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/config.lua | 67 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 67 insertions(+)
 create mode 100644 lua/config.lua

(limited to 'lua/config.lua')

diff --git a/lua/config.lua b/lua/config.lua
new file mode 100644
index 0000000..9d73b64
--- /dev/null
+++ b/lua/config.lua
@@ -0,0 +1,67 @@
+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 = 1,
+        param_random = function() return (math.random() / 5 - 0.1) end,
+        dropout = 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}},
+        },
+    }
+    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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