From 05fcde5bf0caa1ceb70fef02fc88eda6f00c5ed5 Mon Sep 17 00:00:00 2001
From: Qi Liu <liuq901@163.com>
Date: Wed, 9 Mar 2016 11:58:13 +0800
Subject: add recipe

---
 lua/select_linear.lua | 62 +++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 62 insertions(+)
 create mode 100644 lua/select_linear.lua

(limited to 'lua/select_linear.lua')

diff --git a/lua/select_linear.lua b/lua/select_linear.lua
new file mode 100644
index 0000000..a7e20cc
--- /dev/null
+++ b/lua/select_linear.lua
@@ -0,0 +1,62 @@
+local SL = nerv.class('nerv.SelectLinearLayer', 'nerv.Layer')
+
+--id: string
+--global_conf: table
+--layer_conf: table
+--Get Parameters
+function SL:__init(id, global_conf, layer_conf)
+    self.id = id
+    self.dim_in = layer_conf.dim_in
+    self.dim_out = layer_conf.dim_out
+    self.gconf = global_conf
+
+    self.vocab = layer_conf.vocab
+    self.ltp = self:find_param("ltp", layer_conf, global_conf, nerv.LinearTransParam, {self.vocab, self.dim_out[1]}) --layer_conf.ltp
+ 
+    self:check_dim_len(1, 1)
+end
+
+--Check parameter 
+function SL:init(batch_size)
+    if (self.dim_in[1] ~= 1) then --one word id 
+        nerv.error("mismatching dimensions of ltp and input")
+    end
+    if (self.dim_out[1] ~= self.ltp.trans:ncol()) then
+        nerv.error("mismatching dimensions of bp and output")
+    end
+    
+    self.batch_size = bath_size
+    self.ltp:train_init()
+end
+
+function SL:update(bp_err, input, output)
+    --use this to produce reproducable result, don't forget to set the dropout to zero!
+    --for i = 1, input[1]:nrow(), 1 do
+    --    local word_vec = self.ltp.trans[input[1][i - 1][0]]
+    --    word_vec:add(word_vec, bp_err[1][i - 1], 1, - self.gconf.lrate / self.gconf.batch_size)
+    --end 
+    
+    --I tried the update_select_rows kernel which uses atomicAdd, but it generates unreproducable result
+    self.ltp.trans:update_select_rows_by_colidx(bp_err[1], input[1], - self.gconf.lrate / self.gconf.batch_size, 0)
+    self.ltp.trans:add(self.ltp.trans, self.ltp.trans, 1.0, - self.gconf.lrate * self.gconf.wcost)
+end
+
+function SL:propagate(input, output)
+    --for i = 0, input[1]:ncol() - 1, 1 do
+    --    if (input[1][0][i] > 0) then
+    --        output[1][i]:copy_fromd(self.ltp.trans[input[1][0][i]])
+    --    else
+    --        output[1][i]:fill(0)
+    --    end
+    --end
+    output[1]:copy_rows_fromd_by_colidx(self.ltp.trans, input[1])
+end
+
+function SL:back_propagate(bp_err, next_bp_err, input, output)
+    --input is compressed, do nothing
+end
+
+function SL:get_params()
+    local paramRepo = nerv.ParamRepo({self.ltp})
+    return paramRepo
+end
-- 
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