Add test for nested values passed to convert_to_tensor.

Change: 136183184

1 files changed, 41 insertions, 10 deletions

diff --git a/tensorflow/python/framework/ops_test.py b/tensorflow/python/framework/ops_test.py
index 34c6b326b4..086f4e0d71 100644
--- a/tensorflow/python/framework/ops_test.py
+++ b/tensorflow/python/framework/ops_test.py
@@ -31,10 +31,10 @@ from tensorflow.python.framework import test_util
 from tensorflow.python.framework import versions
 # Import gradients to register _IndexedSlicesToTensor.
 from tensorflow.python.ops import control_flow_ops
-import tensorflow.python.ops.gradients  # pylint: disable=unused-import
 from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import variable_scope
 from tensorflow.python.ops import variables
+import tensorflow.python.ops.gradients  # pylint: disable=unused-import
 from tensorflow.python.platform import googletest
 from tensorflow.python.util import compat
 
@@ -270,19 +270,50 @@ class OperationTest(test_util.TensorFlowTestCase):
       ops.Operation(ops._NodeDef("op", "invalid:0"), g)
 
   def testShapeFunctionAbsence(self):
-    def _test():
-      pass
     g = ops.Graph()
     with self.assertRaises(RuntimeError):
       g.create_op("shapeless_op", [], [dtypes.float32])
 
   def testNoShapeFunction(self):
     g = ops.Graph()
-    op = ops.Operation(ops._NodeDef("op", "an_op"), g,
-                       output_types = [dtypes.float32])
+    ops.Operation(ops._NodeDef("op", "an_op"), g,
+                  output_types=[dtypes.float32])
     self.assertEqual(tensor_shape.unknown_shape(),
                      _apply_op(g, "an_op", [], [dtypes.float32]).get_shape())
 
+  def testConvertToTensorNestedArray(self):
+    with self.test_session():
+      values = [[2], [3], [5], [7]]
+      tensor = ops.convert_to_tensor(values)
+      self.assertAllEqual((4, 1), tensor.get_shape().as_list())
+      self.assertAllEqual(values, tensor.eval())
+
+  def testConvertToTensorNestedTuple(self):
+    with self.test_session():
+      values = ((2,), (3,), (5,), (7,))
+      tensor = ops.convert_to_tensor(values)
+      self.assertAllEqual((4, 1), tensor.get_shape().as_list())
+      self.assertAllEqual(values, ops.convert_to_tensor(values).eval())
+
+  def testConvertToTensorNestedTensors(self):
+    with self.test_session():
+      values = ((2,), (3,), (5,), (7,))
+      tensor = ops.convert_to_tensor(
+          [constant_op.constant(row) for row in values])
+      self.assertAllEqual((4, 1), tensor.get_shape().as_list())
+      self.assertAllEqual(values, tensor.eval())
+      tensor = ops.convert_to_tensor(
+          [[constant_op.constant(v) for v in row] for row in values])
+      self.assertAllEqual((4, 1), tensor.get_shape().as_list())
+      self.assertAllEqual(values, tensor.eval())
+
+  def testConvertToTensorNestedMix(self):
+    with self.test_session():
+      values = ([2], (3,), [constant_op.constant(5)], constant_op.constant([7]))
+      tensor = ops.convert_to_tensor(values)
+      self.assertAllEqual((4, 1), tensor.get_shape().as_list())
+      self.assertAllEqual(((2,), (3,), (5,), (7,)), tensor.eval())
+
   def testConvertToTensorPreferred(self):
     with self.test_session():
       values = [2, 3, 5, 7]
@@ -290,7 +321,7 @@ class OperationTest(test_util.TensorFlowTestCase):
       self.assertEqual(dtypes.float32, tensor.dtype)
 
     with self.test_session():
-      # Convert empty tensor to anything
+      # Convert empty tensor to anything.
       values = []
       tensor = ops.convert_to_tensor(values, preferred_dtype=dtypes.int64)
       self.assertEqual(dtypes.int64, tensor.dtype)
@@ -309,7 +340,7 @@ class OperationTest(test_util.TensorFlowTestCase):
       _ = ops.convert_to_tensor(values, dtype=dtypes.int64)
 
   def testNoConvert(self):
-    # Operation cannot be converted to Tensor
+    # Operation cannot be converted to Tensor.
     op = control_flow_ops.no_op()
     with self.assertRaisesRegexp(TypeError,
                                  r"Can't convert Operation '.*' to Tensor"):
@@ -919,13 +950,13 @@ def copy_op(x):
 
 
 @ops.RegisterGradient("copy")
-def _CopyGrad(op, x_grad):
+def _CopyGrad(op, x_grad):  # pylint: disable=invalid-name
   _ = op
   return x_grad
 
 
 @ops.RegisterGradient("copy_override")
-def _CopyOverrideGrad(op, x_grad):
+def _CopyOverrideGrad(op, x_grad):  # pylint: disable=invalid-name
   _ = op
   return x_grad
 
@@ -953,7 +984,7 @@ class RegistrationTest(test_util.TensorFlowTestCase):
     with g.gradient_override_map({"copy": "unknown_override"}):
       y = copy_op(x)
     with self.assertRaisesRegexp(LookupError, "unknown_override"):
-      fn = ops.get_gradient_function(y.op)
+      ops.get_gradient_function(y.op)
 
 
 class ComparisonTest(test_util.TensorFlowTestCase):