-This package implements a new module nn.DAG 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)
The DAG can deal with modules which take as input and produce as
output tensors and nested tables of tensors.
If a node has a single predecessor, the output of the latter is taken
The DAG can deal with modules which take as input and produce as
output tensors and nested tables of tensors.
If a node has a single predecessor, the output of the latter is taken
-input. The indexes of the outputs in that table reflects the order in
-which the edges where created in the DAG:connect() commands.
+input. The indexes of the outputs in that table reflect the
+chronological order in which the edges where created in the
+DAG:connect() commands.
The input to the DAG (respectively the produced output) is a nested
table of inputs reflecting the structure of the nested table of
The input to the DAG (respectively the produced output) is a nested
table of inputs reflecting the structure of the nested table of
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
table composed of two tensors, corresponding to the outputs of d and e
respectively.
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
table composed of two tensors, corresponding to the outputs of d and e
respectively.
-are not already existing. Add edges between every two nodes
-corresponding to a pair of successive modules in the arguments.
+have not been already added in a previous call. Add edges between
+every two nodes associated to two successive modules in the arguments.
-Calling it with n > 2 arguments is strictly equivalent to calling it
-n-1 times on the pairs of successive arguments.
+Calling this function with n > 2 arguments is strictly equivalent to
+calling it n-1 times on the pairs of successive arguments.
Defines 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.
Defines 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.
Save a dot file to be used by the Graphviz set of tools for graph
visualization. This dot file can than be used for instance to produce
Save a dot file to be used by the Graphviz set of tools for graph
visualization. This dot file can than be used for instance to produce