Tweak to EventAccumulator: Process new style summaries as floats.

Before this change, the EventAccumulator parses the new scalar_summaries as
a one-element np array like this: np.array(3, dtype=np.float32).

This is the same as a number wrt equality checking (i.e. expression above is
equal to 3.0), but it isn't json serializable, which causes problems for
TensorBoard.
Change: 136647129

tensorflow/python/summary/event_accumulator.py

@@ -342,7 +342,7 @@ class EventAccumulator(object):
       return
 
     if type_hint == 'scalar':
-      scalar = tensor_util.MakeNdarray(value.tensor)
+      scalar = float(tensor_util.MakeNdarray(value.tensor))
       self._ProcessScalar(name, event.wall_time, event.step, scalar)
     else:
       LogErrorOnce(

tensorflow/python/summary/event_accumulator_test.py

@@ -662,6 +662,8 @@ class MockingEventAccumulatorTest(EventAccumulatorTest):
 
     self.assertEqual(accumulator.Scalars('scalar1'), seq1)
     self.assertEqual(accumulator.Scalars('scalar2'), seq2)
+    first_value = accumulator.Scalars('scalar1')[0].value
+    self.assertTrue(isinstance(first_value, float))
 
   def testTFSummaryImage(self):
     """Verify processing of tf.summary.image."""