Update.

diff --git a/README.md b/README.md
index 0e8bd5f..02a57fe 100644 (file)
--- a/README.md
+++ b/README.md
@@ -1,8 +1,58 @@
 
-This is a simple profiler to estimate processing time per module per function.
+#Introduction#
+
+This is a simple profiler for torch to estimate processing time per module per function.
 
 It seems to work okay, but there was no heavy testing so far. See test-profiler.lua for a short example.
 
+## Example ##
+
+A simple example would be
+
+```lua
+require 'torch'
+require 'nn'
+require 'profiler'
+
+local input = torch.Tensor(100000, 20):uniform()
+local target = torch.Tensor(input:size(1), 2):uniform()
+local criterion = nn.MSECriterion()
+
+local model = nn.Sequential()
+   :add(nn.Linear(input:size(2), 1000))
+   :add(nn.ReLU())
+   :add(nn.Linear(1000, target:size(2)))
+
+profiler.decorate(model)
+profiler.color = nil
+
+local output = model:forward(input)
+criterion:forward(output, target)
+local dloss = criterion:backward(output, target)
+model:backward(input, dloss)
+
+profiler.print(model, input:size(1))
+```
+
+which prints
+
+```
+ nn.Sequential 3.03s [100.00%] (30.3mus/sample)
+  :backward 1.94s [64.16%] (19.4mus/sample)
+  :updateOutput 1.08s [35.84%] (10.8mus/sample)
+  * nn.Linear 1.22s [40.41%] (12.2mus/sample)
+    :backward 0.64s [21.24%] (6.4mus/sample)
+    :updateOutput 0.58s [19.17%] (5.8mus/sample)
+  * nn.ReLU 1.05s [34.62%] (10.5mus/sample)
+    :backward 0.74s [24.30%] (7.4mus/sample)
+    :updateOutput 0.31s [10.32%] (3.1mus/sample)
+  * nn.Linear 0.76s [24.97%] (7.6mus/sample)
+    :backward 0.56s [18.62%] (5.6mus/sample)
+    :updateOutput 0.19s [6.34%] (1.9mus/sample)
+```
+
+##Usage##
+
 ### profiler.color ###
 
 This is a Boolean flag to state if the printing should be done in color. It is true by default.