Switch implementation of tf.scalar.summary back to the ScalarSummary kernel.

I originally intended to replace all the summary ops with implementations that use the TensorSummary kernel. However, I realized this would produce a lot of work without any user-visible benefit, so I decided not to do so.
Although I had already created a TensorSummary wrapper for tf.summary.scalar, now that replacing all summary implementations is a non-goal, it is better to keep using ScalarSummary for consistency and backcompat.

The behavior wrt. TensorBoard and the EventAccumulator is unchanged.
Change: 136742625

tensorflow/python/kernel_tests/summary_tensor_op_test.py

@@ -61,7 +61,7 @@ class SummaryOpsTest(tf.test.TestCase):
   def testScalarSummary(self):
     with self.test_session() as sess:
       const = tf.constant(10.0)
-      summ = tf.summary.scalar("foo", const)
+      summ = tf.summary.tensor_summary("foo", const)
       result = sess.run(summ)
 
     value = self._SummarySingleValue(result)

tensorflow/python/summary/summary.py

@@ -39,11 +39,11 @@ from google.protobuf import json_format as _json_format
 from tensorflow.core.framework import summary_pb2 as _summary_pb2
 from tensorflow.python.framework import dtypes as _dtypes
 from tensorflow.python.framework import ops as _ops
-from tensorflow.python.framework import tensor_shape as _tensor_shape
-from tensorflow.python.framework.dtypes import as_dtype as _as_dtype
 from tensorflow.python.ops import gen_logging_ops as _gen_logging_ops
 # exports tensor_summary
+# pylint: disable=unused-import
 from tensorflow.python.ops.summary_ops import tensor_summary
+# pylint: enable=unused-import
 from tensorflow.python.util.all_util import remove_undocumented
 from tensorflow.python.util import compat as _compat
 
@@ -55,7 +55,7 @@ def _collect(val, collections, default_collections):
     _ops.add_to_collection(key, val)
 
 
-def scalar(name, tensor, summary_description=None, collections=None):
+def scalar(name, tensor, collections=None):
   """Outputs a `Summary` protocol buffer containing a single scalar value.
 
   The generated Summary has a Tensor.proto containing the input Tensor.
@@ -63,8 +63,7 @@ def scalar(name, tensor, summary_description=None, collections=None):
   Args:
     name: A name for the generated node. Will also serve as the series name in
       TensorBoard.
-    tensor: A tensor containing a single floating point or integer value.
-    summary_description: Optional summary_description_pb2.SummaryDescription
+    tensor: A real numeric Tensor containing a single value.
     collections: Optional list of graph collections keys. The new summary op is
       added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
 
@@ -74,19 +73,12 @@ def scalar(name, tensor, summary_description=None, collections=None):
   Raises:
     ValueError: If tensor has the wrong shape or type.
   """
-  dtype = _as_dtype(tensor.dtype)
-  if dtype.is_quantized or not (dtype.is_integer or dtype.is_floating):
-    raise ValueError("Can't create scalar summary for type %s." % dtype)
-
-  shape = tensor.get_shape()
-  if not shape.is_compatible_with(_tensor_shape.scalar()):
-    raise ValueError("Can't create scalar summary for shape %s." % shape)
-
-  if summary_description is None:
-    summary_description = _summary_pb2.SummaryDescription()
-  summary_description.type_hint = 'scalar'
-
-  return tensor_summary(name, tensor, summary_description, collections)
+  with _ops.name_scope(name, None, [tensor]) as scope:
+    # pylint: disable=protected-access
+    val = _gen_logging_ops._scalar_summary(
+        tags=scope.rstrip('/'), values=tensor, name=scope)
+    _collect(val, collections, [_ops.GraphKeys.SUMMARIES])
+  return val
 
 
 def image(name, tensor, max_outputs=3, collections=None):

tensorflow/python/summary/summary_test.py

@@ -27,56 +27,18 @@ from tensorflow.core.framework import types_pb2
 
 class ScalarSummaryTest(tf.test.TestCase):
 
-  def testDtypeErrors(self):
-    def _TryMakingScalarSummary(dtype):
-      base = dtype.base_dtype
-      if base == tf.bool:
-        v = False
-      elif base == tf.string:
-        v = ''
-      elif base.is_complex:
-        v = complex(0, 0)
-      else:
-        v = base.min
-      c = tf.constant(v, dtype)
-      return tf.summary.scalar('name', c)
-
-    for datatype_enum in types_pb2.DataType.values():
-      if (datatype_enum == types_pb2.DT_INVALID or
-          datatype_enum == types_pb2.DT_RESOURCE or
-          datatype_enum == types_pb2.DT_RESOURCE_REF):
-        continue
-      dtype = tf.as_dtype(datatype_enum)
-      if dtype.is_quantized:
-        # Quantized ops are funky, and not expected to work.
-        continue
-      if dtype.is_integer or dtype.is_floating:
-        _TryMakingScalarSummary(dtype)
-        # No exception should be thrown
-      else:
-        with self.assertRaises(ValueError):
-          _TryMakingScalarSummary(dtype)
-
-  def testShapeErrors(self):
-    c1 = tf.constant(0)
-    c2 = tf.zeros(5)
-    c3 = tf.zeros(5, 5)
-
-    tf.summary.scalar('1', c1)
-    with self.assertRaises(ValueError):
-      tf.summary.scalar('2', c2)
-    with self.assertRaises(ValueError):
-      tf.summary.scalar('3', c3)
-
-  def testTensorSummaryOpCreated(self):
-    c = tf.constant(0)
-    s = tf.summary.scalar('x', c)
-    self.assertEqual(s.op.type, 'TensorSummary')
-    self.assertEqual(s.op.inputs[0], c)
-    description = s.op.get_attr('description')
-    summary_description = summary_pb2.SummaryDescription()
-    json_format.Parse(description, summary_description)
-    self.assertEqual(summary_description.type_hint, 'scalar')
+  def testScalarSummary(self):
+    with self.test_session() as s:
+      i = tf.constant(3)
+      with tf.name_scope('outer'):
+        im = tf.summary.scalar('inner', i)
+      summary_str = s.run(im)
+    summary = tf.Summary()
+    summary.ParseFromString(summary_str)
+    values = summary.value
+    self.assertEqual(len(values), 1)
+    self.assertEqual(values[0].tag, 'outer/inner')
+    self.assertEqual(values[0].simple_value, 3.0)
 
   def testImageSummary(self):
     with self.test_session() as s: