Comments (2)
profile results:
Sun Oct 22 11:05:26 2017 profile.out
146756150 function calls (145116825 primitive calls) in 73.000 seconds
Ordered by: internal time
List reduced from 1268 to 10 due to restriction <10>
ncalls tottime percall cumtime percall filename:lineno(function)
4504537 7.587 0.000 31.839 0.000 function.py:9(__call__)
1580537 7.151 0.000 41.363 0.000 program.py:114(__call__)
1410769/100 5.208 0.000 72.835 0.728 search.py:68(dfshelper)
5703616 5.193 0.000 6.054 0.000 {method 'join' of 'str' objects}
1440318 4.946 0.000 11.771 0.000 program.py:61(toprefix)
1440318 3.027 0.000 17.003 0.000 program.py:55(__init__)
4505767 2.725 0.000 6.645 0.000 value.py:29(construct)
4504537 2.693 0.000 3.676 0.000 function.py:10(<listcomp>)
1410769 2.193 0.000 43.671 0.000 search.py:56(is_solution)
15290006 1.918 0.000 1.918 0.000 value.py:12(val)
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I read their benchmark wrong- it's a per task timeout (what timeout solves 20%, 40%, 60%, etc of the test set).
For T=3, they had
20% - 41ms
40% - 126ms
60% - 314ms
Depending on the # of inputs, my numbers are pretty close.
Here is # inputs = 2 (my numbers are actually faster)
(deep) Davids-MacBook-Pro:deepcoder dkamm$ python deepcoder/scripts/solve-examples.py --samples deepcoder/dataset/programs_T=3_inputs=2_test_examples.txt --T 3
100%|████████████████████████████████████████████████████████████████████████| 100/100 [00:19<00:00, 5.01it/s]
solved 100/100 (100.00%)
wall (ms) # steps
0.2 1.984119 18.6
0.4 5.795240 58.6
0.6 226.371956 2358.6
0.8 1799.160671 19767.0
1.0 11683.340073 110009.0
Here is # inputs = 3 (my numbers are much slower, max 100k nodes expanded)
(deep) Davids-MacBook-Pro:deepcoder dkamm$ python deepcoder/scripts/solve-examples.py --samples deepcoder/dataset/programs_T=3_inputs=3_test_examples.txt --T 3
100%|████████████████████████████████████████████████████████████████████████| 500/500 [07:01<00:00, 1.19it/s]
solved 190/500 (38.00%)
wall (ms) # steps
0.2 378.281355 3787.8
0.4 9010.549879 100000.0
0.6 9605.433035 100000.0
0.8 10117.793131 100000.0
1.0 13014.326096 100000.0
I'm curious to know the median number of nodes expanded in their datasets. Also I'm exploring roughly 10k nodes per second.
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Related Issues (11)
- Implement sort-and-add
- License ? HOT 5
- _pickle.PicklingError: Can't pickle <function <lambda> at 0x7fb178651c10>: attribute lookup <lambda> on deepcoder.dsl.impl failed HOT 1
- Jupyter notebook of experiments
- Train nn on gcloud gpu
- Code cleanup
- Generate baseline results
- Not able to run HOT 1
- generate the data files HOT 6
- Extending DSL HOT 3
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