#The Nerv NN Package#
Part of the [Nerv](../README.md) toolkit.
##Description##
###Class hierarchy###
it contains __nerv.LayerRepo__, __nerv.ParamRepo__, and __nerv.DAGLayer__(inherits __nerv.Layer__).
###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__ inherits __nerv.Layer__.
* `table layers` Mapping from a layer ID to its "ref". A ref is of the structure below:
```
nerv.Layer layer --its layer
nerv.Matrix inputs
nerv.Matrix outputs
nerv.Matrix err_inputs
nerv.Matrix err_outputs
table next_layers
int input_len -- #dim_in
int output_len -- #dim_out
int in_deg
bool visited -- used in topology sort
```
* `inputs`
* `outputs`
* `parsed_conn`
* `queue`
##Methods##
###__nerv.ParamRepo__###
* __void ParamRepo:\_\_init(table param_files)__
`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)__
__ParamRepo__ will find the __nerv.ChunkFile__ `pf` that contains parameter of ID `pid` and return `pf:read_chunk(pid, global_conf)`.
###__nerv.LayerRepo__###
* __void LayerRepo:\_\_init(table layer_spec, ParamRepo param_repo, table global_conf)__
__LayerRepo__ will construct the layers specified in `layer_spec`. Every entry in the `layer_spec` table should follow the format below:
```
layer_spec : {[layer_type1] = llist1, [layer_type2] = llist2, ...}
llist : {layer1, layer2, ...}
layer : layerid = {param_config, layer_config}
param_config : {param1 = paramID1, param2 = paramID2}
```
__LayerRepo__ will merge `param_config` into `layer_config` and construct a layer by calling `layer_type(layerid, global_conf, layer_config)`.
* __[nerv.Layer] LayerRepo.get_layer([LayerRepo] self, [string] lid)__
`self`, __nerv.LayerRepo__, ...
Returns the layer with ID `lid`.
###__nerv.DAGLayer__###
* __DAGLayer:\_\_init(id, global_conf, layer_conf, [a, b, ...])__
Returns:
__string__, dfdfdfddf
__asasa__, asasasasa
Parameters:
`id`: __string__, the ID of the layer.
`global_conf`:__table__,the global config.
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