From f26288ba61d3d16866e1b227a71e7d9c46923436 Mon Sep 17 00:00:00 2001
From: Qi Liu <liuq901@163.com>
Date: Fri, 11 Mar 2016 13:32:00 +0800
Subject: update mini_batch_init

---
 nerv/nn/network.lua | 63 +++++++++++++++++++++++++++++++----------------------
 1 file changed, 37 insertions(+), 26 deletions(-)

(limited to 'nerv/nn/network.lua')

diff --git a/nerv/nn/network.lua b/nerv/nn/network.lua
index 39df5f0..35e11e3 100644
--- a/nerv/nn/network.lua
+++ b/nerv/nn/network.lua
@@ -2,8 +2,9 @@ local network = nerv.class('nerv.Network')
 
 function network:__init(id, global_conf, network_conf)
     self.id = id
-    self.dim_in = network_conf.network.dim_in
-    self.dim_out = network_conf.network.dim_out
+    self.network = network_conf.network
+    self.dim_in = self.network.dim_in
+    self.dim_out = self.network.dim_out
     self.gconf = global_conf
     if self.gconf.use_cpu then
         self.mat_type = self.gconf.mmat_type
@@ -18,7 +19,6 @@ function network:__init(id, global_conf, network_conf)
     self.layers = {}
     self.input_conn = {}
     self.output_conn = {}
-    self.network = network_conf.network
     self.socket = self:compile(self.network)
     for i = 1, #self.dim_in do
         local edge = self.socket.inputs[i]
@@ -368,8 +368,21 @@ function network:set_err_output(err_output)
     end
 end
 
-function network:mini_batch_init(information)
-    self.info = information
+--[[
+    [info] is a table that contains information of current mini-batch. These fields must be contained:
+        [input], [output] : matrix array which stores the network input and output
+        [seq_length] : a table contains the length of every sequences
+        [new_seq]: a table contains the batch number of new sequences
+        [do_train]: a bool value indicates do train or not
+        if [do_train] is true, these fileds also must be contained:
+            [err_input], [err_output] : matrix array which stores the network err_input and err_output
+--]]
+function network:mini_batch_init(info)
+    self.info = info
+    self:set_input(self.info.input)
+    self:set_output(self.info.output)
+
+    -- calculate border
     self.max_length = 0
     self.border = {}
     for i = 1, self.chunk_size do
@@ -387,6 +400,7 @@ function network:mini_batch_init(information)
             table.insert(self.border[chunk], i)
         end
     end
+
     -- copy legacy
     for t = 1 - self.delay, 0 do
         for i = 1, #self.layers do
@@ -402,23 +416,27 @@ function network:mini_batch_init(information)
             end
         end
     end
-    -- flush border gradient
-    for t = self.max_length + 1, self.max_length + self.delay do
-        if t > self.chunk_size then
-            break
-        end
-        for i = 1, #self.layers do
-            local dim_in, _ = self.layers[i]:get_dim()
-            for j = 1, #dim_in do
-                self.err_output[t][i][j]:fill(0)
+
+    if self.info.do_train then
+        self:set_err_input(self.info.err_input)
+        self:set_err_output(self.info.err_output)
+        
+        -- flush border gradient
+        for t = self.max_length + 1, self.max_length + self.delay do
+            if t > self.chunk_size then
+                break
+            end
+            for i = 1, #self.layers do
+                local dim_in, _ = self.layers[i]:get_dim()
+                for j = 1, #dim_in do
+                    self.err_output[t][i][j]:fill(0)
+                end
             end
         end
     end
 end
 
-function network:propagate(input, output)
-    self:set_input(input)
-    self:set_output(output)
+function network:propagate()
     for i = 1, #self.queue do
         local t, id = self.queue[i].chunk, self.queue[i].id
         if t <= self.max_length then
@@ -435,11 +453,7 @@ function network:propagate(input, output)
     end
 end
 
-function network:back_propagate(bp_err, next_bp_err, input, output)
-    self:set_input(input)
-    self:set_output(output)
-    self:set_err_input(bp_err)
-    self:set_err_output(next_bp_err)
+function network:back_propagate()
     for i = #self.queue, 1, -1 do
         local t, id = self.queue[i].chunk, self.queue[i].id
         if t <= self.max_length then
@@ -462,10 +476,7 @@ function network:back_propagate(bp_err, next_bp_err, input, output)
     end
 end
 
-function network:update(bp_err, input, output)
-    self:set_input(input)
-    self:set_output(output)
-    self:set_err_input(bp_err)
+function network:update()
     for i = 1, #self.queue do
         local t, id = self.queue[i].chunk, self.queue[i].id
         if t <= self.max_length then
-- 
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