Remove summary ops from tf namespace.

tf.histogram_summary, tf.scalar_summary, tf.audio_summary, tf.image_summary, tf.merge_all_summaries, tf.merge_summary are all removed.
Nearly-identical and fully supported apis are available at
tf.summary.histogram, tf.summary.scalar, tf.summary.audio, tf.summary.image, tf.summary.merge_all, tf.summary.merge

The major change in the new API is that the summary "tag" is now actually the node name, which means the TF naming system will automatically deduplicate summary tags.

If you need an exact match for the old API, you may use tf.contrib.deprecated.histogram_summary, etc, but these endpoints will eventually be removed.
Change: 140792244

4 files changed, 8 insertions, 43 deletions

diff --git a/tensorflow/python/kernel_tests/scalar_strict_test.py b/tensorflow/python/kernel_tests/scalar_strict_test.py
index 7d3a953387..1ad13c1c68 100644
--- a/tensorflow/python/kernel_tests/scalar_strict_test.py
+++ b/tensorflow/python/kernel_tests/scalar_strict_test.py
@@ -116,17 +116,6 @@ class ScalarStrictTest(tf.test.TestCase):
     self.check(tf.sparse_to_dense, (1, 4, 7),
                'output_shape should be a vector', [0, 7, 0, 0])
 
-  def testImageSummary(self):
-    image = np.zeros((2, 2, 2, 3), dtype=np.uint8)
-    self.check(tf.image_summary, (['img'], image), 'Tags must be a scalar')
-
-  def testScalarSummary(self):
-    self.check(tf.scalar_summary, (['a'], 7), 'not the same shape')
-    self.check(tf.scalar_summary, ('a', [7]), 'not the same shape')
-
-  def testHistogramSummary(self):
-    self.check(tf.histogram_summary, (['a'], 7), 'tags must be scalar')
-
   def testTile(self):
     self.check(tf.tile, ([7], 2), 'Expected multiples to be 1-D', [7, 7])
 
diff --git a/tensorflow/python/ops/standard_ops.py b/tensorflow/python/ops/standard_ops.py
index 0fafbfaa0c..73208a350b 100644
--- a/tensorflow/python/ops/standard_ops.py
+++ b/tensorflow/python/ops/standard_ops.py
@@ -53,7 +53,8 @@ from tensorflow.python.ops.histogram_ops import *
 from tensorflow.python.ops.init_ops import *
 from tensorflow.python.ops.io_ops import *
 from tensorflow.python.ops.linalg_ops import *
-from tensorflow.python.ops.logging_ops import *
+from tensorflow.python.ops.logging_ops import Print
+from tensorflow.python.ops.logging_ops import get_summary_op
 from tensorflow.python.ops.math_ops import *
 from tensorflow.python.ops.numerics import *
 from tensorflow.python.ops.parsing_ops import *
diff --git a/tensorflow/python/training/training.py b/tensorflow/python/training/training.py
index 6f02680cae..005c815a39 100644
--- a/tensorflow/python/training/training.py
+++ b/tensorflow/python/training/training.py
@@ -110,31 +110,6 @@ more information about how to configure a distributed TensorFlow program.
 @@WorkerSessionCreator
 @@MonitoredSession
 
-## Summary Operations
-
-The following ops output
-[`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
-protocol buffers as serialized string tensors.
-
-You can fetch the output of a summary op in a session, and pass it to
-a [SummaryWriter](../../api_docs/python/train.md#SummaryWriter) to append it
-to an event file.  Event files contain
-[`Event`](https://www.tensorflow.org/code/tensorflow/core/util/event.proto)
-protos that can contain `Summary` protos along with the timestamp and
-step.  You can then use TensorBoard to visualize the contents of the
-event files.  See [TensorBoard and
-Summaries](../../how_tos/summaries_and_tensorboard/index.md) for more
-details.
-
-@@scalar_summary
-@@image_summary
-@@audio_summary
-@@histogram_summary
-@@zero_fraction
-
-@@merge_summary
-@@merge_all_summaries
-
 ## Reading Summaries from Event Files
 
 See [Summaries and
diff --git a/tensorflow/tensorboard/README.md b/tensorflow/tensorboard/README.md
index f6d8473b8d..52762b9a8f 100644
--- a/tensorflow/tensorboard/README.md
+++ b/tensorflow/tensorboard/README.md
@@ -144,11 +144,11 @@ the run-selector on the left.
 Additionally, you can create new folders to organize tags by writing regular
 expressions in the box in the top-left of the dashboard.
 
-### Histogram Dashboard
+### Distribution Dashboard
 
-The Histogram Dashboard is for visualizing how the statistical distribution of a
-Tensor has varied over time. It visualizes data recorded via a
-tf.histogram_summary. Right now, its name is a bit of a misnomer, as it doesn't
+The Distribution Dashboard is for visualizing how the statistical distribution
+of a Tensor has varied over time. It visualizes data recorded via a
+tf.summary.histogram. Right now, its name is a bit of a misnomer, as it doesn't
 show histograms; instead, it shows some high-level statistics on a distribution.
 Each line on the chart represents a percentile in the distribution over the
 data: for example, the bottom line shows how the minimum value has changed over
@@ -167,7 +167,7 @@ replacement.
 
 ### Image Dashboard
 
-The Image Dashboard can display pngs that were saved via a tf.image_summary. The
+The Image Dashboard can display pngs that were saved via a tf.summary.image. The
 dashboard is set up so that each row corresponds to a different tag, and each
 column corresponds to a run. Since the image dashboard supports arbitrary pngs,
 you can use this to embed custom visualizations (e.g. matplotlib scatterplots)
@@ -176,7 +176,7 @@ into TensorBoard. This dashboard always shows you the latest image for each tag.
 ### Audio Dashboard
 
 The Audio Dashboard can embed playable audio widgets for audio saved via a
-tf.audio_summary. The dashboard is set up so that each row corresponds to a
+tf.summary.audio. The dashboard is set up so that each row corresponds to a
 different tag, and each column corresponds to a run. This dashboard always
 embeds the latest audio for each tag.