Adds summary_description and display_name for add_scalar() call (#570)

* fixes #565

examples/demo.py

@@ -23,9 +23,9 @@
     s1 = torch.rand(1)  # value to keep
     s2 = torch.rand(1)
     # data grouping by `slash`
-    writer.add_scalar('data/scalar_systemtime', s1[0], n_iter)
+    writer.add_scalar('data/scalar_systemtime', s1[0], n_iter, summary_description="# markdown is supported!")
     # data grouping by `slash`
-    writer.add_scalar('data/scalar_customtime', s1[0], n_iter, walltime=n_iter)
+    writer.add_scalar('data/scalar_customtime', s1[0], n_iter, walltime=n_iter, display_name="dudubird")
     writer.add_scalars('data/scalar_group', {"xsinx": n_iter * np.sin(n_iter),
                                              "xcosx": n_iter * np.cos(n_iter),
                                              "arctanx": np.arctan(n_iter)}, n_iter)

tensorboardX/summary.py

@@ -126,15 +126,15 @@ def hparams(hparam_dict=None, metric_dict=None):
     return exp, ssi, sei
 
 
-def scalar(name, scalar, collections=None):
+def scalar(name, scalar, display_name="", summary_description=""):
     """Outputs a `Summary` protocol buffer containing a single scalar value.
     The generated Summary has a Tensor.proto containing the input Tensor.
     Args:
       name: A name for the generated node. Will also serve as the series name in
         TensorBoard.
       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]`.
+      display_name: The title of the plot. If empty string is passed, `name` will be used.
+      summary_description: The comprehensive text that will showed by clicking the information icon on TensorBoard.
     Returns:
       A scalar `Tensor` of type `string`. Which contains a `Summary` protobuf.
     Raises:
@@ -144,7 +144,11 @@ def scalar(name, scalar, collections=None):
     scalar = make_np(scalar)
     assert(scalar.squeeze().ndim == 0), 'scalar should be 0D'
     scalar = float(scalar)
-    return Summary(value=[Summary.Value(tag=name, simple_value=scalar)])
+    if display_name == "" and summary_description == "":
+        return Summary(value=[Summary.Value(tag=name, simple_value=scalar)])
+
+    metadata = SummaryMetadata(display_name=display_name, summary_description=summary_description)
+    return Summary(value=[Summary.Value(tag=name, simple_value=scalar, metadata=metadata)])
 
 
 def histogram_raw(name, min, max, num, sum, sum_squares, bucket_limits, bucket_counts):

tensorboardX/writer.py

@@ -381,15 +381,19 @@ def add_hparams(self, hparam_dict=None, metric_dict=None, name=None, global_step
             for k, v in metric_dict.items():
                 w_hp.add_scalar(k, v, global_step)
 
-    def add_scalar(self, tag, scalar_value, global_step=None, walltime=None):
+    def add_scalar(self, tag, scalar_value, global_step=None, walltime=None,
+                   display_name="", summary_description=""):
         """Add scalar data to summary.
 
         Args:
             tag (string): Data identifier
             scalar_value (float or string/blobname): Value to save
             global_step (int): Global step value to record
             walltime (float): Optional override default walltime (time.time()) of event
-
+            display_name (string): The title of the plot. If empty string is passed,
+              `tag` will be used.
+            summary_description (string): The comprehensive text that will showed
+              by clicking the information icon on TensorBoard.
         Examples::
 
             from tensorboardX import SummaryWriter
@@ -408,7 +412,7 @@ def add_scalar(self, tag, scalar_value, global_step=None, walltime=None):
         if self._check_caffe2_blob(scalar_value):
             scalar_value = workspace.FetchBlob(scalar_value)
         self._get_file_writer().add_summary(
-            scalar(tag, scalar_value), global_step, walltime)
+            scalar(tag, scalar_value, display_name, summary_description), global_step, walltime)
 
     def add_scalars(self, main_tag, tag_scalar_dict, global_step=None, walltime=None):
         """Adds many scalar data to summary.