1 files changed, 11 insertions, 16 deletions
diff --git a/nerv/layer/dropout.lua b/nerv/layer/dropout.lua
index 42660cc..39a8963 100644
--- a/nerv/layer/dropout.lua
+++ b/nerv/layer/dropout.lua
@@ -1,22 +1,17 @@
 local DropoutLayer = nerv.class("nerv.DropoutLayer", "nerv.Layer")
 
 function DropoutLayer:__init(id, global_conf, layer_conf)
- self.id = id
- self.gconf = global_conf
- if self.gconf.use_cpu then
- self.mat_type = self.gconf.mmat_type
- else
- self.mat_type = self.gconf.cumat_type
- end
- self.rate = layer_conf.dropout_rate or global_conf.dropout_rate
- if self.rate == nil then
+ nerv.Layer.__init(self, id, global_conf, layer_conf)
+ if self.gconf.dropout_rate == nil then
 nerv.warning("[DropoutLayer:propagate] dropout rate is not set")
 end
- self.dim_in = layer_conf.dim_in
- self.dim_out = layer_conf.dim_out
 self:check_dim_len(1, 1) -- two inputs: nn output and label
 end
 
+function DropoutLayer:bind_params()
+ -- do nothing
+end
+
 function DropoutLayer:init(batch_size, chunk_size)
 if self.dim_in[1] ~= self.dim_out[1] then
 nerv.error("mismatching dimensions of input and output")
@@ -45,12 +40,12 @@ function DropoutLayer:propagate(input, output, t)
 if t == nil then
 t = 1
 end
- if self.rate then
+ if self.gconf.dropout_rate ~= 0 then
 self.mask[t]:rand_uniform()
 -- since we will lose a portion of the actvations, we multiply the
 -- activations by 1 / (1 - rate) to compensate
- self.mask[t]:thres_mask(self.mask[t], self.rate,
- 0, 1 / (1.0 - self.rate))
+ self.mask[t]:thres_mask(self.mask[t], self.gconf.dropout_rate,
+ 0, 1 / (1.0 - self.gconf.dropout_rate))
 output[1]:mul_elem(input[1], self.mask[t])
 else
 output[1]:copy_fromd(input[1])
@@ -65,7 +60,7 @@ function DropoutLayer:back_propagate(bp_err, next_bp_err, input, output, t)
 if t == nil then
 t = 1
 end
- if self.rate then
+ if self.gconf.dropout_rate then
 next_bp_err[1]:mul_elem(bp_err[1], self.mask[t])
 else
 next_bp_err[1]:copy_fromd(bp_err[1])
@@ -73,5 +68,5 @@ function DropoutLayer:back_propagate(bp_err, next_bp_err, input, output, t)
 end
 
 function DropoutLayer:get_params()
- return nerv.ParamRepo({})
+ return nerv.ParamRepo({}, self.loc_type)
 end