def __init__(self, filepath: str):
"""Constructs model by loading pretrained net.
Arguments:
filepath (str) : the path to the pretrained h5 net
Raises:
TypeError: filepath not string
FileNotFoundError: filepath not pointing to anything
NotKerasModelError: filepath not pointing to h5 keras model
"""
type_check(filepath, str, "filepath")
file_exists(filepath)
self.load(filepath)
super(WafBrainWrapper, self).__init__(self._keras_classifier)
def create_dataset_from_file(
self, filepath: str, label: int, limit: int = None, unique_rows=True
):
"""Create dataset from fil containing sql queries.
Arguments:
filepath (str) : path of sql queries dataset
label (int) : labels to assign to each sample
Keyword Arguments:
limit (int) : if None, it specifies how many queries to use (default: (None))
unique_rows (bool) : True for removing all the duplicates (default: (True))
Raises:
TypeError: params has wrong types
FileNotFoundError: filepath not pointing to regular file
TypeError: limit is not None and not int
Returns:
(numpy ndarray, list) : X and y
"""
type_check(filepath, str, "filepath")
type_check(label, int, "label")
type_check(unique_rows, bool, "unique_rows")
if limit is not None:
type_check(limit, int, "limit")
file_exists(filepath)
X = []
with open(filepath, "r") as f:
i = 0
for line in f:
if limit is not None and i > limit:
break
line = line.strip()
X.append(self.produce_feat_vector(line))
i += 1
if unique_rows:
X = np.unique(X, axis=0)
else:
X = np.array(X)
y = [label for _ in X]
return X, y
def load_model(self, filepath, ModelClass):
"""Loads a PyTorch classifier stored in filepath.
Arguments:
filepath (string) : The path of the PyTorch classifier.
Raises:
TypeError: filepath is not string.
FileNotFoundError: filepath not pointing to any file.
NotPyTorchModelError: model can not be loaded.
Returns:
self
"""
type_check(filepath, str, "filepath")
file_exists(filepath)
ModelClass.load_state_dict(torch.load(filepath))
ModelClass.eval()
self._pytorch_classifier = ModelClass
return self
def load(self, filepath):
"""Loads a sklearn classifier stored in filepath.
Arguments:
filepath (string) : The path of the sklearn classifier.
Raises:
TypeError: filepath is not string.
FileNotFoundError: filepath not pointing to any file.
NotSklearnModelError: model can not be loaded.
Returns:
self
"""
type_check(filepath, str, "filepath")
file_exists(filepath)
try:
self._sklearn_classifier = joblib.load(filepath)
except Exception as e:
raise NotSklearnModelError("Error in loading model.") from e
return self
def load(self, filepath):
"""Loads a keras classifier stored in filepath.
Arguments:
filepath (string) : The path of the keras classifier.
Returns:
self
Raises:
TypeError: filepath is not string.
FileNotFoundError: filepath not pointing to any file.
NotKerasModelError: model can not be loaded.
"""
type_check(filepath, str, "filepath")
file_exists(filepath)
try:
self._keras_classifier = keras.models.load_model(filepath)
except Exception as e:
raise NotKerasModelError(
"Can not load keras model. See inner exception for details."
) from e