Rename global_step -> step in contrib/summary API

Since it's more succinct and the API doesn't actually care if the provided step
is the one true global step.

PiperOrigin-RevId: 176063779

2 files changed, 42 insertions, 34 deletions

diff --git a/tensorflow/contrib/summary/summary_ops.py b/tensorflow/contrib/summary/summary_ops.py
index bf810744a1..3e65f83051 100644
--- a/tensorflow/contrib/summary/summary_ops.py
+++ b/tensorflow/contrib/summary/summary_ops.py
@@ -344,10 +344,9 @@ def summary_writer_function(name, tensor, function, family=None):
   return op
 
 
-def generic(name, tensor, metadata=None, family=None, global_step=None):
+def generic(name, tensor, metadata=None, family=None, step=None):
   """Writes a tensor summary if possible."""
-  if global_step is None:
-    global_step = training_util.get_global_step()
+
   def function(tag, scope):
     if metadata is None:
       serialized_metadata = constant_op.constant("")
@@ -358,12 +357,15 @@ def generic(name, tensor, metadata=None, family=None, global_step=None):
     # Note the identity to move the tensor to the CPU.
     return gen_summary_ops.write_summary(
         context.context().summary_writer_resource,
-        global_step, array_ops.identity(tensor),
-        tag, serialized_metadata, name=scope)
+        _choose_step(step),
+        array_ops.identity(tensor),
+        tag,
+        serialized_metadata,
+        name=scope)
   return summary_writer_function(name, tensor, function, family=family)
 
 
-def scalar(name, tensor, family=None, global_step=None):
+def scalar(name, tensor, family=None, step=None):
   """Writes a scalar summary if possible.
 
   Unlike @{tf.contrib.summary.generic} this op may change the dtype
@@ -375,68 +377,68 @@ def scalar(name, tensor, family=None, global_step=None):
       `float32`, `float64`, `int32`, `int64`, `uint8`, `int16`,
       `int8`, `uint16`, `half`, `uint32`, `uint64`.
     family: Optional, the summary's family.
-    global_step: The `int64` monotonic step variable, which defaults
+    step: The `int64` monotonic step variable, which defaults
       to @{tf.train.get_global_step}.
 
   Returns:
     The created @{tf.Operation} or a @{tf.no_op} if summary writing has
     not been enabled for this context.
   """
-  if global_step is None:
-    global_step = training_util.get_global_step()
-  else:
-    global_step = ops.convert_to_tensor(global_step, dtypes.int64)
+
   def function(tag, scope):
     # Note the identity to move the tensor to the CPU.
     return gen_summary_ops.write_scalar_summary(
         context.context().summary_writer_resource,
-        global_step, tag, array_ops.identity(tensor),
+        _choose_step(step),
+        tag,
+        array_ops.identity(tensor),
         name=scope)
+
   return summary_writer_function(name, tensor, function, family=family)
 
 
-def histogram(name, tensor, family=None, global_step=None):
+def histogram(name, tensor, family=None, step=None):
   """Writes a histogram summary if possible."""
-  if global_step is None:
-    global_step = training_util.get_global_step()
+
   def function(tag, scope):
     # Note the identity to move the tensor to the CPU.
     return gen_summary_ops.write_histogram_summary(
         context.context().summary_writer_resource,
-        global_step, tag, array_ops.identity(tensor),
+        _choose_step(step),
+        tag,
+        array_ops.identity(tensor),
         name=scope)
 
   return summary_writer_function(name, tensor, function, family=family)
 
 
-def image(name, tensor, bad_color=None, max_images=3, family=None,
-          global_step=None):
+def image(name, tensor, bad_color=None, max_images=3, family=None, step=None):
   """Writes an image summary if possible."""
-  if global_step is None:
-    global_step = training_util.get_global_step()
+
   def function(tag, scope):
     bad_color_ = (constant_op.constant([255, 0, 0, 255], dtype=dtypes.uint8)
                   if bad_color is None else bad_color)
     # Note the identity to move the tensor to the CPU.
     return gen_summary_ops.write_image_summary(
         context.context().summary_writer_resource,
-        global_step, tag, array_ops.identity(tensor),
+        _choose_step(step),
+        tag,
+        array_ops.identity(tensor),
         bad_color_,
-        max_images, name=scope)
+        max_images,
+        name=scope)
 
   return summary_writer_function(name, tensor, function, family=family)
 
 
-def audio(name, tensor, sample_rate, max_outputs, family=None,
-          global_step=None):
+def audio(name, tensor, sample_rate, max_outputs, family=None, step=None):
   """Writes an audio summary if possible."""
-  if global_step is None:
-    global_step = training_util.get_global_step()
+
   def function(tag, scope):
     # Note the identity to move the tensor to the CPU.
     return gen_summary_ops.write_audio_summary(
         context.context().summary_writer_resource,
-        global_step,
+        _choose_step(step),
         tag,
         array_ops.identity(tensor),
         sample_rate=sample_rate,
@@ -483,15 +485,13 @@ def graph(param, step=None, name=None):
   if writer is None:
     return control_flow_ops.no_op()
   with ops.device("cpu:0"):
-    if step is None:
-      step = training_util.get_global_step()
-    else:
-      step = ops.convert_to_tensor(step, dtypes.int64)
     if isinstance(param, (ops.Graph, graph_pb2.GraphDef)):
       tensor = ops.convert_to_tensor(_serialize_graph(param), dtypes.string)
     else:
       tensor = array_ops.identity(param)
-    return gen_summary_ops.write_graph_summary(writer, step, tensor, name=name)
+    return gen_summary_ops.write_graph_summary(
+        writer, _choose_step(step), tensor, name=name)
+
 
 _graph = graph  # for functions with a graph parameter
 
@@ -527,3 +527,11 @@ def _serialize_graph(arbitrary_graph):
     return arbitrary_graph.as_graph_def(add_shapes=True).SerializeToString()
   else:
     return arbitrary_graph.SerializeToString()
+
+
+def _choose_step(step):
+  if step is None:
+    return training_util.get_global_step()
+  if not isinstance(step, ops.Tensor):
+    return ops.convert_to_tensor(step, dtypes.int64)
+  return step
diff --git a/tensorflow/contrib/summary/summary_ops_test.py b/tensorflow/contrib/summary/summary_ops_test.py
index c5ca054f77..ad89c0c36a 100644
--- a/tensorflow/contrib/summary/summary_ops_test.py
+++ b/tensorflow/contrib/summary/summary_ops_test.py
@@ -97,13 +97,13 @@ class TargetTest(test_util.TensorFlowTestCase):
       self.assertEqual(events[1].summary.value[0].tag, 'scalar')
 
   def testSummaryGlobalStep(self):
-    global_step = training_util.get_or_create_global_step()
+    step = training_util.get_or_create_global_step()
     logdir = tempfile.mkdtemp()
     with summary_ops.create_summary_file_writer(
         logdir, max_queue=0,
         name='t2').as_default(), summary_ops.always_record_summaries():
 
-      summary_ops.scalar('scalar', 2.0, global_step=global_step)
+      summary_ops.scalar('scalar', 2.0, step=step)
 
       events = summary_test_util.events_from_logdir(logdir)
       self.assertEqual(len(events), 2)