New API summaries (#134)

- `tf.math.reduce_mean()`.
- `tf.GradientTape`
- `tf.GradientTape.gradient()`

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

@@ -259,6 +259,10 @@ public void testTf2()
     testTf2("tf2_test_add5.py", "f", 1, 1, 2);
     testTf2("tf2_test_add6.py", "f", 1, 1, 2);
     testTf2("multigpu_training.py", "run_optimization", 2, 4, 2, 3);
+    testTf2("tf2_test_reduce_mean.py", "f", 1, 1, 2);
+    testTf2("tf2_test_reduce_mean.py", "g", 1, 1, 2);
+    testTf2("tf2_test_reduce_mean.py", "h", 1, 1, 2);
+    testTf2("tf2_test_gradient.py", "f", 1, 1, 2);
   }
 
   private void testTf2(

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

@@ -51,6 +51,8 @@
         <putfield class="LRoot" field="run" fieldType="LRoot" ref="app" value="run" />
         <new def="Estimator" class="Ltensorflow/estimator/Estimator" />
         <putfield class="LRoot" field="Estimator" fieldType="LRoot" ref="estimator" value="Estimator" />
+        <new def="GradientTape" class="Ltensorflow/GradientTape" />
+        <putfield class="LRoot" field="GradientTape" fieldType="LRoot" ref="x" value="GradientTape" />
         <new def="Dataset" class="Ltensorflow/data/Dataset" />
         <putfield class="LRoot" field="Dataset" fieldType="LRoot" ref="data" value="Dataset" />
         <new def="MirroredStrategy" class="Ltensorflow/distribute/MirroredStrategy" />
@@ -79,6 +81,9 @@
         <new def="add" class="Ltensorflow/math/add" />
         <putfield class="LRoot" field="add" fieldType="LRoot" ref="x" value="add" />
         <putfield class="LRoot" field="add" fieldType="LRoot" ref="math" value="add" />
+        <new def="reduce_mean" class="Ltensorflow/math/reduce_mean" />
+        <putfield class="LRoot" field="reduce_mean" fieldType="LRoot" ref="x" value="reduce_mean" />
+        <putfield class="LRoot" field="reduce_mean" fieldType="LRoot" ref="math" value="reduce_mean" />
         <new def="placeholder" class="Ltensorflow/functions/placeholder" />
         <putfield class="LRoot" field="placeholder" fieldType="LRoot" ref="x" value="placeholder" />
         <new def="examples" class="Lobject" />
@@ -280,6 +285,12 @@
           <return value="xx" />
         </method>
       </class>
+      <class name="reduce_mean" allocatable="true">
+        <!-- https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/reduce_mean -->
+        <method name="do" descriptor="()LRoot;" numArgs="5" paramNames="self input_tensor axis keepdims name">
+          <return value="input_tensor" />
+        </method>
+      </class>
     </package>
     <package name="tensorflow/functions">
       <class name="AdamOptimizer" allocatable="true">
@@ -716,6 +727,22 @@
         </method>
       </class>
     </package>
+    <package name="tensorflow">
+      <class name="GradientTape" allocatable="true">
+        <!-- https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/GradientTape -->
+        <method name="do" descriptor="()LRoot;" numArgs="3" paramNames="self persistent watch_accessed_variables">
+          <new def="gradient" class="Ltensorflow/gradient" />
+          <putfield class="LRoot" field="gradient" fieldType="LRoot" ref="arg0" value="gradient" />
+          <return value="arg0" />
+        </method>
+      </class>
+      <class name="gradient" allocatable="true">
+        <!-- https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/GradientTape#gradient -->
+        <method name="do" descriptor="()LRoot;" numArgs="5" paramNames="self target sources output_gradients unconnected_gradients">
+          <return value="sources" />
+        </method>
+      </class>
+    </package>
     <package name="tensorflow/data">
       <class name="Dataset" allocatable="true">
         <!-- "read_dataset" means that this function reads a tensor iterable. -->

com.ibm.wala.cast.python.test/data/tf2_test_gradient.py

@@ -0,0 +1,14 @@
+# From https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/GradientTape#gradient.
+
+import tensorflow as tf
+
+
+def f(a):
+    pass
+
+
+x = tf.ragged.constant([[1.0, 2.0], [3.0]])
+with tf.GradientTape() as g:
+    g.watch(x)
+    y = x * x
+f(g.gradient(y, x))

com.ibm.wala.cast.python.test/data/tf2_test_reduce_mean.py

@@ -0,0 +1,22 @@
+# From https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/math/reduce_mean#for_example
+import tensorflow as tf
+
+
+def f(a):
+    pass
+
+
+def g(a):
+    pass
+
+
+def h(a):
+    pass
+
+
+x = tf.constant([[1.0, 1.0], [2.0, 2.0]])
+f(tf.reduce_mean(x))
+
+g(tf.reduce_mean(x, 0))
+
+h(tf.reduce_mean(x, 1))