eager: Graceful failure on invalid inputs.

Tests added to pywrap_tfe_test.py would fail
(segmentation fault / infinite loop)
without corresponding fixes to pywrap_tfe.i and pywrap_tfe_src.cc

Other statements that would fail ungracefully without this fix
(and with eager execution enabled) include:
tf.split(value=0, num_or_size_splits=-1)
tf.dynamic_partition(data=0, partitions=0, num_partitions=-1)
tf.split(value=0, num_or_size_splits=1.23, num=-1)
tf.unstack(value=0, num=-1)

PiperOrigin-RevId: 212731927

3 files changed, 33 insertions, 6 deletions

diff --git a/tensorflow/python/eager/BUILD b/tensorflow/python/eager/BUILD
index 85da1baaf0..c1bc27d443 100644
--- a/tensorflow/python/eager/BUILD
+++ b/tensorflow/python/eager/BUILD
@@ -345,6 +345,7 @@ py_test(
     deps = [
         ":backprop",
         ":context",
+        ":core",
         ":test",
         "//tensorflow/python:framework_test_lib",
         "//tensorflow/python:math_ops",
diff --git a/tensorflow/python/eager/pywrap_tfe_src.cc b/tensorflow/python/eager/pywrap_tfe_src.cc
index c6a55949ab..1a8f3577b2 100644
--- a/tensorflow/python/eager/pywrap_tfe_src.cc
+++ b/tensorflow/python/eager/pywrap_tfe_src.cc
@@ -2563,13 +2563,18 @@ PyObject* TFE_Py_FastPathExecute_C(PyObject*, PyObject* args) {
   int num_retvals = 0;
   for (int i = 0; i < op_def->output_arg_size(); i++) {
     const auto& output_arg = op_def->output_arg(i);
+    int delta = 1;
     if (!output_arg.number_attr().empty()) {
-      num_retvals += attr_list_sizes[output_arg.number_attr()];
+      delta = attr_list_sizes[output_arg.number_attr()];
     } else if (!output_arg.type_list_attr().empty()) {
-      num_retvals += attr_list_sizes[output_arg.type_list_attr()];
-    } else {
-      num_retvals++;
+      delta = attr_list_sizes[output_arg.type_list_attr()];
+    }
+    if (delta < 0) {
+      RaiseFallbackException(
+          "Attributes suggest that the size of an output list is less than 0");
+      return nullptr;
     }
+    num_retvals += delta;
   }
 
   tensorflow::gtl::InlinedVector<TFE_TensorHandle*, 2> retvals(num_retvals);
diff --git a/tensorflow/python/eager/pywrap_tfe_test.py b/tensorflow/python/eager/pywrap_tfe_test.py
index fd8ab695b8..669fa08488 100644
--- a/tensorflow/python/eager/pywrap_tfe_test.py
+++ b/tensorflow/python/eager/pywrap_tfe_test.py
@@ -21,6 +21,7 @@ from __future__ import print_function
 from tensorflow.python import pywrap_tensorflow
 from tensorflow.python.eager import backprop
 from tensorflow.python.eager import context
+from tensorflow.python.eager import core
 from tensorflow.python.eager import test
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
@@ -123,8 +124,8 @@ class Tests(test.TestCase):
   def testFastpathExecute_MixedPrecisionVariableTapeWrite(self):
     ctx = context.context()
     with backprop.GradientTape(persistent=True) as tape:
-      a_2_by_2 = constant_op.constant(
-          [[1.0, 2.0], [3.0, 4.0]], dtype=dtypes.float32)
+      a_2_by_2 = constant_op.constant([[1.0, 2.0], [3.0, 4.0]],
+                                      dtype=dtypes.float32)
       a_2_by_2_fp16 = math_ops.cast(a_2_by_2, dtype=dtypes.float16)
       m1 = resource_variable_ops.ResourceVariable(a_2_by_2)
       m2 = resource_variable_ops._MixedPrecisionVariable(
@@ -233,6 +234,26 @@ class Tests(test.TestCase):
       pywrap_tensorflow.TFE_Py_FastPathExecute(ctx_handle, ctx.device_name,
                                                ctx_handle, None, [], a_2_by_2)
 
+  @test_util.assert_no_new_tensors
+  @test_util.assert_no_garbage_created
+  def testFastPathExecute_InvalidAttributes(self):
+    split_dim = constant_op.constant(0, dtype=dtypes.int32)
+    value = constant_op.constant([0, 1, 2, 3], dtype=dtypes.float32)
+    ctx = context.context()
+    ctx_handle = ctx._handle
+    with self.assertRaises(core._FallbackException):
+      pywrap_tensorflow.TFE_Py_FastPathExecute(ctx_handle, ctx.device_name,
+                                               "Split", None, None, split_dim,
+                                               value, "num_split", -1)
+
+  @test_util.assert_no_new_tensors
+  @test_util.assert_no_garbage_created
+  def testInvalidNumOutputs(self):
+    with self.assertRaisesRegexp(
+        Exception,
+        "Value for attr 'num_split' of -1 must be at least minimum 1"):
+      array_ops.split(value=[1, 2, 3], num_or_size_splits=-1)
+
 
 if __name__ == "__main__":
   test.main()