1 files changed, 19 insertions, 33 deletions

diff --git a/nerv/layer/affine_recurrent.lua b/nerv/layer/affine_recurrent.lua
index d537f4a..fd6f38f 100644
--- a/nerv/layer/affine_recurrent.lua
+++ b/nerv/layer/affine_recurrent.lua
@@ -9,31 +9,37 @@ function Recurrent:__init(id, global_conf, layer_conf)
     self.dim_in = layer_conf.dim_in
     self.dim_out = layer_conf.dim_out
     self.gconf = global_conf
+    self.log_pre = self.id .. "[LOG]"
 
     self.bp = self:find_param("bp", layer_conf, global_conf, nerv.BiasParam, {1, self.dim_out[1]}) --layer_conf.bp
-    self.ltp_hh = self:find_param("ltp_hh", layer_conf, global_conf, nerv.LinearTransParam, {self.dim_in[2], self.dim_out[1]}) --layer_conf.ltp_hh --from hidden to hidden
+    self.ltp_hh = self:find_param("ltphh", layer_conf, global_conf, nerv.LinearTransParam, {self.dim_in[2], self.dim_out[1]}) --layer_conf.ltp_hh --from hidden to hidden
+    self.ltp_ih = self:find_param("ltpih", layer_conf, global_conf, nerv.LinearTransParam, {self.dim_in[1], self.dim_out[1]}) --layer_conf.ltp_hh --from hidden to hidden
     
     self:check_dim_len(2, 1)
     self.direct_update = layer_conf.direct_update
 
     self.clip = layer_conf.clip --clip error in back_propagate
+    if self.clip ~= nil then
+        nerv.info("%s creating, will clip the error by %f", self.log_pre, self.clip)
+    end
 end
 
 --Check parameter 
 function Recurrent:init(batch_size)
-    if (self.ltp_hh.trans:ncol() ~= self.bp.trans:ncol()) then
+    if self.ltp_hh.trans:ncol() ~= self.bp.trans:ncol() or
+       self.ltp_ih.trans:ncol() ~= self.bp.trans:ncol() then
         nerv.error("mismatching dimensions of ltp and bp")
     end
-    if (self.dim_in[1] ~= self.ltp_hh.trans:nrow() or
-        self.dim_in[2] ~= self.ltp_hh.trans:nrow()) then
+    if self.dim_in[1] ~= self.ltp_ih.trans:nrow() or
+        self.dim_in[2] ~= self.ltp_hh.trans:nrow() then
         nerv.error("mismatching dimensions of ltp and input")
     end
     if (self.dim_out[1] ~= self.bp.trans:ncol()) then
         nerv.error("mismatching dimensions of bp and output")
     end
     
-    self.ltp_hh_grad = self.ltp_hh.trans:create()
     self.ltp_hh:train_init()
+    self.ltp_ih:train_init()
     self.bp:train_init()
 end
 
@@ -42,39 +48,19 @@ function Recurrent:batch_resize(batch_size)
 end
 
 function Recurrent:update(bp_err, input, output)
-    if self.direct_update == true then
-        local ltp_hh = self.ltp_hh.trans
-        local bp = self.bp.trans
-        local gconf = self.gconf
-        if (gconf.momentum > 0) then
-            -- momentum gain
-            local mmt_gain = 1.0 / (1.0 - gconf.momentum)
-            local n = input[1]:nrow() * mmt_gain
-            -- update corrections (accumulated errors)
-            self.ltp_hh.correction:mul(input[2], bp_err[1], 1.0, gconf.momentum, 'T', 'N')
-            self.bp.correction:add(self.bp.correction, bp_err[1]:colsum(), gconf.momentum, 1.0)
-            -- perform update and weight decay
-            ltp_hh:add(ltp_hh, self.ltp_hh.correction, 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, - gconf.lrate / n)
-            bp:add(bp, self.bp.correction, 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, - gconf.lrate / n)
-        else
-            ltp_hh:mul(input[2], bp_err[1], - gconf.lrate / gconf.batch_size, 1.0 - gconf.wcost * gconf.lrate / gconf.batch_size, 'T', 'N')
-            bp:add(bp, bp_err[1]:colsum(), 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, - gconf.lrate / gconf.batch_size)
-        end
-    else
-        --self.ltp_hh_grad:mul(input[2], bp_err[1], 1.0, 0.0, 'T', 'N') 
-        self.ltp_hh:update_by_err_input(bp_err[1], input[2])       
-        self.bp:update_by_gradient(bp_err[1]:colsum())
-    end
+    self.ltp_ih:update_by_err_input(bp_err[1], input[1])       
+    self.ltp_hh:update_by_err_input(bp_err[1], input[2])       
+    self.bp:update_by_gradient(bp_err[1]:colsum())
 end
 
 function Recurrent:propagate(input, output)
-    output[1]:copy_fromd(input[1])
+    output[1]:mul(input[1], self.ltp_ih.trans, 1.0, 0.0, 'N', 'N')
     output[1]:mul(input[2], self.ltp_hh.trans, 1.0, 1.0, 'N', 'N')
     output[1]:add_row(self.bp.trans, 1.0)
 end
 
 function Recurrent:back_propagate(bp_err, next_bp_err, input, output)
-    next_bp_err[1]:copy_fromd(bp_err[1])
+    next_bp_err[1]:mul(bp_err[1], self.ltp_ih.trans, 1.0, 0.0, 'N', 'T')
     next_bp_err[2]:mul(bp_err[1], self.ltp_hh.trans, 1.0, 0.0, 'N', 'T')
     --[[
     for i = 0, next_bp_err[2]:nrow() - 1 do
@@ -84,11 +70,11 @@ function Recurrent:back_propagate(bp_err, next_bp_err, input, output)
         end
     end
     ]]--
-    if (self.clip ~= nil) then
-        next_bp_err[2]:clip(- self.clip, self.clip)
+    if self.clip ~= nil then
+        next_bp_err[2]:clip(-self.clip, self.clip)
     end
 end
 
 function Recurrent:get_params()
-    return nerv.ParamRepo({self.ltp_hh, self.bp})
+    return nerv.ParamRepo({self.ltp_ih, self.ltp_hh, self.bp})
 end