From e8ad72ef9085f72da4417ec29da8d86670df3b1a Mon Sep 17 00:00:00 2001
From: Nicki Skafte Detlefsen <skaftenicki@gmail.com>
Date: Mon, 25 Oct 2021 16:47:45 +0200
Subject: [PATCH] Improve docs on logging in lightning (#582)

---
 docs/source/pages/lightning.rst | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/docs/source/pages/lightning.rst b/docs/source/pages/lightning.rst
index 0261ce91d65..b547b13f3fe 100644
--- a/docs/source/pages/lightning.rst
+++ b/docs/source/pages/lightning.rst
@@ -39,6 +39,12 @@ The example below shows how to use a metric in your `LightningModule <https://py
             # log epoch metric
             self.log('train_acc_epoch', self.accuracy.compute())
 
+.. note::
+    ``self.log`` in Lightning only supports logging of *scalar-tensors*. While the vast majority of metrics in torchmetrics returns a scalar tensor, some metrics such as
+    :class:`~torchmetrics.ConfusionMatrix`, :class:`~torchmetrics.ROC`, :class:`~torchmetrics.MAP`, :class:`~torchmetrics.RougeScore` return outputs that are non-scalar
+    tensors (often dicts or list of tensors) and should therefore be dealt with separately. For info about the return type and shape please look at the documentation for
+    the ``compute`` method for each metric you want to log.
+
 ********************
 Logging TorchMetrics
 ********************