khatchad
commented
10 months ago Suppose we have this input code stored in A.py:
import tensorflow as tf
# Create an override model to classify pictures
class SequentialModel(tf.keras.Model):
def __init__(self, **kwargs):
super(SequentialModel, self).__init__(**kwargs)
self.flatten = tf.keras.layers.Flatten(input_shape=(28, 28))
# Add a lot of small layers
num_layers = 100
self.my_layers = [tf.keras.layers.Dense(64, activation="relu")
for n in range(num_layers)]
self.dropout = tf.keras.layers.Dropout(0.2)
self.dense_2 = tf.keras.layers.Dense(10)
def __call__(self, x):
x = self.flatten(x)
for layer in self.my_layers:
x = layer(x)
x = self.dropout(x)
x = self.dense_2(x)
return x
if __name__ == '__main__':
input_data = tf.random.uniform([20, 28, 28])
print("Input:")
print(type(input_data))
print(input_data)
model = SequentialModel()
result = model(input_data)
print("Output:")
print(type(input_data))
print(result)The problematic expression above is result = model(input_data), because that implicitly invokes SequentialModel.__call__. When building a call graph, I am not even seeing a node for __call__, which is strange. Perhaps it only gets created if there is a call to the function? I would expect to see a method reference of < PythonLoader, Lscript A.py/SequentialModel/__call__, do()LRoot; > somewhere in the following CG nodes:
Node: synthetic < PythonLoader, Lcom/ibm/wala/FakeRootClass, fakeRootMethod()V > Context: Everywhere
Node: synthetic < PythonLoader, Lcom/ibm/wala/FakeRootClass, fakeWorldClinit()V > Context: Everywhere
Node: <Code body of function Lscript A.py> Context: CallStringContext: [ com.ibm.wala.FakeRootClass.fakeRootMethod()V@2 ]
Node: synthetic < PythonLoader, Ltensorflow, import()Ltensorflow; > Context: CallStringContext: [ script A.py.do()LRoot;@88 ]
Node: synthetic < PythonLoader, Lwala/builtin/type, do()LRoot; > Context: CallStringContext: [ script A.py.do()LRoot;@114 ]
Node: synthetic < PythonLoader, Lscript A.py/SequentialModel, do()LRoot; > Context: CallStringContext: [ script A.py.do()LRoot;@117 ]
Node: synthetic < PythonLoader, Lwala/builtin/type, do()LRoot; > Context: CallStringContext: [ script A.py.do()LRoot;@122 ]
Node: <Code body of function Lscript A.py/SequentialModel/__init__> Context: CallStringContext: [ script A.py.SequentialModel.do()LRoot;@12 ]
Node: synthetic < PythonLoader, Lsuperfun, do()LRoot; > Context: DelegatingContext [A=super call, B=CallStringContext: [ script A.py.SequentialModel.__init__.do()LRoot;@5 ]]
Node: synthetic < PythonLoader, Lwala/builtin/range, do()LRoot; > Context: CallStringContext: [ script A.py.SequentialModel.__init__.do()LRoot;@25 ]
Node: synthetic < PythonLoader, LCodeBody, __Lscript A.py/SequentialModel/__init__/comprehension1()LRoot; > Context: CallStringContext: [ script A.py.SequentialModel.__init__.do()LRoot;@26 ]
Node: <Code body of function Lscript A.py/SequentialModel/__init__/comprehension1> Context: CallStringContext: [ CodeBody.__Lscript A.py/SequentialModel/__init__/comprehension1()LRoot;@2 ]
Node: synthetic < PythonLoader, Ltensorflow/functions/uniform, do()LRoot; > Context: CallStringContext: [ script A.py.do()LRoot;@111 ]
Node: synthetic < PythonLoader, Ltensorflow/functions/uniform, read_data()LRoot; > Context: CallStringContext: [ tensorflow.functions.uniform.do()LRoot;@0 ]
__call__doesn't show up in the call graph.