# Introduction #
-This package implements a new module nn.DAG for the torch framework,
-which inherits from nn.Container and allows to combine modules in an
-arbitrary graph without cycle.
+This package implements a new module nn.DAG for the [torch framework](https://torch.ch),
+which inherits from [nn.Container](https://github.com/torch/nn/blob/master/Container.lua) and allows to combine modules in an
+arbitrary [Directed Acyclic Graph (DAG).](https://en.wikipedia.org/wiki/Directed_acyclic_graph)
## Example ##
modules given as argument to DAG:setInput (respectively DAG:setOutput)
So for instance, in the example above, the model expects a tensor as
-input, since it is the input to the module a, and its output will is a
+input, since it is the input to the module a, and its output is a
table composed of two tensors, corresponding to the outputs of d and e
respectively.
### nn.DAG:setInput(i) ###
-Defines the content and structure of the input. The argument should be
+Define the content and structure of the input. The argument should be
either a module, or a (nested) table of modules. The input to the DAG
-should be a (nested) table of inputs, with the corresponding structure.
+should be a (nested) table of inputs, with the corresponding
+structure.
### nn.DAG:setOutput(o) ###
### nn.DAG:print() ###
-Prints the list of nodes.
+Print the list of nodes.
### nn.DAG:saveDot(filename) ###