Learning to Execute
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wojciechz Merge pull request #4 from AjayTalati/master
Added dropout, replaced sgd with adam optimizer
Latest commit dc6baf6 Apr 9, 2016


Learning to Execute

This software allows to train a Recurrent Neural Network (RNN) with Long-Short Term Memory (LSTM) units on short snippets of python code. The Network is trained to predict the output of the generated programs.


Please install Torch 7 http://torch.ch/ with the cunn package. Moreover, our software requires an NVIDIA GPU.

To execute the program, call:

torch main.lua

This program starts training the LSTM and displays intermediate results. main.lua can be executed with the following options:

torch main.lua -gpuidx 1 -target_length 6 -target_nesting 3
  • gpuidx: chooses a GPU for the program
  • target_length: is a maximum number of digits in every number generated in test programs in a test dataset.
  • target_nesting: is the depth of the nesting in the generated programs in the test dataset.

Moreover, the command

torch data.lua

verifies that training data is correct by evaluating 1000 samples with a python interpreter (python2.7 is required).

More information about the scientific work is provided at http://arxiv.org/abs/1410.4615

This software is located at https://github.com/wojciechz/learning_to_execute