Add "third level" (i.e., tf.x.y.z) APIs (#85)

- Adding third level APIs
- Adding more tests for experimental.numpy.ndarray

Co-authored-by: Tatiana Castro-Vélez <[email protected]>

com.ibm.wala.cast.python.ml.test/source/com/ibm/wala/cast/python/ml/test/TestTensorflowModel.java

@@ -175,6 +175,16 @@ public void testTf2()
     testTf2("tf2ll.py", "add", 2, 3, 2, 3);
     testTf2("tf2ll2.py", "add", 2, 3, 2, 3);
     testTf2("tf2ll3.py", "add", 2, 3, 2, 3);
+    testTf2("tf2mm.py", "add", 2, 3, 2, 3);
+    testTf2("tf2mm2.py", "add", 2, 3, 2, 3);
+    testTf2("tf2nn.py", "value_index", 2, 4, 2, 3);
+    testTf2("tf2nn2.py", "value_index", 2, 4, 2, 3);
+    testTf2("tf2nn3.py", "value_index", 2, 4, 2, 3);
+    testTf2("tf2nn4.py", "value_index", 2, 4, 2, 3);
+    testTf2("tf2oo.py", "func2", 1, 4, 2);
+    testTf2("tf2oo2.py", "func2", 1, 4, 2);
+    testTf2("tf2oo3.py", "func2", 1, 4, 2);
+    testTf2("tf2oo4.py", "func2", 1, 4, 2);
   }
 
   private void testTf2(

com.ibm.wala.cast.python.ml/data/tensorflow.xml

@@ -35,8 +35,6 @@
 
         <new def="nn" class="Lobject" />
         <putfield class="LRoot" field="nn" fieldType="LRoot" ref="x" value="nn" />
-        <new def="layers" class="Lobject" />
-        <putfield class="LRoot" field="layers" fieldType="LRoot" ref="x" value="layers" />
         <new def="random" class="Lobject" />
         <putfield class="LRoot" field="random" fieldType="LRoot" ref="x" value="random" />
         <new def="sparse" class="Lobject" />
@@ -45,6 +43,9 @@
         <putfield class="LRoot" field="linalg" fieldType="LRoot" ref="x" value="linalg" />
         <new def="keras" class="Lobject" />
         <putfield class="LRoot" field="keras" fieldType="LRoot" ref="x" value="keras" />
+        <new def="layers" class="Lobject" />
+        <putfield class="LRoot" field="layers" fieldType="LRoot" ref="x" value="layers" />
+        <putfield class="LRoot" field="layers" fieldType="LRoot" ref="keras" value="layers" />
 
         <new def="app" class="Lobject" />
         <putfield class="LRoot" field="app" fieldType="LRoot" ref="x" value="app" />
@@ -63,9 +64,6 @@
         <new def="reshape" class="Ltensorflow/functions/reshape" />
         <putfield class="LRoot" field="reshape" fieldType="LRoot" ref="x" value="reshape" />
 
-        <new def="Input" class="Ltensorflow/functions/Input" />
-        <putfield class="LRoot" field="Input" fieldType="LRoot" ref="keras" value="Input" />
-
         <new def="conv2d" class="Ltensorflow/functions/conv2d" />
         <putfield class="LRoot" field="conv2d" fieldType="LRoot" ref="x" value="conv2d" />
         <putfield class="LRoot" field="conv2d" fieldType="LRoot" ref="nn" value="conv2d" />
@@ -106,6 +104,12 @@
         <putfield class="LRoot" field="ragged" fieldType="LRoot" ref="x" value="ragged" />
         <putfield class="LRoot" field="ragged" fieldType="LRoot" ref="ops" value="ragged" />
 
+        <new def="experimental" class="Lobject" />
+        <putfield class="LRoot" field="experimental" fieldType="LRoot" ref="x" value="experimental" />
+
+        <new def="numpy" class="Lobject" />
+        <putfield class="LRoot" field="numpy" fieldType="LRoot" ref="experimental" value="numpy" />
+
         <new def="array_ops" class="Lobject" />
         <putfield class="LRoot" field="array_ops" fieldType="LRoot" ref="ops" value="array_ops" />
 
@@ -139,6 +143,13 @@
         <new def="ragged_tensor" class="Lobject" />
         <putfield class="LRoot" field="ragged_tensor" fieldType="LRoot" ref="ragged" value="ragged_tensor" />
 
+        <new def="ndarray" class="Ltensorflow/functions/ndarray" />
+        <putfield class="LRoot" field="ndarray" fieldType="LRoot" ref="numpy" value="ndarray" />
+
+        <new def="Input" class="Ltensorflow/functions/Input" />
+        <putfield class="LRoot" field="Input" fieldType="LRoot" ref="keras" value="Input" />
+        <putfield class="LRoot" field="Input" fieldType="LRoot" ref="layers" value="Input" />
+
         <new def="Variable" class="Ltensorflow/functions/Variable" />
         <putfield class="LRoot" field="Variable" fieldType="LRoot" ref="x" value="Variable" />
         <putfield class="LRoot" field="Variable" fieldType="LRoot" ref="variables" value="Variable" />
@@ -470,6 +481,17 @@
         </method>
       </class>
 
+      <class name="ndarray" allocatable="true">
+        <method name="read_data" descriptor="()LRoot;">
+          <new def="x" class="Ltensorflow/python/framework/ops/ndarray" />
+          <return value="x" />
+        </method>
+        <method name="do" descriptor="()LRoot;" numArgs="3" paramNames="op value_index dtype">
+          <call class="LRoot" name="read_data" descriptor="()LRoot;" type="virtual" arg0="arg0" def="x" />
+          <return value="x" />
+        </method>
+      </class>
+
       <class name="ragged_range" allocatable="true">
         <method name="read_data" descriptor="()LRoot;">
           <new def="x" class="Ltensorflow/python/ops/ragged/ragged_math_ops/range" />

com.ibm.wala.cast.python.test/data/tf2mm.py

@@ -0,0 +1,7 @@
+import tensorflow as tf
+
+def add(a, b):
+  return a + b
+
+
+c = add(tf.keras.layers.Input(shape=(32,)), tf.keras.layers.Input(shape=(32,)))

com.ibm.wala.cast.python.test/data/tf2mm2.py

@@ -0,0 +1,7 @@
+import tensorflow
+
+def add(a, b):
+  return a + b
+
+
+c = add(tensorflow.keras.layers.Input(shape=(32,)), tensorflow.keras.layers.Input(shape=(32,)))

com.ibm.wala.cast.python.test/data/tf2nn.py

@@ -0,0 +1,13 @@
+import tensorflow as tf
+
+def value_index(a,b):
+  return a.value_index + b.value_index
+
+# From https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/Graph#using_graphs_directly_deprecated
+g = tf.Graph()
+with g.as_default():
+  # Defines operation and tensor in graph
+  c = tf.constant(30.0)
+  assert c.graph is g
+
+result = value_index(tf.experimental.numpy.ndarray(g.get_operations()[0], 0, tf.float32), tf.experimental.numpy.ndarray(g.get_operations()[0], 0, tf.float32))

com.ibm.wala.cast.python.test/data/tf2nn2.py

@@ -0,0 +1,14 @@
+from tensorflow.experimental import numpy
+import tensorflow as tf
+
+def value_index(a,b):
+  return a.value_index + b.value_index
+
+# From https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/Graph#using_graphs_directly_deprecated
+g = tf.Graph()
+with g.as_default():
+  # Defines operation and tensor in graph
+  c = tf.constant(30.0)
+  assert c.graph is g
+
+result = value_index(numpy.ndarray(g.get_operations()[0], 0, tf.float32), numpy.ndarray(g.get_operations()[0], 0, tf.float32))

com.ibm.wala.cast.python.test/data/tf2nn3.py

@@ -0,0 +1,14 @@
+from tensorflow.experimental.numpy import ndarray
+import tensorflow as tf
+
+def value_index(a,b):
+  return a.value_index + b.value_index
+
+# From https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/Graph#using_graphs_directly_deprecated
+g = tf.Graph()
+with g.as_default():
+  # Defines operation and tensor in graph
+  c = tf.constant(30.0)
+  assert c.graph is g
+
+result = value_index(ndarray(g.get_operations()[0], 0, tf.float32), ndarray(g.get_operations()[0], 0, tf.float32))

com.ibm.wala.cast.python.test/data/tf2nn4.py

@@ -0,0 +1,14 @@
+from tensorflow import experimental
+import tensorflow as tf
+
+def value_index(a,b):
+  return a.value_index + b.value_index
+
+# From https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/Graph#using_graphs_directly_deprecated
+g = tf.Graph()
+with g.as_default():
+  # Defines operation and tensor in graph
+  c = tf.constant(30.0)
+  assert c.graph is g
+
+result = value_index(experimental.numpy.ndarray(g.get_operations()[0], 0, tf.float32), experimental.numpy.ndarray(g.get_operations()[0], 0, tf.float32))

com.ibm.wala.cast.python.test/data/tf2oo.py

@@ -0,0 +1,14 @@
+import tensorflow as tf
+
+def func2(t):
+  pass
+
+@tf.function
+def func():
+  a = tf.constant([[1.0, 2.0], [3.0, 4.0]])
+  b = tf.constant([[1.0, 1.0], [0.0, 1.0]])
+  c = tf.matmul(a, b)
+  tensor = tf.experimental.numpy.ndarray(c.op, 0, tf.float32)
+  func2(tensor)
+
+func()

com.ibm.wala.cast.python.test/data/tf2oo2.py

@@ -0,0 +1,15 @@
+from tensorflow import experimental
+import tensorflow as tf
+
+def func2(t):
+  pass
+
+@tf.function
+def func():
+  a = tf.constant([[1.0, 2.0], [3.0, 4.0]])
+  b = tf.constant([[1.0, 1.0], [0.0, 1.0]])
+  c = tf.matmul(a, b)
+  tensor = experimental.numpy.ndarray(c.op, 0, tf.float32)
+  func2(tensor)
+
+func()

com.ibm.wala.cast.python.test/data/tf2oo3.py

@@ -0,0 +1,15 @@
+from tensorflow.experimental import numpy
+import tensorflow as tf
+
+def func2(t):
+  pass
+
+@tf.function
+def func():
+  a = tf.constant([[1.0, 2.0], [3.0, 4.0]])
+  b = tf.constant([[1.0, 1.0], [0.0, 1.0]])
+  c = tf.matmul(a, b)
+  tensor = numpy.ndarray(c.op, 0, tf.float32)
+  func2(tensor)
+
+func()

com.ibm.wala.cast.python.test/data/tf2oo4.py

@@ -0,0 +1,15 @@
+from tensorflow.experimental.numpy import ndarray
+import tensorflow as tf
+
+def func2(t):
+  pass
+
+@tf.function
+def func():
+  a = tf.constant([[1.0, 2.0], [3.0, 4.0]])
+  b = tf.constant([[1.0, 1.0], [0.0, 1.0]])
+  c = tf.matmul(a, b)
+  tensor = ndarray(c.op, 0, tf.float32)
+  func2(tensor)
+
+func()