diff options
Diffstat (limited to 'nerv/layer/dropout.lua')
| -rw-r--r-- | nerv/layer/dropout.lua | 11 |
1 files changed, 5 insertions, 6 deletions
diff --git a/nerv/layer/dropout.lua b/nerv/layer/dropout.lua index 1a379c9..de0fb64 100644 --- a/nerv/layer/dropout.lua +++ b/nerv/layer/dropout.lua @@ -2,8 +2,7 @@ local DropoutLayer = nerv.class("nerv.DropoutLayer", "nerv.Layer") function DropoutLayer:__init(id, global_conf, layer_conf) nerv.Layer.__init(self, id, global_conf, layer_conf) - self.rate = layer_conf.dropout_rate or global_conf.dropout_rate - if self.rate == nil then + if self.gconf.dropout_rate == nil then nerv.warning("[DropoutLayer:propagate] dropout rate is not set") end self:check_dim_len(1, 1) -- two inputs: nn output and label @@ -41,12 +40,12 @@ function DropoutLayer:propagate(input, output, t) if t == nil then t = 1 end - if self.rate then + if self.gconf.dropout_rate 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]) @@ -61,7 +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]) |