD_TIME_FEATURE=ADD_TIME,
FIND_PARAMETER=False,
ANLP_LR=LR_ANLP,
DNN_MODEL=True,
ONLY_TRAIN_ANLP=False,
LOG_PREFIX="dnn")
RUNNING_MODEL.create_graph()
RUNNING_MODEL.run_model()
print("Please input learning rate and campaign")
sys.exit(0)
LR = float(sys.argv[1])
input_file = sys.argv[2]
LR_ANLP = LR
RUNNING_MODEL = BASE_RNN(EMB_DIM=EMB_DIM,
FEATURE_SIZE=FEATURE_SIZE,
BATCH_SIZE=BATCH_SIZE,
MAX_DEN=MAX_DEN,
MAX_SEQ_LEN=MAX_SEQ_LEN,
TRAING_STEPS=TRAING_STEPS,
STATE_SIZE=STATE_SIZE,
LR=LR,
GRAD_CLIP=GRAD_CLIP,
L2_NORM=L2_NORM,
INPUT_FILE=input_file,
ALPHA=ALPHA,
BETA=BETA,
ADD_TIME_FEATURE=ADD_TIME,
FIND_PARAMETER=False,
ANLP_LR=LR,
DNN_MODEL=False,
DISCOUNT=1,
ONLY_TRAIN_ANLP=False,
LOG_PREFIX="dlf")
min_price = 1
max_price = 300
price_range_size = max_price - min_price + 1
step = 5
RUNNING_MODEL.create_graph()