fix add_histogram_raw (#20688)

Summary:
This is a porting of the fix from:
https://github.com/lanpa/tensorboardX/issues/421

cc orionr
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20688

Reviewed By: NarineK

Differential Revision: D15415093

Pulled By: orionr

fbshipit-source-id: d32a6298218fbc6fe315aa0f18b57e0c8ef92627

docs/source/tensorboard.rst

@@ -86,6 +86,7 @@ Expected result:
    .. automethod:: add_scalar
    .. automethod:: add_scalars
    .. automethod:: add_histogram
+   .. automethod:: add_histogram_raw
    .. automethod:: add_image
    .. automethod:: add_images
    .. automethod:: add_figure

test/test_tensorboard.py

@@ -105,7 +105,7 @@ if TEST_TENSORBOARD:
                                     num=num,
                                     sum=floats.sum().item(),
                                     sum_squares=sum_sq,
-                                    bucket_limits=limits.tolist(),
+                                    bucket_limits=limits[1:].tolist(),
                                     bucket_counts=counts.tolist())
 
                 ints = make_np(torch.randint(0, 100, (num,)))
@@ -118,7 +118,7 @@ if TEST_TENSORBOARD:
                                     num=num,
                                     sum=ints.sum().item(),
                                     sum_squares=sum_sq,
-                                    bucket_limits=limits.tolist(),
+                                    bucket_limits=limits[1:].tolist(),
                                     bucket_counts=counts.tolist())
 
                 ints = torch.tensor(range(0, 100)).float()

torch/utils/tensorboard/writer.py

@@ -385,13 +385,48 @@ class SummaryWriter(object):
             num (int): Number of values
             sum (float or int): Sum of all values
             sum_squares (float or int): Sum of squares for all values
-            bucket_limits (torch.Tensor, numpy.array): Upper value per bucket
+            bucket_limits (torch.Tensor, numpy.array): Upper value per bucket.
+              The number of elements of it should be the same as `bucket_counts`.
             bucket_counts (torch.Tensor, numpy.array): Number of values per bucket
             global_step (int): Global step value to record
             walltime (float): Optional override default walltime (time.time())
               seconds after epoch of event
             see: https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/histogram/README.md
+
+        Examples::
+
+            from torch.utils.tensorboard import SummaryWriter
+            import numpy as np
+            writer = SummaryWriter()
+            dummy_data = []
+            for idx, value in enumerate(range(50)):
+                dummy_data += [idx + 0.001] * value
+
+            bins = list(range(50+2))
+            bins = np.array(bins)
+            values = np.array(dummy_data).astype(float).reshape(-1)
+            counts, limits = np.histogram(values, bins=bins)
+            sum_sq = values.dot(values)
+            writer.add_histogram_raw(
+                tag='histogram_with_raw_data',
+                min=values.min(),
+                max=values.max(),
+                num=len(values),
+                sum=values.sum(),
+                sum_squares=sum_sq,
+                bucket_limits=limits[1:].tolist(),
+                bucket_counts=counts.tolist(),
+                global_step=0)
+            writer.close()
+
+        Expected result:
+
+        .. image:: _static/img/tensorboard/add_histogram_raw.png
+           :scale: 50 %
+
         """
+        if len(bucket_limits) != len(bucket_counts):
+            raise ValueError('len(bucket_limits) != len(bucket_counts), see the document.')
         self._get_file_writer().add_summary(
             histogram_raw(tag,
                           min,