Merge pull request #37 from liuq901/master

add general trainer

1 files changed, 63 insertions, 0 deletions

diff --git a/nerv/examples/ptb/select_linear.lua b/nerv/examples/ptb/select_linear.lua
new file mode 100644
index 0000000..42778f8
--- /dev/null
+++ b/nerv/examples/ptb/select_linear.lua
@@ -0,0 +1,63 @@
+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)
+    nerv.Layer.__init(self, id, global_conf, layer_conf)
+
+    self.vocab = layer_conf.vocab
+ 
+    self:check_dim_len(1, 1)
+    self:bind_params()
+end
+
+function SL:bind_params()
+    self.ltp = self:find_param("ltp", self.lconf, self.gconf, nerv.LinearTransParam, {self.vocab, self.dim_out[1]}) --layer_conf.ltp
+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()
+    --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:update_by_err_input()
+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
+    self.ltp:back_propagate_by_err_input(bp_err[1], input[1]:decompress(self.vocab))
+end
+
+function SL:get_params()
+    local paramRepo = nerv.ParamRepo({self.ltp}, self.loc_type)
+    return paramRepo
+end