ant l2 -Darg1=./problem/L2/reverse.json

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ant deep -Dapp=./problem/DeepCoder/prog5.json -Ddepth=3

Neo version

Without learning and statistical model ant neodeep -Dapp=./problem/DeepCoder/prog7.json -Ddepth=4 -Dlearn=false -Dstat=false

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With learning and statistical model ant neoDeepOLD -Dapp=./problem/DeepCoder/prog7.json -Ddepth=4 -Dlearn=true -Dstat=true

Note: Neo depth is -1 than deep (e.g. if deep depth is 4, neo depth is 3)

New version of Neo: ant neoDeep -Dapp=./problem/DeepCoder/prog2.json -Ddepth=2 -Dlearn=false -Dstat=false

Note: Neo2 searches by number of lines. Still experimental version that only enumerates partial programs.

Neo for Morpheus

Without n-gram information: ant neoMorpheus -Dapp=./problem/Morpheus/r4.json -Ddepth=3 -Dlearn=false -Dstat=false -Dfile=""

With n-gram information using a file: ant neoMorpheus -Dapp=./problem/Morpheus/r4.json -Ddepth=3 -Dlearn=false -Dstat=false -Dfile="./sketches/sketches-size3.txt"

Set up neural net model

requires:

- Python 2.7

- NumPy and Tensorflow

The latter can be installed using the following commands:

pip install numpy pip install tensorflow

Then, run org.genesys.clients.DeepCoderDeciderMain to test the Python decider.

If a python interpreter other than the default should be used, then create

a text file ./model/tmp/python_path.txt and include the path. For example,

to use /usr/local/bin/python, include "/usr/local/bin/" in this file.