finish rest of the easy imports
from utils.featurizer import extract_features
+from utils.iterator import BatchIterator
from utils.pcap_utils import is_private
from utils.pcap_utils import extract_macs
from utils.pcap_utils import get_indiv_source
@@ -25,7 +26,11 @@ from utils.rnnclassifier import get_available_gpus
from utils.rnnclassifier import weight_variable
from utils.rnnclassifier import bias_variable
from utils.rnnclassifier import AbnormalDetector
-
+from utils.session_iterator import BatchIterator as SessBatchIterator
+from utils.training_utils import read_data
+from utils.training_utils import select_features
+from utils.training_utils import whiten_features
+from utils.training_utils import choose_regularization
from utils.OneLayer import OneLayerModel
from utils.RandomForestModel import RandomForestModel
@@ -35,6 +40,7 @@ from utils.SoSmodel import weight_variable
from utils.SoSmodel import bias_variable
from utils.SoSmodel import SoSModel
+
def test_OneLayerModel():
instance = OneLayerModel(15)
@@ -44,5 +50,11 @@ def test_RandomForestModel():
def test_SoSModel():
instance = SoSModel()
+def test_BatchIterator():
+ instance = BatchIterator({}, {})
+
+def test_SessBatchIterator():
+ instance = SessBatchIterator({}, {})
+
def test_AbnormalDetector():
instnace = AbnormalDetector()
