TensorFlow: merge changes from internal

Change 110004767
	Add Cast to list of supported ConstantValue ops, mainly useful for shape inference
Change 110002200
	Bug fix for b/24814668. The fix uses mdevin's CL/109324239, which adds support to clear control dependency and control flow contexts.

	Bug fix for b/25914830. We now clear the control related contexts for initial values of variables in adagrad.
Change 110000213
	Further (minor) improvements to print usage in docs and tutorials
Change 109975099
	Update `tensor_util.ConstantValue()` to return scalars when appropriate.

	The `ConstantValue()` implementations for `tf.size()` and `tf.rank()`
	were returning single-element numpy vectors, whereas the op
	implementations produce scalar outputs.
Change 109950165
	TensorBoard tag to 5

Base CL: 110006867

1 files changed, 19 insertions, 6 deletions

diff --git a/tensorflow/python/framework/tensor_util_test.py b/tensorflow/python/framework/tensor_util_test.py
index f2828475ae..0e2847faf9 100644
--- a/tensorflow/python/framework/tensor_util_test.py
+++ b/tensorflow/python/framework/tensor_util_test.py
@@ -27,6 +27,7 @@ from tensorflow.python.framework import tensor_util
 from tensorflow.python.framework import test_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import constant_op
+from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import state_ops
 from tensorflow.python.platform import googletest
 
@@ -385,19 +386,31 @@ class ConstantValueTest(test_util.TensorFlowTestCase):
     self.assertEqual(np.int32, c_val.dtype)
 
   def testSize(self):
-    np_val = np.array([6], dtype=np.int32)
     tf_val = array_ops.size(constant_op.constant(0.0, shape=[1, 2, 3]))
     c_val = tensor_util.ConstantValue(tf_val)
-    self.assertAllEqual(np_val, c_val)
-    self.assertEqual(np.int32, c_val.dtype)
+    self.assertEqual(6, c_val)
+
+  def testSizeOfScalar(self):
+    tf_val = array_ops.size(constant_op.constant(0.0))
+    c_val = tensor_util.ConstantValue(tf_val)
+    self.assertEqual(1, c_val)
+    self.assertEqual(np.int32, type(c_val))
 
   def testRank(self):
-    np_val = np.array([3], dtype=np.int32)
     tf_val = array_ops.rank(constant_op.constant(0.0, shape=[1, 2, 3]))
     c_val = tensor_util.ConstantValue(tf_val)
-    self.assertAllEqual(np_val, c_val)
-    self.assertEqual(np.int32, c_val.dtype)
+    self.assertEqual(3, c_val)
 
+  def testCast(self):
+    np_val = np.random.rand(3, 4, 7).astype(np.float32)
+    tf_val = math_ops.cast(constant_op.constant(np_val), dtypes.float64)
+    c_val = tensor_util.ConstantValue(tf_val)
+    self.assertAllClose(np_val.astype(np.float64), c_val)
+
+    np_val = np.random.rand(3, 0, 7).astype(np.float32)
+    tf_val = math_ops.cast(constant_op.constant(np_val), dtypes.float64)
+    c_val = tensor_util.ConstantValue(tf_val)
+    self.assertAllClose(np_val.astype(np.float64), c_val)
 
 if __name__ == "__main__":
   googletest.main()