Merge branch 'master' of https://speechlab.sjtu.edu.cn/gitlab/Nerv-SJTU/nerv

8 files changed, 60 insertions, 55 deletions

diff --git a/README.md b/README.md
index fe9dfc1..d3843c9 100644
--- a/README.md
+++ b/README.md
@@ -1,9 +1,9 @@
-#The Nerv Toolkit User Manual#
+# The Nerv Toolkit User Manual
 NOTE: This readme is obsolete and will be rearranged, for further information, please check http://nerv-sjtu.github.io/nerv/
 
 This user manual will information about how to use __Nerv__ and __Nerv__'s interface.
 
-##How to make and start using##
+## How to make and start using
 First make sure you have __lua__ and __CUDA__ installed on your computer.  
 __Nerv__ is currently developed via github.You can download and make __Nerv__ by doing the following:
 ```
@@ -29,11 +29,11 @@ You need to be at or (copy files from) `/slfs1`(SJTU speechlab cluster) to get t
 ./install/bin/nerv nerv/examples/asr_trainer.lua nerv/examples/swb_baseline.lua
 ```
 
-##How to contribute##
+## How to contribute
 Fork the original repository, then use the __pull&merge__ function in github to contribute.  
 The pull&merge request can be found on your dashboard in github. See this [sync-help] to sync with the original repository.
 
-##Nerv Packages##
+## Nerv Packages
 * __luaT__  
 Nerv uses [luaT]\(a [Torch] library\) to define lua class in C.
 * __[The Nerv OOP](nerv/doc/nerv_class.md)__  
diff --git a/nerv/doc/nerv.md b/nerv/doc/nerv.md
index 28411f5..125928d 100644
--- a/nerv/doc/nerv.md
+++ b/nerv/doc/nerv.md
@@ -1,6 +1,6 @@
-#The Nerv utility functions#
+# The Nerv utility functions
 Part of the [Nerv](../README.md) toolkit.
-##Methods##
+## Methods
 * __string = nerv.typename(obj a)__  
 A registered function, the original function is `luaT_lua_typename`. In some cases if you call `type(a)`  for object of some class in __Nerv__(like __Nerv.CuMatrix__) it will only return "userdata"(because it is created in C), in this case you can use this method to get its type.
 
@@ -14,4 +14,4 @@ A registered function, the original function is `luaT_newmetatable`, it returns
 * __string = nerv.setmetatable(table self, string tname)__  
 A registered function, the original function is `luaT_lua_setmetatable`. It assigns the metatable registered in __luaT__ by the name *tname* to the table *self*. And return *tname* to user.
 * __table = nerv.get_type(string typename)__  
-Returns the type(`loadstring("return " .. typename)`).
\ No newline at end of file
+Returns the type(`loadstring("return " .. typename)`).
diff --git a/nerv/doc/nerv_class.md b/nerv/doc/nerv_class.md
index 99f63e7..8314b12 100644
--- a/nerv/doc/nerv_class.md
+++ b/nerv/doc/nerv_class.md
@@ -1,10 +1,10 @@
-#The Nerv OOP#
+# The Nerv OOP
 Part of the [Nerv](../README.md) toolkit.
-##Methods##
+## Methods
 * __metatable mt, metatable mpt = nerv.class(string tname, string parenttname)__  
 This method is used to create a class by the name `tname`, which inherits `parenttname` in __Nerv__, then you create a new instance of this class by calling `obj=tname(...)`. The  `tname.__init(...)` method(if defined) will be called in the constructing. The metatable of the class and its parent class will be returned.
 
-##Examples##
+## Examples
 * This example implements a simple `nerv.Counter` class which is inherited by `nerv.BetterCounter`.  
 
 ```
@@ -33,4 +33,4 @@ c1 = nerv.Counter(1)
 print(c1.c)
 bc1 = nerv.BetterCounter(1, 1)
 print(bc1.c, bc1.bc)
-```
\ No newline at end of file
+```
diff --git a/nerv/doc/nerv_io.md b/nerv/doc/nerv_io.md
index 07589df..299362f 100644
--- a/nerv/doc/nerv_io.md
+++ b/nerv/doc/nerv_io.md
@@ -1,7 +1,7 @@
-#The Nerv IO Package#
+# The Nerv IO Package
 Part of the [Nerv](../README.md) toolkit.
 
-##Description##
+## Description
 The main class that the user uses to store and read parameter object to and from files is __nerv.ChunkFile__.  
 In the file, a parameter object will be saved using a standard format. First is the length(in byte) of this object, then a table which includes some meta information of the object, and a data area. Below is an example text file.  
 ```
@@ -23,7 +23,7 @@ In the file, a parameter object will be saved using a standard format. First is
 3.000000 3.000000 3.000000 
 ```
 
-##Methods##
+## Methods
 * __ChunkFile ChunkFile(string fn, string mode)__  
 `mode` can be `r` or `w`, for reading or writing a file. The returned __ChunkFile__ will be ready to write or read objects which follows the __nerv.Param__ interface(using `write_chunk` and `read_chunk`). 
 * __void ChunkFile.write_chunk(ChunkFile self, Param p)__  
@@ -33,7 +33,7 @@ Read the __Param__ object by id `id` from the file `self`. It will be constructe
 * __void ChunkFile.close(ChunkFile self)__  
 Close the opened file.
 
-##Examples##
+## Examples
 * An example showing how to use __ChunkFile__ to store and read parameter objects.
 ```
 require 'io'
@@ -96,7 +96,7 @@ do
 end
 ```
 
-##Developer Notes##
+## Developer Notes
 * There are four classes in to deal with chunk data, which are __nerv.ChunkFile__, __nerv.ChunkFileHandle__, __nerv.ChunkInfo__, __nerv.ChunkData__. Below is the underlying C structs.
 ```
 typedef struct ChunkFileHandle {
@@ -110,4 +110,5 @@ typedef struct ChunkData {
     char *data;
 } ChunkData;
 ```
-* In __Nerv.io__, a returned(by `ChunkFile.__init`) __nerv.ChunkFile__ will have a member `handle`, which is a __nerv.ChunkFileHandle__.  
\ No newline at end of file
+
+* In __Nerv.io__, a returned(by `ChunkFile.__init`) __nerv.ChunkFile__ will have a member `handle`, which is a __nerv.ChunkFileHandle__.  
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]]--
 ```
+
diff --git a/nerv/doc/nerv_matrix.md b/nerv/doc/nerv_matrix.md
index dfd843d..7555e6c 100644
--- a/nerv/doc/nerv_matrix.md
+++ b/nerv/doc/nerv_matrix.md
@@ -1,8 +1,8 @@
-#The Nerv Matrix Package#
+# The Nerv Matrix Package
 Part of the [Nerv](../README.md) toolkit.
 
-##Description##
-###Underlying structure###
+## Description
+### Underlying structure
 In the begining is could be useful to know something about the underlying structure of a __Nerv__ matrix. Please keep in mind that matrice in __Nerv__ is row-major.  
 Every matrix object is a encapsulation of a C struct that describes the attributes of this matrix.  
 ```
@@ -20,12 +20,12 @@ typedef struct Matrix {
 It is worth mentioning that that `data_ref` is a counter which counts the number of references to its memory space, mind that it will also be increased when a row of the matrix is referenced(`col = m[2]`). A __Nerv__ matrix will deallocate its space when this counter is decreased to zero.
 Also note that all assigning operation in __Nerv__ is reference copy, you can use `copy_tod` or `copy_toh` method to copy value. Also, row assigning operations like `m1[2]=m2[3]` is forbidden in __Nerv__.
 
-###Class hierarchy###
+### Class hierarchy
 The class hierarchy of the matrix classes can be clearly observed in `matrix/init.c`.
 First there is a abstract base class __Nerv.Matrix__, which is inherited by __Nerv.CuMatrix__ and __Nerv.MMatrix__(also abstract).  
 Finally, there is __Nerv.CuMatrixFloat__, __Nerv.CuMatrixDouble__, inheriting __Nerv.CuMatrix__, and __Nerv.MMatrixFloat__, __Nerv.MMatrixDouble__, __Nerv.MMatrixInt__ , inheriting __Nerv.MMatrix__.
 
-##Methods##
+## Methods
 Mind that usually a matrix object can only do calculation with matrix of its own type(a __Nerv.CuMatrixFloat__ matrix can only do add operation with a __Nerv.CuMatrixFloat__).  
 In the methods description below, __Matrix__ could be __Nerv.CuMatrixFloat__, __Nerv.CuMatrixDouble__, __Nerv.MMatrixFloat__ or __Nerv.MMatrixDouble__. __Element_type__ could be `float` or `double`, respectively.
 * __Matrix = Matrix(int nrow, int ncol)__  
@@ -113,7 +113,7 @@ Write `self` to the file position in `chunk`.
 * __void MMatrix.copy_from(MMatrix ma, MMatrix mb,[int b_bgein, int b_end, int a_begin])__  
 Copy a part of `mb`(rows of index `[b_begin..b_end)`) to `ma` beginning at row index `a_begin`. If not specified, `b_begin` will be `0`, `b_end` will be `b.nrow`, `a_begin` will be `0`.
 
-##Examples##
+## Examples
 * Use `get_dataref_value` to test __Nerv__'s matrix space allocation.  
 ```
 m = 10
@@ -134,6 +134,7 @@ print("test fm:get_dataref_value:", fm:get_dataref_value())
 print(fm)
 print(dm)
 ```
+
 * Test some __Matrix__ calculations.
 ```
 m = 4
@@ -167,3 +168,4 @@ print(a)
 a:log_elem(fs)
 print(a)
 ```
+
diff --git a/nerv/doc/nerv_nn.md b/nerv/doc/nerv_nn.md
index c57447d..63537fb 100644
--- a/nerv/doc/nerv_nn.md
+++ b/nerv/doc/nerv_nn.md
@@ -1,19 +1,19 @@
-#The Nerv NN Package#
+# The Nerv NN Package
 Part of the [Nerv](../README.md) toolkit.
 
-##Description##
-###Class hierarchy###
+## Description
+### Class hierarchy
 it contains __nerv.LayerRepo__, __nerv.ParamRepo__, and __nerv.DAGLayer__(inherits __nerv.Layer__).
 
-###Class hierarchy and their members###
-####nerv.ParamRepo#### 
+### Class hierarchy and their members
+#### nerv.ParamRepo
 Get parameter object by ID.  
 *	`table param_table` Contains the mapping of parameter ID to parameter file(__nerv.ChunkFile__)  
 *  __nerv.LayerRepo__ Get layer object by ID.  
 * 	`table layers` Contains the mapping of layer ID to layer object.
 objects.
 
-####__nerv.DAGLayer__####
+#### __nerv.DAGLayer__
 Inherits __nerv.Layer__.  
 * 	`layers`: __table__, a mapping from a layer ID to its "ref". A ref is a structure that contains reference to space allocations and other info of the layer.
 * 	`inputs`: __table__, a mapping from the inputs ports of the DAG layer to the input ports of the sublayer, the key is the port number, the value is `{ref, port}`.
@@ -21,17 +21,17 @@ Inherits __nerv.Layer__.
 * 	`parsed_conn`: __table__, a list of parsed connections, each entry is of format `{{ref_from, port_from}, {ref_to, port_to}}`.
 * 	`queue`: __table__, a list of "ref"s, the propagation of the DAGLayer will follow this order, and back-propagation will follow a reverse order.
 	
-##Methods##
+## Methods
 
-###__nerv.ParamRepo__###
+### __nerv.ParamRepo__
 
-####nerv.ParamRepo:\_\_init(param\_files)####
+#### nerv.ParamRepo:\_\_init(param\_files)
 * 	Parameters:  
 	`param_files`: __table__
 *	Description:  
 	`param_files` is a list of file names that stores parameters, the newed __ParamRepo__ will read them from file and store the mapping for future fetching.  
     
-####nerv.Param ParamRepo.get_param(ParamRepo self, string pid, table global_conf)####
+#### nerv.Param ParamRepo.get_param(ParamRepo self, string pid, table global_conf)
 *	Returns:  
 	__nerv.Layer__  
 *	Parameters:  
@@ -41,8 +41,8 @@ Inherits __nerv.Layer__.
 *	Description:  
 	__ParamRepo__ will find the __nerv.ChunkFile__ `pf` that contains parameter of ID `pid` and return `pf:read_chunk(pid, global_conf)`.
 
-###__nerv.LayerRepo__###
-####nerv.LayerRepo:\_\_init(layer\_spec, param\_repo, global\_conf)####
+### __nerv.LayerRepo__
+#### nerv.LayerRepo:\_\_init(layer\_spec, param\_repo, global\_conf)
 * 	Returns:  
   	__nerv.LayerRepo__.  
 * 	Parameters:  
@@ -60,7 +60,7 @@ Inherits __nerv.Layer__.
     
   	__LayerRepo__ will merge `param_config` into `layer_config` and construct a layer by calling `layer_type(layerid, global_conf, layer_config)`.    
 
-####nerv.LayerRepo.get\_layer(self, lid)####
+#### nerv.LayerRepo.get\_layer(self, lid)
 * 	Returns:  
 	__nerv.LayerRepo__, the layer with ID `lid`.
 * 	Parameters:  
@@ -69,8 +69,8 @@ Inherits __nerv.Layer__.
 *	Description:   
 	Returns the layer with ID `lid`.
     
-###nerv.DAGLayer###
-####nerv.DAGLayer:\_\_init(id, global\_conf, layer\_conf)####
+### nerv.DAGLayer
+#### nerv.DAGLayer:\_\_init(id, global\_conf, layer\_conf)
 *	Returns:  
 	__nerv.DAGLayer__  
 *	Parameters:  
@@ -89,7 +89,7 @@ Inherits __nerv.Layer__.
   	}})
     ```
     
-####nerv.DAGLayer.init(self, batch\_size)####
+#### nerv.DAGLayer.init(self, batch\_size)
 *	Parameters:  
 	`self`: __nerv.DAGLayer__  
     `batch_size`: __int__
@@ -97,7 +97,7 @@ Inherits __nerv.Layer__.
 	This initialization method will allocate space for output and input matrice, and will call `init()` for each of its sub layers.
     
 
-####nerv.DAGLayer.propagate(self, input, output)####
+#### nerv.DAGLayer.propagate(self, input, output)
 *	Parameters:  
 	`self`: __nerv.DAGLayer__  
     `input`: __table__  
@@ -105,7 +105,7 @@ Inherits __nerv.Layer__.
 *	Description:  
 	The same function as __nerv.Layer.propagate__, do propagation for each layer in the order of `self.queue`.
 
-####nerv.DAGLayer.back\_propagate(self, next\_bp\_err, bp\_err, input, output)####
+#### nerv.DAGLayer.back\_propagate(self, next\_bp\_err, bp\_err, input, output)
 *	Parameters:  
 	`self`: __nerv.DAGLayer__  
     `next_bp_err`: __table__  
@@ -115,7 +115,7 @@ Inherits __nerv.Layer__.
 *	Description:  
 	The same function as __nerv.Layer.back_propagate__, do back-propagation for each layer in the reverse order of `self.queue`.
 
-####nerv.DAGLayer.update(self, bp\_err, input, output)####
+#### nerv.DAGLayer.update(self, bp\_err, input, output)
 *	Parameters:  
 	`self`: __nerv.DAGLayer__  
     `bp_err`: __table__  
@@ -124,7 +124,7 @@ Inherits __nerv.Layer__.
 *	Description:  
 	The same function as __nerv.Layer.update__, do update for each layer in the order of `self.queue`.
     
-##Examples##
+## Examples
 *	aaa
 	
 ```
@@ -253,4 +253,5 @@ for l = 0, 10, 1 do
     ce_last = softmaxL.total_ce 
 end
 --[[end training]]--
-```
\ No newline at end of file
+```
+
diff --git a/nerv/doc/nerv_param.md b/nerv/doc/nerv_param.md
index 167cb11..98793f0 100644
--- a/nerv/doc/nerv_param.md
+++ b/nerv/doc/nerv_param.md
@@ -1,17 +1,17 @@
-#The Nerv Parameter Package#
+# The Nerv Parameter Package
 Part of the [Nerv](../README.md) toolkit.
 
-##Description##
-###Class hierarchy###
+## Description
+### Class hierarchy
 There is a base class __Nerv.Param__ defined in `layer/init.lua`.
 
-###Class hierarchy and their members###
+### Class hierarchy and their members
 * __nerv.MatrixParam__ inherits __nerv.Param__  
 	* `Matrix trans` stores the parameter matrix.
 * __nerv.LinearTransParam__ inherits __Nerv.MatrixParam__.  
 * __Nerv.BiasParam__ inherits __Nerv.MatrixParam__.  
 
-##Methods##
+## Methods
 * __void Param.\_\_init(Param self, string id, table global_conf)__  
 Constructor of a __Param__, it will set `self.id` to be `id` and `self.gconf` to be `global_conf`.
 * __void Param.set_info(Param self, table info)__