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pytorch version of code completion with neural attention and pointer networks

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Code-Completion

Pytorch version of code completion with neural attention and pointer networks

TO DO LIST:

  • refactor preprocessing code
  • add python to AST code
  • config for preprocessing
  • join training for type

Requirments list:

  • python3 >= 3.6
  • torch >= 1.2, or tensorboadX for earlier versions
  • pyyaml

Instruction:

  • run python3 preprocess.py for preprocessing
  • run CUDA_VISIBLE_DEVICES=id python3 train.py --config=path/to/config.yml for training with specified config, list of available configscan be found at configs folder

Results for python value prediction (acc@1):

model vocab_size 1k vocab_size 10k vocab_size 50k
simple_lstm 66.33 65.7 61.68, 1 epoch
attn_lstm 64.95 65.77 63.15, 1 epoch
pointer_mixture 66.62 67.05 65.3, 3 epochs

Examples:

Here will be examples of code generation

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