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-rw-r--r--nerv/doc/nerv_layer.md13
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diff --git a/nerv/doc/nerv_layer.md b/nerv/doc/nerv_layer.md
index de2fb12..dd7c9bb 100644
--- a/nerv/doc/nerv_layer.md
+++ b/nerv/doc/nerv_layer.md
@@ -1,9 +1,9 @@
-#The Nerv Layer Package#
+# The Nerv Layer Package
Part of the [Nerv](../README.md) toolkit.
-##Description##
+## Description
__nerv.Layer__ is the base class and most of its methods are abstract.
-###Class hierarchy and their members###
+### Class hierarchy and their members
* __nerv.Layer__.
* `table dim_in` It specifies the dimensions of the inputs.
* `table dim_out` It specifies the dimensions of the outputs.
@@ -20,7 +20,7 @@ __nerv.Layer__ is the base class and most of its methods are abstract.
* `int total_frams` Records how many frames have passed.
* `bool compressed` The reference distribution can be a one-hot format. This feature is enabled by `layer_conf.compressed`.
-##Methods##
+## Methods
* __void Layer.\_\_init(Layer self, string id, table global_conf, table layer_conf)__
Abstract method.
The constructing method should assign `id` to `self.id` and `global_conf` to `self.gconf`, `layer_conf.dim_in` to `self.dim_in`, `layer_conf.dim_out` to `self.dim_out`. `dim_in` and `dim_out` are a list specifies the dimensions of the inputs and outputs. Also, `layer_conf` will include the parameters, which should also be properly saved.
@@ -43,7 +43,7 @@ Check whether `#self.dim_in == len_in` and `#self.dim_out == len_out`, if violat
Abstract method.
The layer should return a list containing its parameters.
-####nerv.Layer.get\_dim(self)####
+#### nerv.Layer.get\_dim(self)
* Returns:
`dim_in`: __table__.
`dim_out`: __table__.
@@ -52,7 +52,7 @@ The layer should return a list containing its parameters.
* Description:
Returns `self.dim_in, self.dim_out`.
-##Examples##
+## Examples
* a basic example using __Nerv__ layers to a linear classification.
```
@@ -178,3 +178,4 @@ for l = 0, 10, 1 do
end
--[[end training]]--
```
+