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author | Ted Yin <[email protected]> | 2015-06-09 17:28:16 +0800 |
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committer | Ted Yin <[email protected]> | 2015-06-09 17:28:16 +0800 |
commit | c20af45d0756d5d3004105da10e51d42a382ad66 (patch) | |
tree | f646f82082aad806676fe42d16b35b5bda1e0b8c /doc/nerv_layer.md | |
parent | 480de75f52a4f185546978da023a77e27a8644c3 (diff) | |
parent | 3e07a536a89badff65fc81f56bb19cc69291396e (diff) |
Merge pull request #21 from cloudygoose/master
add doc for layers
Diffstat (limited to 'doc/nerv_layer.md')
-rw-r--r-- | doc/nerv_layer.md | 43 |
1 files changed, 43 insertions, 0 deletions
diff --git a/doc/nerv_layer.md b/doc/nerv_layer.md new file mode 100644 index 0000000..dd991df --- /dev/null +++ b/doc/nerv_layer.md @@ -0,0 +1,43 @@ +#The Nerv Layer Package# +Part of the [Nerv](../README.md) toolkit. + +##Description## +__nerv.Layer__ is the base class and most of its methods are abstract. +###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. + * `string id` ID of this layer. + * `table gconf` Stores the `global_conf`. +* __nerv.AffineLayer__ inherits __nerv.Layer__, both `#dim_in` and `#dim_out` are 1. + * `MatrixParam ltp` The liner transform parameter. + * `BiasParam bp` The bias parameter. +* __nerv.BiasLayer__ inherits __nerv.Layer__, both `#dim_in` nad `#dim_out` are 1. + * `BiasParam bias` The bias parameter. +* __nerv.SigmoidLayer__ inherits __nerv.Layer__, both `#dim_in` and `#dim_out` are 1. +* __nerv.SoftmaxCELayer__ inherits __nerv.Layer__, `#dim_in` is 2 and `#dim_out` is 1. + * `float total_ce` + * `int total_frams` Records how many frames have passed. +##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. +* __void Layer.init(Layer self)__ +Abstract method. +Initialization method, in this method the layer should do some self-checking and allocate space for intermediate results. +* __void Layer.update(Layer self, table bp_err, table input, table output)__ +Abstract method. +`bp_err[i]` should be the error on `output[i]`. In this method the parameters of `self` is updated. +* __void Layer.propagate(Layer self, table input, table output)__ +Abstract method. +Given `input` and the current parameters, propagate and store the result in `output`. +* __void Layer.back_propagate(Layer self, Matrix next_bp_err, Matrix bp_err, Matrix input, Matrix output)__ +Abstract method. +Calculate the error on the inputs and store them in `next_bp_err`. + +* __void Layer.check_dim_len(int len_in, int len_out)__ +Check whether `#self.dim_in == len_in` and `#self.dim_out == len_out`, if violated, an error will be posted. +* __void Layer.get_params(Layer self)__ +Abstract method. +The layer should return a list containing its parameters. + |