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View Code? Open in Web Editor NEWpytorch version of code completion with neural attention and pointer networks
License: MIT License
pytorch version of code completion with neural attention and pointer networks
License: MIT License
Hello, and thank you for sharing this work.
Got a little question:
the paper (https://arxiv.org/abs/1711.09573) says we need to encode two additional bits of info for each flattened AST node:
the note about "right" is essential, as otherwise it will be impossible (I believe) to restore the tree.
However, the implementation seems to encode the fact that this node has (any) siblings (not necessarily a "right" one):
Am I missing anything or it's something to be be fixed?
Thank you.
In the original paper, it is said that each program is divided into many short segments (len=50) to feed into model respectively and they are interacted by reusing the hidden states and memory states from previous segment as initial states. However, in this implementation, two points do not fit this description:
This is only my own question for this implementation. Thanks for any explainations or replies.
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