From 4520b00d36d9c1388c3079333092bdbe6bb8b1b2 Mon Sep 17 00:00:00 2001
From: txh18 <cloudygooseg@gmail.com>
Date: Thu, 24 Dec 2015 22:31:40 +0800
Subject: trying to find a fimpler lstm_v2, then abort

---
 nerv/examples/lmptb/lmptb/lstm_t_v2.lua | 37 +++++++++++++++------------------
 1 file changed, 17 insertions(+), 20 deletions(-)

diff --git a/nerv/examples/lmptb/lmptb/lstm_t_v2.lua b/nerv/examples/lmptb/lmptb/lstm_t_v2.lua
index dc2fe45..e7bf3a7 100644
--- a/nerv/examples/lmptb/lmptb/lstm_t_v2.lua
+++ b/nerv/examples/lmptb/lmptb/lstm_t_v2.lua
@@ -1,5 +1,4 @@
-local LSTMLayerT = nerv.class('nerv.LSTMLayerTv2', 'nerv.LayerT') 
---a version of LSTM that only feed h into the gates
+local LSTMLayerT = nerv.class('nerv.LSTMLayerV2T', 'nerv.LayerT')
 
 function LSTMLayerT:__init(id, global_conf, layer_conf)
     --input1:x input2:h input3:c
@@ -21,13 +20,13 @@ function LSTMLayerT:__init(id, global_conf, layer_conf)
     local layers = {
         ["nerv.CombinerLayer"] = {
             [ap("inputXDup")] = {{}, {["dim_in"] = {self.dim_in[1]}, 
-                ["dim_out"] = {self.dim_in[1], self.dim_in[1], self.dim_in[1], self.dim_in[1]}, ["lambda"] = {1}}},
+                ["dim_out"] = {self.dim_in[1], self.dim_in[1], self.dim_in[1]}, ["lambda"] = {1}}},
             [ap("inputHDup")] = {{}, {["dim_in"] = {self.dim_in[2]}, 
-                ["dim_out"] = {self.dim_in[2], self.dim_in[2], self.dim_in[2], self.dim_in[2]}, ["lambda"] = {1}}},
-            [ap("inputCDup")] = {{}, {["dim_in"] = {self.dim_in[3]}, 
-                ["dim_out"] = {self.dim_in[3]}, ["lambda"] = {1}}},
-            [ap("mainCDup")] = {{}, {["dim_in"] = {self.dim_in[3], self.dim_in[3]}, 
-                ["dim_out"] = {self.dim_in[3], self.dim_in[3]}, ["lambda"] = {1, 1}}},
+                ["dim_out"] = {self.dim_in[2], self.dim_in[2], self.dim_in[2]}, ["lambda"] = {1}}},
+            --[ap("inputCDup")] = {{}, {["dim_in"] = {self.dim_in[3]}, 
+                --["dim_out"] = {self.dim_in[3], self.dim_in[3], self.dim_in[3]}, ["lambda"] = {1}}},
+            [ap("mainCDup")] = {{}, {["dim_in"] = {self.dim_in[3], self.dim_in[3]}, ["dim_out"] = {self.dim_in[3], self.dim_in[3]},
+                ["lambda"] = {1, 1}}},
         },
         ["nerv.AffineLayer"] = {
             [ap("mainAffineL")] = {{}, {["dim_in"] = {self.dim_in[1], self.dim_in[2]}, 
@@ -42,14 +41,14 @@ function LSTMLayerT:__init(id, global_conf, layer_conf)
                 ["dim_out"] = {self.dim_in[3]}, ["pr"] = pr}},
             [ap("inputGateL")] = {{}, {["dim_in"] = {self.dim_in[1], self.dim_in[2]}, 
                 ["dim_out"] = {self.dim_in[3]}, ["pr"] = pr}},
-            [ap("outputGateL")] = {{}, {["dim_in"] = {self.dim_in[1], self.dim_in[2]}, 
-                ["dim_out"] = {self.dim_in[3]}, ["pr"] = pr}},
+            --[ap("outputGateL")] = {{}, {["dim_in"] = {self.dim_in[1], self.dim_in[2], self.dim_in[3]}, 
+            --    ["dim_out"] = {self.dim_in[3]}, ["pr"] = pr}},
 
         },
         ["nerv.ElemMulLayer"] = {
             [ap("inputGMulL")] = {{}, {["dim_in"] = {self.dim_in[3], self.dim_in[3]}, ["dim_out"] = {self.dim_in[3]}}},
             [ap("forgetGMulL")] = {{}, {["dim_in"] = {self.dim_in[3], self.dim_in[3]}, ["dim_out"] = {self.dim_in[3]}}},
-            [ap("outputGMulL")] = {{}, {["dim_in"] = {self.dim_in[3], self.dim_in[3]}, ["dim_out"] = {self.dim_in[3]}}},
+            --[ap("outputGMulL")] = {{}, {["dim_in"] = {self.dim_in[3], self.dim_in[3]}, ["dim_out"] = {self.dim_in[3]}}},
         },
     }
     
@@ -58,38 +57,36 @@ function LSTMLayerT:__init(id, global_conf, layer_conf)
     local connections_t = {
         ["<input>[1]"] = ap("inputXDup[1]"), 
         ["<input>[2]"] = ap("inputHDup[1]"),
-        ["<input>[3]"] = ap("inputCDup[1]"),
 
         [ap("inputXDup[1]")] = ap("mainAffineL[1]"),
         [ap("inputHDup[1]")] = ap("mainAffineL[2]"),
-        
         [ap("mainAffineL[1]")] = ap("mainTanhL[1]"),
 
         [ap("inputXDup[2]")] = ap("inputGateL[1]"),
         [ap("inputHDup[2]")] = ap("inputGateL[2]"),
+        --[ap("inputCDup[1]")] = ap("inputGateL[3]"),
         
         [ap("inputXDup[3]")] = ap("forgetGateL[1]"),
         [ap("inputHDup[3]")] = ap("forgetGateL[2]"),
+        --[ap("inputCDup[2]")] = ap("forgetGateL[3]"),
 
         [ap("mainTanhL[1]")] = ap("inputGMulL[1]"),
         [ap("inputGateL[1]")] = ap("inputGMulL[2]"),
         
-        [ap("inputCDup[1]")] = ap("forgetGMulL[1]"),
+        [ap("<input>[3]")] = ap("forgetGMulL[1]"),
         [ap("forgetGateL[1]")] = ap("forgetGMulL[2]"),
 
         [ap("inputGMulL[1]")] = ap("mainCDup[1]"),
         [ap("forgetGMulL[1]")] = ap("mainCDup[2]"),
 
-        [ap("inputXDup[4]")] = ap("outputGateL[1]"),
-        [ap("inputHDup[4]")] = ap("outputGateL[2]"),
+        --[ap("inputXDup[4]")] = ap("outputGateL[1]"),
+        --[ap("inputHDup[4]")] = ap("outputGateL[2]"),
+        --[ap("mainCDup[3]")] = ap("outputGateL[3]"),
 
         [ap("mainCDup[2]")] = "<output>[2]",
         [ap("mainCDup[1]")] = ap("outputTanhL[1]"),
         
-        [ap("outputTanhL[1]")] = ap("outputGMulL[1]"),
-        [ap("outputGateL[1]")] = ap("outputGMulL[2]"),
-
-        [ap("outputGMulL[1]")] = "<output>[1]",
+        [ap("outputTanhL[1]")] = "<output>[1]",
     }
     self.dagL = nerv.DAGLayerT(self.id, global_conf, 
             {["dim_in"] = self.dim_in, ["dim_out"] = self.dim_out, ["sub_layers"] = layerRepo, 
-- 
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