Fix convert_to_tensor problem for list of TensorNodes

Current code fail to error out in convert_to_tensor
when multiple TensorNodes are passed in.

PiperOrigin-RevId: 167319274

3 files changed, 36 insertions, 14 deletions

diff --git a/tensorflow/python/eager/backprop_test.py b/tensorflow/python/eager/backprop_test.py
index 429eeabb42..b437905509 100644
--- a/tensorflow/python/eager/backprop_test.py
+++ b/tensorflow/python/eager/backprop_test.py
@@ -307,6 +307,20 @@ class BackpropTest(test.TestCase):
         [tensor_shape.TensorShape(s).as_proto() for s in shape_list],
         backprop.make_attr([pywrap_tensorflow.TF_ATTR_SHAPE], shape_list))
 
+  def testMultiValueConvertToTensor(self):
+    x = resource_variable_ops.ResourceVariable(
+        initial_value=array_ops.constant([1.0]), name='x')
+
+    def fn():
+      tape.watch_variable(x)
+      a = math_ops.add(x.value(), 1.0)
+      # Make sure convert_to_tensor works correctly with list of TensorNodes.
+      b = array_ops.stack([a, a], axis=0)
+      return math_ops.reduce_mean(b)
+
+    grad = backprop.implicit_grad(fn)()[0][1]
+    self.assertAllEqual([1.0], grad.numpy())
+
 
 if __name__ == '__main__':
   test.main()
diff --git a/tensorflow/python/framework/ops.py b/tensorflow/python/framework/ops.py
index 659bc394b9..b197e96886 100644
--- a/tensorflow/python/framework/ops.py
+++ b/tensorflow/python/framework/ops.py
@@ -49,6 +49,7 @@ from tensorflow.python.framework import versions
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.util import compat
 from tensorflow.python.util import decorator_utils
+from tensorflow.python.util import nest
 from tensorflow.python.util import tf_contextlib
 
 # Temporary global switch determining if we should enable the work-in-progress
@@ -1036,12 +1037,19 @@ def internal_convert_to_tensor(value,
   # tracing gradients, to ensure the same behavior happens with and without
   # tracing.
   unwrapped = ag_core.getval(value)
-  # Fast path for EagerTensors that don't need any conversion.
-  if isinstance(unwrapped, EagerTensor) and context.in_eager_mode():
-    # Note that we don't check that value's dtype matches the dtype
-    # argument.  We exepct that the C runtime will do that checking
-    # when we execute the kernel.
-    return value
+
+  if context.in_eager_mode():
+    # Fast path for EagerTensors that don't need any conversion.
+    if isinstance(unwrapped, EagerTensor):
+      # Note that we don't check that value's dtype matches the dtype
+      # argument.  We exepct that the C runtime will do that checking
+      # when we execute the kernel.
+      return value
+    values = nest.flatten(value)
+    if (len(values) > 1 and
+        any(isinstance(ag_core.getval(v), EagerTensor) for v in values)):
+      raise TypeError("Cannot convert to a eager tensor.")
+
   if dtype is not None:
     dtype = dtypes.as_dtype(dtype)
   unwrapped_type = type(unwrapped)
diff --git a/tensorflow/python/kernel_tests/array_ops_test.py b/tensorflow/python/kernel_tests/array_ops_test.py
index 392639fa17..77c5bb6d40 100644
--- a/tensorflow/python/kernel_tests/array_ops_test.py
+++ b/tensorflow/python/kernel_tests/array_ops_test.py
@@ -981,15 +981,15 @@ class SequenceMaskTest(test_util.TensorFlowTestCase):
 
 class ConcatSliceResourceTest(test_util.TensorFlowTestCase):
 
+  @test_util.run_in_graph_and_eager_modes()
   def testConcatSlice(self):
-    with self.test_session():
-      r1 = test_ops.stub_resource_handle_op(container="a", shared_name="b")
-      r2 = test_ops.stub_resource_handle_op(container="a", shared_name="c")
-      c = array_ops.stack([r1, r2])
-      s = array_ops.strided_slice(c, [1], [2])
-      test_ops.resource_create_op(s).run()
-      with self.assertRaises(errors.AlreadyExistsError):
-        test_ops.resource_create_op(r2).run()
+    r1 = test_ops.stub_resource_handle_op(container="a", shared_name="b")
+    r2 = test_ops.stub_resource_handle_op(container="a", shared_name="c")
+    c = array_ops.stack([r1, r2])
+    s = array_ops.strided_slice(c, [1], [2])
+    self.evaluate(test_ops.resource_create_op(s))
+    with self.assertRaises(errors.AlreadyExistsError):
+      self.evaluate(test_ops.resource_create_op(r2))
 
 
 class IdentityTest(test_util.TensorFlowTestCase):