fix duplicate cubic crossings when loading model

When specify "--cubic pnf" crossing at command line and load an initial model "-i vw.bin" with the same cubic cross, it will be applied twice and causing large mismatch. Feature count jumped from 1434 to 1616 for the first example. Looked at the source code. "-q" was properly safe guarded with de-dup logic, but triples were left out. Hence proposing the simple fix for it. It runs fine locally in the same test. 

out/vw.darwin --loss_function logistic -l 0.1 --initial_t 1e6 -b 27 --holdout_off -d /Users/huig/projects/ps_opt/data/vw_data.txt --keep c --keep d --keep e --keep f --keep j --keep k --keep l --keep m --keep n --keep o --keep p --keep r --keep s --keep t --keep u --keep v --keep w -q ev -q ew -q fj -q fk -q fl -q fm -q fn -q fo -q fp -q st -q r: --cubic pnf -f vw.bin
creating quadratic features for pairs: ev ew fj fk fl fm fn fo fp st r: 
creating cubic features for triples: pnf 
using namespaces beginning with: c d e f j k l m n o p r s t u v w 
Num weight bits = 27
learning rate = 0.1
initial_t = 1e+06
power_t = 0.5
using no cache
Reading datafile = /Users/huig/projects/ps_opt/data/vw_data.txt
num sources = 1
average    since         example     example  current  current  current
loss       last          counter      weight    label  predict features
2.373233   2.373233            1         1.0   1.0000  -2.2754     1434
2.846391   3.319548            2         2.0   1.0000  -3.2827      731
1.903481   0.960571            5         4.0   1.0000  -0.8174      897
0.420754   0.138329            8        25.0  -1.0000  -3.1213     1196
0.221305   0.102586           12        67.0  -1.0000  -2.8766      897
0.267882   0.314458           22       134.0   1.0000  -3.2036     1210

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out/vw.darwin --loss_function logistic -l 0.1 --initial_t 1e6 -b 27 --holdout_off -d /Users/huig/projects/ps_opt/data/vw_data.txt --keep c --keep d --keep e --keep f --keep j --keep k --keep l --keep m --keep n --keep o --keep p --keep r --keep s --keep t --keep u --keep v --keep w -q ev -q ew -q fj -q fk -q fl -q fm -q fn -q fo -q fp -q st -q r: --cubic pnf -i vw.bin -f vw2.bin
creating quadratic features for pairs: ev ew fj fk fl fm fn fo fp st r: 
creating cubic features for triples: pnf 
final_regressor = vw2.bin
using namespaces beginning with: c d e f j k l m n o p r s t u v w 
Num weight bits = 27
learning rate = 0.1
initial_t = 1e+06
power_t = 0.5
using no cache
Reading datafile = /Users/huig/projects/ps_opt/data/vw_data.txt
num sources = 1
average    since         example     example  current  current  current
loss       last          counter      weight    label  predict features
3.338374   3.338374            1         1.0   1.0000  -3.3022     1616
3.231990   3.125606            2         2.0   1.0000  -3.0807      909
2.151710   1.071431            5         4.0   1.0000  -0.9686     1031
0.452659   0.129031            8        25.0  -1.0000  -3.8653     1372
0.232247   0.101049           12        67.0  -1.0000  -3.2103     1075
0.259889   0.287531           22       134.0   1.0000  -3.2256     1372