-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathtree.config
55 lines (55 loc) · 2.64 KB
/
tree.config
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
dotproduct x_dot_y()
-all_user dnn([$kfactors,$kfactors,$kfactors], activation='tanh',bn=True,keep_prob=None)
--tanh_user tf.nn.tanh()
---merge_user concat($kfactors)
----huser lookup(dataname='user', initrange=$initrange, shape=[None, $kfactors])
----hage dnn([$kfactors,$kfactors,$kfactors],activation='tanh',bn=True,keep_prob=None)
-----agelookup embedding()
------age placeholder(tf.float32)
------user placeholder(tf.int32)
----hsex dnn([$kfactors,$kfactors,$kfactors],activation='tanh',bn=True,keep_prob=None)
-----sexlookup embedding()
------sex_weights weights('tnorm', tf.float32, [2, $kfactors])
------sexes embedding()
-------sex placeholder(tf.int32)
-------user placeholder(tf.int32)
----hocc dnn([$kfactors,$kfactors,$kfactors],activation='tanh',bn=True,keep_prob=None)
-----occlookup embedding()
------occ_weights weights('tnorm', tf.float32, [21, $kfactors])
------occs embedding()
-------occ placeholder(tf.int32)
-------user placeholder(tf.int32)
----hzip dnn([$kfactors,$kfactors,$kfactors],activation='tanh',bn=True,keep_prob=None)
-----ziplookup embedding()
------zip_weights weights('tnorm', tf.float32, [1000, $kfactors])
------zips embedding()
-------zip placeholder(tf.int32)
-------user placeholder(tf.int32)
----husertime dnn([$kfactors,$kfactors,$kfactors],activation='tanh',bn=True,keep_prob=None)
-----time placeholder(tf.float32)
-all_item dnn([$kfactors,$kfactors,$kfactors], activation='tanh',bn=True,keep_prob=None)
--tanh_item tf.nn.tanh()
---merge_item concat($kfactors)
----hitem lookup(dataname='item', initrange=$initrange, shape=[None, $kfactors])
----hgenre dnn([$kfactors,$kfactors,$kfactors],activation='tanh',bn=True,keep_prob=None)
-----genrelookup embedding()
------genres placeholder(tf.float32)
------item placeholder(tf.int32)
----hmonth dnn([$kfactors,$kfactors,$kfactors],activation='tanh',bn=True,keep_prob=None)
-----monthlookup embedding()
------month_weights weights('tnorm', tf.float32, [12, $kfactors])
------months embedding()
-------month placeholder(tf.int32)
-------item placeholder(tf.int32)
----hyear dnn([$kfactors,$kfactors,$kfactors],activation='tanh',bn=True,keep_prob=None)
-----yearlookup embedding()
------year placeholder(tf.float32)
------item placeholder(tf.int32)
----htfidf dnn([$kfactors,$kfactors,$kfactors],activation='tanh',bn=True,keep_prob=None)
-----tfidflookup embedding()
------tfidf_doc_term placeholder(tf.float32)
------item placeholder(tf.int32)
----hitemtime dnn([$kfactors,$kfactors,$kfactors],activation='tanh',bn=True,keep_prob=None)
-----time placeholder(tf.float32)
-ibias lookup(dataname='item', shape=[None, 1], initrange=$initrange)
-ubias lookup(dataname='user', shape=[None, 1], initrange=$initrange)