library documentation++

1 files changed, 14 insertions, 7 deletions

diff --git a/README.md b/README.md
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@@ -49,24 +49,31 @@ tests:
 ## Library Documentation ##
 This section includes documentation for the following objects:
  * [SoftMaxTree](#nnx.SoftMaxTree) : a hierarchical log-softmax Module;
- * [TreeNLLCriterion](#nnx.TreeNLLCriterion) : a Negative log-likelihodd Criterion for the SoftMaxTree;
+ * [TreeNLLCriterion](#nnx.TreeNLLCriterion) : a negative log-likelihood Criterion for the SoftMaxTree;
 
 <a name='nnx.SoftMaxTree'/>
 ### SoftMaxTree ###
 A hierarchy of parameterized log-softmaxes. Used for computing the likelihood of a leaf class. 
-This Module should be used with the [TreeNLLCriterion](#nnx.TreeNLLCriterion). 
-Requires a Tensor mapping one `parent_id` to many `child_id`. 
-Greatly accelerates learning and testing for language models with large vocabularies. 
+This Module should be used in conjunction with the [TreeNLLCriterion](#nnx.TreeNLLCriterion). 
+Using this for large vocabularies (100,000 and more) greatly accelerates training and evaluation 
+of neural network language models (NNLM). 
 A vocabulary hierarchy is provided via the [dp](https://github.com/nicholas-leonard/dp/blob/master/README.md) package's
 [BillionWords](https://github.com/nicholas-leonard/dp/blob/master/doc/data.md#dp.BillionWords) 
 [DataSource](https://github.com/nicholas-leonard/dp/blob/master/doc/data.md#dp.DataSource).
 
-Computes the log of a product of softmaxes in a path.
-Returns an output tensor of size 1D.
+The constructor takes 2 mandatory and 4 optional arguments : 
+ * `inputSize` : the number of units in the input embedding representation;
+ * `hierarchy` : a Tensor mapping one `parent_id` to many `child_id` (a tree);
+ * `rootId` : a number identifying the root node in the hierarchy. Defaults to `-1`;
+ * `accUpdate` : when the intent is to use `backwardUpdate` or `accUpdateGradParameters`, set this to true to save memory. Defaults to false;
+ * `static` : when true (the defualt), returns parameters with keys that don't change from batch to batch;
+ * `verbose` : prints some additional information concerning the hierarchy during construction.
+
+Method `forward` returns an `output` Tensor of size 1D.
 
 <a name='nnx.TreeNLLCriterion''/>
 ### TreeNLLCriterion ###
-Measures the Negative Log Likelihood (NLL) for [SoftMaxTrees](#nnx.SoftMaxTree). 
+Measures the Negative log-likelihood (NLL) for [SoftMaxTrees](#nnx.SoftMaxTree). 
 Used for maximizing the likelihood of SoftMaxTree outputs.
 The SoftMaxTree Module outputs a column Tensor representing the log likelihood
 of each target in the batch. Thus SoftMaxTree requires the targets.