Update.

[dagnn.git] / README.md

diff --git a/README.md b/README.md
index 1d6f5bd..fbb7a96 100644 (file)
--- a/README.md
+++ b/README.md
@@ -1,15 +1,15 @@
 
 

-#Introduction#
+# Introduction #

 
 

-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,
+which inherits from nn.Container and allows to combine modules in an
+arbitrary graph without cycle.

 
 

-##Example##
+## Example ##

 
 A typical use would be:
 
 
 A typical use would be:
 

-```Lua
+```lua

 model = nn.DAG()
 
 a = nn.Linear(100, 10)
 model = nn.DAG()
 
 a = nn.Linear(100, 10)


@@ -48,35 +48,36 @@ Note that DAG:connect allows to add a bunch of edges at once. This is
 particularly useful to add anonymous modules which have a single
 predecessor and successor.
 
 particularly useful to add anonymous modules which have a single
 predecessor and successor.
 

-#Usage#
+# Usage #

 
 

-##Input and output##
+## Input and output ##

 
 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

-as-is as the input of the former. If it has multiple predecessors, all
+as-is as the input to the former. If it has multiple predecessors, all

 the outputs are collected into a table, and the table is used as
 the outputs are collected into a table, and the table is used as

-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

-modules provided to DAG:setInput (respectively DAG:setOutput)
+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
 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.
 

-##Functions##
+## Functions ##

 
 

-###nn.DAG()###
+### nn.DAG() ###

 
 Create a new empty DAG, which inherits from nn.Container.
 
 
 Create a new empty DAG, which inherits from nn.Container.
 

-###nn.DAG:connect([module1 [, module2 [, ...]]])###
+### nn.DAG:connect([module1 [, module2 [, ...]]]) ###

 
 Add new nodes corresponding to the modules passed as arguments if they
 are not already existing. Add edges between every two nodes
 
 Add new nodes corresponding to the modules passed as arguments if they
 are not already existing. Add edges between every two nodes


@@ -85,21 +86,21 @@ corresponding to a pair of 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 it with n > 2 arguments is strictly equivalent to calling it
 n-1 times on the pairs of successive arguments.
 

-###nn.DAG:setInput(i)###
+### nn.DAG:setInput(i) ###

 
 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.
 

-###nn.DAG:setOutput(o)###
+### nn.DAG:setOutput(o) ###

 
 Similar to DAG:setInput().
 
 
 Similar to DAG:setInput().
 

-###nn.DAG:print()###
+### nn.DAG:print() ###

 
 Prints the list of nodes.
 
 
 Prints the list of nodes.
 

-###nn.DAG:saveDot(filename)###
+### nn.DAG:saveDot(filename) ###

 
 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