Fix tf.range (#152)

Not only does `tf.range()` "generate" a new tensor, i.e., the result
value itself is a tensor, inside that tensor are more, newly generated
tensors. Here, we model it as a one element sequence, which should
suffice for analysis purposes.

com.ibm.wala.cast.python.ml.test/source/com/ibm/wala/cast/python/ml/test/TestTensorflow2Model.java

@@ -1198,6 +1198,18 @@ public void testRelu()
     test("tf2_test_relu.py", "f", 1, 1, 2);
   }
 
+  @Test
+  public void testTFRange()
+      throws ClassHierarchyException, IllegalArgumentException, CancelException, IOException {
+    test("tf2_test_tf_range.py", "f", 1, 1, 2);
+  }
+
+  @Test
+  public void testTFRange2()
+      throws ClassHierarchyException, IllegalArgumentException, CancelException, IOException {
+    test("tf2_test_tf_range2.py", "f", 1, 1, 2);
+  }
+
   private void test(
       String filename,
       String functionName,

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

@@ -463,7 +463,9 @@
       </class>
       <class name="range" allocatable="true">
         <method name="read_data" descriptor="()LRoot;">
-          <new def="x" class="Ltensorflow/python/ops/math_ops/range" />
+          <new def="x" class="Llist" />
+          <call class="Ltensorflow/functions/constant" name="do" descriptor="()LRoot;" type="virtual" arg0="1" def="y" />
+          <putfield class="LRoot" field="0" fieldType="LRoot" ref="x" value="y" />
           <return value="x" />
         </method>
         <method name="do" descriptor="()LRoot;" numArgs="4" paramNames="limit delta dtype name">

com.ibm.wala.cast.python.test/data/tf2_test_tf_range.py

@@ -0,0 +1,17 @@
+# From: https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/range#for_example
+
+import tensorflow as tf
+
+
+def f(a):
+    pass
+
+
+start = 3
+limit = 18
+delta = 3
+
+r = tf.range(start, limit, delta)
+
+for i in r:
+    f(i)

com.ibm.wala.cast.python.test/data/tf2_test_tf_range2.py

@@ -0,0 +1,13 @@
+# From: https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/range#for_example
+
+import tensorflow as tf
+
+
+def f(a):
+    pass
+
+
+r = [tf.constant(3), tf.constant(6), tf.constant(9), tf.constant(12), tf.constant(15)]
+
+for i in r:
+    f(i)