From: Francois Fleuret Date: Fri, 13 Jan 2017 22:14:08 +0000 (+0100) Subject: Cosmetics. X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=5a149d40e14c1931103514b41c56a4139f06973a;p=dagnn.git Cosmetics. --- diff --git a/README.md b/README.md index f370b71..436aa63 100644 --- a/README.md +++ b/README.md @@ -65,13 +65,13 @@ 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. -#Usage# +##Usage## -##nn.DAG()## +###nn.DAG()### 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 @@ -80,21 +80,21 @@ 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. -##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 module. 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(). -##nn.DAG:print()## +###nn.DAG:print()### 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 @@ -104,15 +104,15 @@ a pdf file with dot graph.dot -T pdf -o graph.pdf ``` -##nn.DAG:updateOutput(input)## +###nn.DAG:updateOutput(input)### See the torch documentation. -##nn.DAG:updateGradInput(input, gradOutput)## +###nn.DAG:updateGradInput(input, gradOutput)### See the torch documentation. -##nn.DAG:accGradParameters(input, gradOutput, scale)## +###nn.DAG:accGradParameters(input, gradOutput, scale)### See the torch documentation.