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diff --git a/tensorflow/contrib/framework/python/ops/accumulate_n_v2_eager_test.py b/tensorflow/contrib/framework/python/ops/accumulate_n_v2_eager_test.py
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+++ b/tensorflow/contrib/framework/python/ops/accumulate_n_v2_eager_test.py
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+# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for new version of accumulate_n op that will eventually go into 
+`ops.math_ops`.
+
+These test cases spefically exercise the `eager` APIs. They need to be in a 
+separate file from the remaining tests because eager mode is currently something
+you can turn on but can't turn off for the lifetime of the current process."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import numpy as np
+
+from tensorflow.contrib.framework.python.ops import accumulate_n_v2 as av2
+
+from tensorflow.python.eager import backprop
+from tensorflow.python.eager import context as eager_context
+from tensorflow.python.eager import tape
+
+
+from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import dtypes as dtypes_lib
+from tensorflow.python.framework import ops
+from tensorflow.python.framework import test_util
+from tensorflow.python.ops import gradients
+from tensorflow.python.ops import math_ops
+from tensorflow.python.ops import resource_variable_ops
+from tensorflow.python.platform import test
+
+
+
+class AccumulateNV2EagerTest(test_util.TensorFlowTestCase):
+  """Tests of the new, differentiable version of accumulate_n"""
+
+  def testMinimalEagerMode(self):
+    forty = constant_op.constant(40)
+    two = constant_op.constant(2)
+    answer = av2.accumulate_n_v2([forty, two])
+    self.assertEqual(42, answer.numpy())
+
+
+  def testFloat(self):
+    np.random.seed(12345)
+    x = [np.random.random((1, 2, 3, 4, 5)) - 0.5 for _ in range(5)]
+    tf_x = ops.convert_n_to_tensor(x)
+    with self.test_session(use_gpu=True):
+      self.assertAllClose(sum(x), av2.accumulate_n_v2(tf_x).numpy())
+      self.assertAllClose(x[0] * 5, av2.accumulate_n_v2([tf_x[0]] * 5).numpy())
+
+  def testGrad(self):
+    np.random.seed(42)
+    num_inputs = 3
+    input_vars = [
+        resource_variable_ops.ResourceVariable(10.0 * np.random.random(), 
+                                               name="t%d" % i)
+        for i in range(0, num_inputs)
+    ]
+
+    def fn(first, second, third):
+      return av2.accumulate_n_v2([first, second, third])
+
+    grad_fn = backprop.gradients_function(fn)      
+    grad = grad_fn(input_vars[0], input_vars[1], input_vars[2])
+    self.assertAllEqual(np.repeat(1.0, num_inputs), # d/dx (x + y + ...) = 1
+                        [elem.numpy() for elem in grad])
+
+
+
+if __name__ == "__main__":
+  ops.enable_eager_execution()
+  test.main()
+