From e2a9af061db485d4388902d738c9d8be3f94ab34 Mon Sep 17 00:00:00 2001
From: Qi Liu <liuq901@163.com>
Date: Fri, 11 Mar 2016 20:11:00 +0800
Subject: add recipe and fix bugs

---
 lua/config.lua | 67 ----------------------------------------------------------
 1 file changed, 67 deletions(-)
 delete mode 100644 lua/config.lua

(limited to 'lua/config.lua')

diff --git a/lua/config.lua b/lua/config.lua
deleted file mode 100644
index ff98ae0..0000000
--- a/lua/config.lua
+++ /dev/null
@@ -1,67 +0,0 @@
-function get_global_conf()
-    local global_conf = {
-        lrate = 0.15,
-        wcost = 1e-5,
-        momentum = 0,
-        clip = 5,
-        cumat_type = nerv.CuMatrixFloat,
-        mmat_type = nerv.MMatrixFloat,
-        vocab_size = 10000,
-        nn_act_default = 0,
-        hidden_size = 300,
-        layer_num = 1,
-        chunk_size = 15,
-        batch_size = 20,
-        max_iter = 35,
-        param_random = function() return (math.random() / 5 - 0.1) end,
-        dropout_rate = 0.5,
-        timer = nerv.Timer(),
-        pr = nerv.ParamRepo(),
-    }
-    return global_conf
-end
-
-function get_layers(global_conf)
-    local pr = global_conf.pr
-    local layers = {
-        ['nerv.LSTMLayer'] = {},
-        ['nerv.DropoutLayer'] = {},
-        ['nerv.SelectLinearLayer'] = {
-            ['select'] = {dim_in = {1}, dim_out = {global_conf.hidden_size}, vocab = global_conf.vocab_size, pr = pr},
-        },
-        ['nerv.CombinerLayer'] = {},
-        ['nerv.AffineLayer'] = {
-            output = {dim_in = {global_conf.hidden_size}, dim_out = {global_conf.vocab_size}, pr = pr}
-        },
-        ['nerv.SoftmaxCELayer'] = {
-            softmax = {dim_in = {global_conf.vocab_size, global_conf.vocab_size}, dim_out = {1}, compressed = true},
-        },
-    }
-    for i = 1, global_conf.layer_num do
-        layers['nerv.LSTMLayer']['lstm' .. i] = {dim_in = {global_conf.hidden_size, global_conf.hidden_size, global_conf.hidden_size}, dim_out = {global_conf.hidden_size, global_conf.hidden_size}, pr = pr}
-        layers['nerv.DropoutLayer']['dropout' .. i] = {dim_in = {global_conf.hidden_size}, dim_out = {global_conf.hidden_size}}
-        layers['nerv.CombinerLayer']['dup' .. i] = {dim_in = {global_conf.hidden_size}, dim_out = {global_conf.hidden_size, global_conf.hidden_size}, lambda = {1}}
-    end
-    return layers
-end
-
-function get_connections(global_conf)
-    local connections = {
-        {'<input>[1]', 'select[1]', 0},
-        {'select[1]', 'lstm1[1]', 0},
-        {'dropout' .. global_conf.layer_num .. '[1]', 'output[1]', 0},
-        {'output[1]', 'softmax[1]', 0},
-        {'<input>[2]', 'softmax[2]', 0},
-        {'softmax[1]', '<output>[1]', 0},
-    }
-    for i = 1, global_conf.layer_num do
-        table.insert(connections, {'lstm' .. i .. '[1]', 'dup' .. i .. '[1]', 0})
-        table.insert(connections, {'lstm' .. i .. '[2]', 'lstm' .. i .. '[3]', 1})
-        table.insert(connections, {'dup' .. i .. '[1]', 'lstm' .. i .. '[2]', 1})
-        table.insert(connections, {'dup' .. i .. '[2]', 'dropout' .. i .. '[1]', 0})
-        if i > 1 then
-            table.insert(connections, {'dropout' .. (i - 1) .. '[1]', 'lstm' .. i .. '[1]', 0})
-        end
-    end
-    return connections
-end
-- 
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