From 94e38c05b84dfc283e863f1d96ca5d48be3d3c68 Mon Sep 17 00:00:00 2001
From: Mike J Innes <mike.j.innes@gmail.com>
Date: Wed, 27 Sep 2017 18:33:23 +0100
Subject: [PATCH 1/2] more informative

---
 src/optimise/train.jl | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/optimise/train.jl b/src/optimise/train.jl
index 8ad437db..0a91e978 100644
--- a/src/optimise/train.jl
+++ b/src/optimise/train.jl
@@ -8,8 +8,8 @@ function train!(m, data, opt; cb = () -> ())
   cb = tocb(cb)
   @progress for x in data
     l = m(x...)
-    isinf(l.data[]) && error("Inf")
-    isnan(l.data[]) && error("NaN")
+    isinf(l.data[]) && error("Loss is Inf")
+    isnan(l.data[]) && error("Loss is NaN")
     back!(l)
     opt()
     cb()

From c51f5afb3d2d14247e332ae0cf711a904f374288 Mon Sep 17 00:00:00 2001
From: Mike J Innes <mike.j.innes@gmail.com>
Date: Wed, 27 Sep 2017 18:37:07 +0100
Subject: [PATCH 2/2] clarity

---
 docs/src/training/training.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/src/training/training.md b/docs/src/training/training.md
index 1eaa8a46..d4bed5fe 100644
--- a/docs/src/training/training.md
+++ b/docs/src/training/training.md
@@ -9,7 +9,7 @@ To actually train a model we need three things:
 With these we can call `Flux.train!`:
 
 ```julia
-Flux.train!(model, data, opt)
+Flux.train!(modelLoss, data, opt)
 ```
 
 There are plenty of examples in the [model zoo](https://github.com/FluxML/model-zoo).