Removed the signature.

[profiler-torch.git] / README.md

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@@ -1,18 +1,72 @@
 
-This is a simple profiler to estimate processing time per module per function. One should call
+# Introduction #
 
-  profiler.decorate(model[, functionsToDecorate])
+This is a simple profiler for torch to estimate processing time per module per function.
 
-before starting the computation. It will replace functions specified in functionsToDecorate by instrumented versions which keep track of computation times. If functionsToDecorate is not provided, it will decorate by default updateOutput and backward.
+It seems to work okay, but there was no heavy testing so far. See test-profiler.lua for a short example.
 
-When the computation is over.
+## Example ##
 
-  profiler.print(model[, nbSamples])
+A simple example would be
 
-will print the measured processing times. If nbSamples is provided, the time per samples will also be printed.
+```Lua
+require 'torch'
+require 'nn'
+require 'profiler'
 
-It seems to work okay, but there was no heavy testing so far.
+local input = torch.Tensor(100000, 20):uniform()
+local target = torch.Tensor(input:size(1), 2):uniform()
+local criterion = nn.MSECriterion()
 
---
-Francois Fleuret
-Dec 5th, 2016
+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.
+
+### profiler.decorate(model, [functionsToDecorate]) ###
+
+This function should be called before starting the computation.
+
+It replaces functions specified in functionsToDecorate by instrumented versions which keep track of computation times. If functionsToDecorate is not provided, it decorates by default updateOutput and backward.
+
+It also resets the accumulated timings to zero.
+
+### profiler.print(model, [nbSamples], [totalTime]) ###
+
+Prints the measured processing times. If nbSamples is provided, the time per samples will also be printed. If totalTime is not provided, the total at the top is used.
+
+Non-Containers are hilighted with a '*' or in red.