Fix bug with dataset iterator processing

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

@@ -961,7 +961,7 @@ public void testDataset18()
       throws ClassHierarchyException, IllegalArgumentException, CancelException, IOException {
     test("tf2_test_dataset18.py", "add", 2, 2, 2, 3);
     test("tf2_test_dataset18.py", "f", 1, 1, 2);
-    test("tf2_test_dataset18.py", "g", 0, 2);
+    test("tf2_test_dataset18.py", "g", 0, 1);
   }
 
   /** Test a dataset that uses an iterator. */
@@ -1107,6 +1107,35 @@ public void testDataset33()
     test("tf2_test_dataset33.py", "f", 1, 1, 2);
   }
 
+  /** Test a dataset that uses an iterator. */
+  @Test
+  public void testDataset34()
+      throws ClassHierarchyException, IllegalArgumentException, CancelException, IOException {
+    test("tf2_test_dataset34.py", "add", 2, 2, 2, 3);
+  }
+
+  /** Test a dataset that uses an iterator. */
+  @Test
+  public void testDataset35()
+      throws ClassHierarchyException, IllegalArgumentException, CancelException, IOException {
+    test("tf2_test_dataset35.py", "add", 2, 2, 2, 3);
+  }
+
+  /** Test a dataset that uses an iterator. */
+  @Test
+  public void testDataset36()
+      throws ClassHierarchyException, IllegalArgumentException, CancelException, IOException {
+    test("tf2_test_dataset36.py", "id1", 1, 1, 2);
+    //    test("tf2_test_dataset36.py", "id2", 1, 1, 2);
+  }
+
+  /** Test a dataset that uses an iterator. */
+  @Test
+  public void testDataset37()
+      throws ClassHierarchyException, IllegalArgumentException, CancelException, IOException {
+    test("tf2_test_dataset37.py", "add", 2, 2, 2, 3);
+  }
+
   /**
    * Test enumerating a dataset (https://github.com/wala/ML/issues/140). The first element of the
    * tuple returned isn't a tensor.

com.ibm.wala.cast.python.ml/source/com/ibm/wala/cast/python/ml/client/PythonTensorAnalysisEngine.java

@@ -131,47 +131,7 @@ private static Set<PointsToSetVariable> getDataflowSources(
         if (inst instanceof SSAAbstractInvokeInstruction) {
           // We potentially have a function call that generates a tensor.
           SSAAbstractInvokeInstruction ni = (SSAAbstractInvokeInstruction) inst;
-
-          if (ni.getCallSite()
-                  .getDeclaredTarget()
-                  .getName()
-                  .toString()
-                  .equals(TENSOR_GENERATOR_SYNTHETIC_FUNCTION_NAME)
-              && ni.getException() != vn) {
-            sources.add(src);
-            logger.info("Added dataflow source from tensor generator: " + src + ".");
-          } else if (ni.getNumberOfUses() > 1) {
-            // Get the invoked function from the PA.
-            int target = ni.getUse(0);
-            PointerKey targetKey =
-                pointerAnalysis.getHeapModel().getPointerKeyForLocal(localPointerKeyNode, target);
-
-            for (InstanceKey ik : pointerAnalysis.getPointsToSet(targetKey)) {
-              if (ik instanceof ConcreteTypeKey) {
-                ConcreteTypeKey ctk = (ConcreteTypeKey) ik;
-                IClass type = ctk.getType();
-                TypeReference reference = type.getReference();
-
-                if (reference.equals(NEXT.getDeclaringClass())) {
-                  // it's a call to `next()`. Look up the call to `iter()`.
-                  int iterator = ni.getUse(1);
-                  SSAInstruction iteratorDef = du.getDef(iterator);
-
-                  // Let's see if the iterator is over a tensor dataset.
-                  if (iteratorDef != null && iteratorDef.getNumberOfUses() > 1) {
-                    // Get the argument.
-                    int iterArg = iteratorDef.getUse(1);
-                    processInstructionInterprocedurally(
-                        iteratorDef, iterArg, localPointerKeyNode, src, sources, pointerAnalysis);
-                  } else
-                    // Use the original instruction. NOTE: We can only do this because `iter()` is
-                    // currently just passing-through its argument.
-                    processInstructionInterprocedurally(
-                        ni, iterator, localPointerKeyNode, src, sources, pointerAnalysis);
-                }
-              }
-            }
-          }
+          processInstruction(ni, du, localPointerKeyNode, src, vn, sources, pointerAnalysis);
         } else if (inst instanceof EachElementGetInstruction) {
           // We are potentially pulling a tensor out of a tensor iterable.
           EachElementGetInstruction eachElementGetInstruction = (EachElementGetInstruction) inst;
@@ -215,15 +175,112 @@ private static Set<PointsToSetVariable> getDataflowSources(
           } else if (def instanceof EachElementGetInstruction
               || def instanceof PythonPropertyRead
               || def instanceof PythonInvokeInstruction) {
-            processInstruction(
-                def, du, localPointerKeyNode, src, sources, callGraph, pointerAnalysis);
+            boolean added = false;
+            // we may be invoking `next()` on a dataset.
+            if (def instanceof SSAAbstractInvokeInstruction && def.getNumberOfUses() > 1) {
+              SSAAbstractInvokeInstruction invokeInstruction = (SSAAbstractInvokeInstruction) def;
+              added =
+                  processInstruction(
+                      invokeInstruction,
+                      du,
+                      localPointerKeyNode,
+                      src,
+                      vn,
+                      sources,
+                      pointerAnalysis);
+            }
+
+            if (!added)
+              processInstruction(
+                  def, du, localPointerKeyNode, src, sources, callGraph, pointerAnalysis);
           }
         }
       }
     }
     return sources;
   }
 
+  /**
+   * Processes the given {@link SSAAbstractInvokeInstruction}, adding the given {@link PointsToSetVariable} to the given {@link Set} of {@link PointsToSetVariable}s as a dataflow source if the given {@link SSAAbstractInvokeInstruction} results in a tensor value.
+   *
+   * @param instruction The {@link SSAAbstractInvokeInstruction} to consider.
+   * @param du The {@link DefUse} for the given {@link SSAAbstractInvokeInstruction}.
+   * @param node The {@link CGNode} containing the given {@link SSAAbstractInvokeInstruction}.
+   * @param src The {@link PointsToSetVariable} to add to the given {@link Set} of {@link PointsToSetVariable}s if there a tensor flows from the given {@link SSAAbstractInvokeInstruction.
+   * @param vn The value number in the given {@link CGNode} corresponding to the given {@link PointsToSetVariable}.
+   * @param sources The {@link Set} of {@link PointsToSetVariable}s representing tensor dataflow sources.
+   * @param pointerAnalysis The {@link PointerAnalysis} for the given {@link CGNode}.
+   * @return True iff given the source was added to the set.
+   */
+  private static boolean processInstruction(
+      SSAAbstractInvokeInstruction instruction,
+      DefUse du,
+      CGNode node,
+      PointsToSetVariable src,
+      int vn,
+      Set<PointsToSetVariable> sources,
+      PointerAnalysis<InstanceKey> pointerAnalysis) {
+    boolean ret = false;
+
+    // don't consider exceptions as a data source.
+    if (instruction.getException() != vn) {
+      if (instruction
+          .getCallSite()
+          .getDeclaredTarget()
+          .getName()
+          .toString()
+          .equals(TENSOR_GENERATOR_SYNTHETIC_FUNCTION_NAME)) {
+        sources.add(src);
+        logger.info("Added dataflow source from tensor generator: " + src + ".");
+        ret = true;
+      } else if (instruction.getNumberOfUses() > 1) {
+        // Get the invoked function from the PA.
+        int target = instruction.getUse(0);
+        PointerKey targetKey = pointerAnalysis.getHeapModel().getPointerKeyForLocal(node, target);
+
+        for (InstanceKey ik : pointerAnalysis.getPointsToSet(targetKey)) {
+          if (ik instanceof ConcreteTypeKey) {
+            ConcreteTypeKey ctk = (ConcreteTypeKey) ik;
+            IClass type = ctk.getType();
+            TypeReference reference = type.getReference();
+
+            if (reference.equals(NEXT.getDeclaringClass())) {
+              // it's a call to `next()`. Look up the iterator definition.
+              int iterator = instruction.getUse(1);
+              SSAInstruction iteratorDef = du.getDef(iterator);
+
+              // Let's see if the iterator is over a tensor dataset. First, check the iterator
+              // for a dataset source. NOTE: We can only do this because `iter()` is currently
+              // just passing-through its argument.
+              if (iteratorDef != null && iteratorDef.getNumberOfUses() > 1) {
+                boolean added =
+                    processInstructionInterprocedurally(
+                        iteratorDef, iteratorDef.getDef(), node, src, sources, pointerAnalysis);
+
+                ret |= added;
+
+                if (!added && iteratorDef instanceof SSAAbstractInvokeInstruction) {
+                  // It may be a call to `iter()`. Get the argument.
+                  int iterArg = iteratorDef.getUse(1);
+                  ret |=
+                      processInstructionInterprocedurally(
+                          iteratorDef, iterArg, node, src, sources, pointerAnalysis);
+                }
+              } else
+                // Use the original instruction. NOTE: We can only do this because `iter()` is
+                // currently just passing-through its argument.
+                ret |=
+                    processInstructionInterprocedurally(
+                        instruction, iterator, node, src, sources, pointerAnalysis);
+            }
+          }
+        }
+      }
+    }
+
+    return ret;
+  }
+
   /**
    * Processes the given {@link SSAInstruction} to decide if the given {@link PointsToSetVariable}
    * is added to the given {@link Set} of {@link PointsToSetVariable}s as tensor dataflow sources.

com.ibm.wala.cast.python.test/data/tf2_test_dataset34.py

@@ -0,0 +1,24 @@
+import tensorflow as tf
+
+
+class C:
+
+    def __init__(self, some_iter):
+        self.some_iter = some_iter
+
+    def __str__(self):
+        return str(self.some_iter)
+
+
+def add(a, b):
+    return a + b
+
+
+dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3])
+my_iter = iter(dataset)
+c = C(my_iter)
+length = len(dataset)
+
+for _ in range(length):
+    element = next(c.some_iter)
+    add(element, element)

com.ibm.wala.cast.python.test/data/tf2_test_dataset35.py

@@ -0,0 +1,19 @@
+import tensorflow as tf
+
+
+def add(a, b):
+    return a + b
+
+
+def gen_iter(ds):
+    return iter(ds)
+
+
+dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3])
+
+my_iter = gen_iter(dataset)
+length = len(dataset)
+
+for _ in range(length):
+    element = next(my_iter)
+    add(element, element)

com.ibm.wala.cast.python.test/data/tf2_test_dataset36.py

@@ -0,0 +1,34 @@
+import tensorflow as tf
+
+
+class C:
+
+    def __init__(self, some_iter):
+        self.some_iter = some_iter
+
+    def __str__(self):
+        return str(self.some_iter)
+
+
+def id1(a):
+    return a
+
+
+def id2(a):
+    return a
+
+
+def gen():
+    yield "42", tf.constant("43")
+
+
+dataset = tf.data.Dataset.from_generator(gen, output_types=(tf.string, tf.string))
+
+my_iter = iter(dataset)
+c = C(my_iter)
+length = 1
+
+for _ in range(length):
+    x, y = next(c.some_iter)
+    id1(x)
+    id2(y)

com.ibm.wala.cast.python.test/data/tf2_test_dataset37.py

@@ -0,0 +1,28 @@
+import tensorflow as tf
+
+
+class C:
+
+    def __init__(self, some_iter):
+        self.some_iter = some_iter
+
+    def __str__(self):
+        return str(self.some_iter)
+
+
+def add(a, b):
+    return a + b
+
+
+def gen_iter(dataset):
+    my_iter = iter(dataset)
+    return C(my_iter)
+
+
+dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3])
+c = gen_iter(dataset)
+length = len(dataset)
+
+for _ in range(length):
+    element = next(c.some_iter)
+    add(element, element)