Comments (3)
another solution could be to host the data in some university box/drop box link that doesn't die (since universities usually pay for box or drop box).
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also why aren't we extracting the test data?
for split in ['train', 'valid']:
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For the path problem: I think requiring a specific path won't be problematic since one could always use symbolic links even if the data is stored somewhere else. But I agree it would be great to have a more flexible way of handling paths in the code.
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For the global variable, feel free to submit a pull request.
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For
for split in ['train', 'valid']
: Our model is trained to predict individual proof steps. That's why we extract proof steps for training and validation. For testing, however, the goal for the model is to generate a correct proof rather than predicting a single proof step. See eval_env.py and agent.py for details.
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Related Issues (20)
- What is the train, val, test splits? HOT 1
- Code for bottom up tree traversal and parser for terms str to AST HOT 4
- How is the mapping of individual words (or symbols) to vectors is done HOT 3
- How to efficiently process a batch of terms in one go for Tree Neural Networks HOT 2
- Hidden states in TermEncoder accessed before initialized HOT 2
- discussion feature from github for CoqGym HOT 1
- Parsing error HOT 4
- Embeddings for tactics HOT 3
- CoqExn Error when starting next proof HOT 2
- line 6: unrecognized keyword ignored: db_pagesize HOT 1
- A little question about CoqGym HOT 3
- A bug in the dataset of CoqGym HOT 5
- Usage of pre-trained model HOT 1
- ASTactic/extract_proof_steps.py process killed after 17% HOT 5
- ASTactic/extract_proof_steps.py not working with --filter flag HOT 6
- Version of pytorch missing from `coq_gym.yml` HOT 1
- Documentation for how to reproduce benchmark HOT 1
- Testing fails with EOF on test folder HOT 5
- License Compatibility Review Suggested for Dataset
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