New API and new operator overloading issue (#81)

* Add `tf.nn.sparse_softmax_cross_entropy_with_logits()`.

* Mark test that tests wala#136.

* Update tests to reflect new API.

* Update test in light of wala#136.

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

@@ -217,7 +217,11 @@ public void testTf2()
     testTf2("tf2_test_dataset10.py", "add", 2, 2, 2, 3);
     testTf2("tf2_test_tensor_list.py", "add", 2, 2, 2, 3);
     testTf2("tf2_test_tensor_list2.py", "add", 0, 0);
-    testTf2("tf2_test_tensor_list3.py", "add", 0, 0);
+    testTf2(
+        "tf2_test_tensor_list3.py",
+        "add",
+        0,
+        0); // NOTE: Change to 2, 2, 2, 3 once https://github.com/wala/ML/issues/136 is fixed.
     testTf2("tf2_test_tensor_list4.py", "add", 0, 0);
     testTf2("tf2_test_tensor_list5.py", "add", 0, 0);
     testTf2("tf2_test_model_call.py", "SequentialModel.__call__", 1, 1, 3);
@@ -234,10 +238,10 @@ public void testTf2()
         "neural_network.py",
         "cross_entropy_loss",
         1,
-        4,
+        8,
         3); // NOTE: Change to 2 tensor parameters once https://github.com/wala/ML/issues/127 is
     // fixed. Values 2 and 3 will correspond to the tensor parameters.
-    testTf2("neural_network.py", "run_optimization", 2, 2, 2, 3);
+    testTf2("neural_network.py", "run_optimization", 2, 3, 2, 3);
     testTf2(
         "neural_network.py",
         "accuracy",
@@ -259,13 +263,19 @@ 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(
+        "multigpu_training.py",
+        "average_gradients",
+        0,
+        0); // NOTE: Change to 1, 1, 2 once https://github.com/wala/ML/issues/136 is fixed.
     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);
     testTf2("tf2_test_gradient2.py", "f", 1, 1, 2);
     testTf2("tf2_test_multiply.py", "f", 1, 1, 2);
     testTf2("tf2_test_multiply2.py", "f", 1, 1, 2);
+    testTf2("tf2_test_sparse_softmax_cross_entropy_with_logits.py", "f", 1, 1, 2);
   }
 
   private void testTf2(

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

@@ -75,6 +75,8 @@
         <putfield class="LRoot" field="conv3d" fieldType="LRoot" ref="nn" value="conv3d" />
         <new def="softmax" class="Ltensorflow/functions/softmax" />
         <putfield class="LRoot" field="softmax" fieldType="LRoot" ref="nn" value="softmax" />
+        <new def="sparse_softmax_cross_entropy_with_logits" class="Ltensorflow/functions/sparse_softmax_cross_entropy_with_logits" />
+        <putfield class="LRoot" field="sparse_softmax_cross_entropy_with_logits" fieldType="LRoot" ref="nn" value="sparse_softmax_cross_entropy_with_logits" />
         <new def="sigmoid" class="Ltensorflow/math/sigmoid" />
         <putfield class="LRoot" field="sigmoid" fieldType="LRoot" ref="nn" value="sigmoid" />
         <putfield class="LRoot" field="sigmoid" fieldType="LRoot" ref="math" value="sigmoid" />
@@ -697,6 +699,12 @@
           <return value="logits" />
         </method>
       </class>
+      <class name="sparse_softmax_cross_entropy_with_logits" allocatable="true">
+        <!-- https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/nn/sparse_softmax_cross_entropy_with_logits -->
+        <method name="do" descriptor="()LRoot;" numArgs="4" paramNames="self labels logits name">
+          <return value="labels" />
+        </method>
+      </class>
     </package>
     <package name="tensorflow/estimator">
       <class name="Estimator" allocatable="true">

com.ibm.wala.cast.python.test/data/tf2_test_sparse_softmax_cross_entropy_with_logits.py

@@ -0,0 +1,14 @@
+# from https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/nn/sparse_softmax_cross_entropy_with_logits
+
+import tensorflow as tf
+
+
+def f(a):
+    pass
+
+
+logits = tf.constant(
+    [[2.0, -5.0, 0.5, -0.1], [0.0, 0.0, 1.9, 1.4], [-100.0, 100.0, -100.0, -100.0]]
+)
+labels = tf.constant([0, 3, 1])
+f(tf.nn.sparse_softmax_cross_entropy_with_logits(labels=labels, logits=logits.numpy()))

com.ibm.wala.cast.python.test/data/tf2_test_tensor_list3.py

@@ -1,3 +1,5 @@
+# Test https://github.com/wala/ML/issues/136.
+
 import tensorflow as tf