1 files changed, 66 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/resource_variable_ops_test.py b/tensorflow/python/kernel_tests/resource_variable_ops_test.py
index 0fb0b8895c..c739cd2c0d 100644
--- a/tensorflow/python/kernel_tests/resource_variable_ops_test.py
+++ b/tensorflow/python/kernel_tests/resource_variable_ops_test.py
@@ -246,6 +246,15 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
     read = resource_variable_ops.read_variable_op(handle, dtype=dtypes.int32)
     self.assertEqual(self.evaluate(read), [[2]])
 
+  def testUseResource(self):
+    v = variables.Variable(1.0, use_resource=True)
+    self.assertTrue(isinstance(v, resource_variable_ops.ResourceVariable))
+
+  def testEagerNoUseResource(self):
+    with context.eager_mode():
+      v = variables.Variable(1.0)
+      self.assertTrue(isinstance(v, resource_variable_ops.ResourceVariable))
+
   @test_util.run_in_graph_and_eager_modes
   def testScatterMin(self):
     with ops.device("cpu:0"):
@@ -852,5 +861,62 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
       state_ops.scatter_update(v, [0, 1], [0, 1, 2])
 
 
+class _MixedPrecisionVariableTest(test_util.TensorFlowTestCase):
+
+  @test_util.run_in_graph_and_eager_modes()
+  def test_dense_var_to_tensor_read_dtype_same_as_var_dtype(self):
+    # read_dtype is same as dtype
+    v = resource_variable_ops.ResourceVariable(1.0, dtype=dtypes.float32)
+    v = resource_variable_ops._MixedPrecisionVariable(v, dtypes.float32)
+    if not context.executing_eagerly():
+      v.initializer.run()
+
+    # dtype is not read_dtype, return NotImplemented
+    self.assertEqual(
+        NotImplemented, v._dense_var_to_tensor(dtype=dtypes.float16))
+    self.assertEqual(NotImplemented,
+                     v._dense_var_to_tensor(dtype=dtypes.float16, as_ref=True))
+
+    # as_ref is False
+    t = v._dense_var_to_tensor(as_ref=False)
+    self.assertTrue(isinstance(t, ops.Tensor))
+    self.assertEqual(t.dtype, dtypes.float32)
+    self.assertEqual(self.evaluate(t), 1.0)
+
+    t = v._dense_var_to_tensor(dtype=dtypes.float32, as_ref=False)
+    self.assertTrue(isinstance(t, ops.Tensor))
+    self.assertEqual(t.dtype, dtypes.float32)
+    self.assertEqual(self.evaluate(t), 1.0)
+
+    # as_ref is True
+    self.assertEqual(NotImplemented, v._dense_var_to_tensor(as_ref=True))
+    self.assertEqual(NotImplemented,
+                     v._dense_var_to_tensor(dtype=dtypes.float32, as_ref=True))
+
+  @test_util.run_in_graph_and_eager_modes()
+  def test_dense_var_to_tensor_read_dtype_different_from_var_dtype(self):
+    # read_dtype is different from dtype
+    v = resource_variable_ops.ResourceVariable(1.0, dtype=dtypes.float32)
+    v = resource_variable_ops._MixedPrecisionVariable(v, dtypes.float16)
+    if not context.executing_eagerly():
+      v.initializer.run()
+
+    # as_ref is False
+    t = v._dense_var_to_tensor(as_ref=False)
+    self.assertTrue(isinstance(t, ops.Tensor))
+    self.assertEqual(t.dtype, dtypes.float16)
+    self.assertEqual(self.evaluate(t), 1.0)
+
+    t = v._dense_var_to_tensor(dtype=dtypes.float16, as_ref=False)
+    self.assertTrue(isinstance(t, ops.Tensor))
+    self.assertEqual(t.dtype, dtypes.float16)
+    self.assertEqual(self.evaluate(t), 1.0)
+
+    # as_ref is True
+    self.assertEqual(NotImplemented, v._dense_var_to_tensor(as_ref=True))
+    self.assertEqual(NotImplemented,
+                     v._dense_var_to_tensor(dtype=dtypes.float16, as_ref=True))
+
+
 if __name__ == "__main__":
   test.main()