We lifted 17 functions out of this paper's own repositories and ran 13 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| deep-spin/sigmorphon-seq2seq | pwc_unofficial | 6 of 7 |
| jarl93/joeynmt-modified | pwc_unofficial | 2 of 5 |
| benjaminbeilharz/hierarchical-reinforcement-learning | pwc_unofficial | 2 of 2 |
| deep-spin/S7 | extension | 2 of 2 |
| copy not recorded | — | 1 of 1 |
| Function | Status | Where it lives |
|---|---|---|
| build_general_value_network | Ran | benjaminbeilharz/hierarchical-reinforcement-learning/joeynmt/value_network.py code served (permissive licence) · get_code("fbfce742341c3312") |
| check_vocab_and_split | Ran | this paper's copy was not recorded; identical code first harvested from rsennrich/subword-nmt pointer only · get_code("a0deb98db94ae939") |
| clones | Ran | jarl93/joeynmt-modified/joeynmt/helpers.py code served (permissive licence) · get_code("86b7d1950504d5b1") |
| encode | Ran | deep-spin/S7/scripts/apply_bpe.py code served (permissive licence) · get_code("52d69829a4cee830") |
| ends | Ran | deep-spin/sigmorphon-seq2seq/hallucination/augment.py code served (permissive licence) · get_code("a8c303bcecfe0b48") |
| find_good_range | Ran | deep-spin/sigmorphon-seq2seq/hallucination/augment.py code served (permissive licence) · get_code("294b5b42eb8b85cc") |
| get_pairs | Ran | deep-spin/S7/scripts/apply_bpe.py code served (permissive licence) · get_code("290febe7a42e8479") |
| make_fake_user_answer_labels | Ran | benjaminbeilharz/hierarchical-reinforcement-learning/subtask_pretraining.py code served (permissive licence) · get_code("5664f103cf301cd7") |
| make_logger | Ran | jarl93/joeynmt-modified/joeynmt/helpers.py code served (permissive licence) · get_code("aad8945d314699ad") |
| pad_and_stack_hyps | Ran | deep-spin/sigmorphon-seq2seq/joeynmt/model.py code served (permissive licence) · get_code("a19f205cc566f56c") |
| read_data | Ran | deep-spin/sigmorphon-seq2seq/hallucination/augment.py code served (permissive licence) · get_code("ff0ec87d63da9b32") |
| read_task1_data | Ran | deep-spin/sigmorphon-seq2seq/hallucination/generate_task1_data.py code served (permissive licence) · get_code("77a42ba2975545ab") |
| rules | Ran | deep-spin/sigmorphon-seq2seq/hallucination/generate_task1_data.py code served (permissive licence) · get_code("9e0d921dd261c239") |
| build_scheduler | Not yet run | jarl93/joeynmt-modified/joeynmt/builders.py code served (permissive licence) · get_code("e0cdbcc27a1c011a") |
| build_scheduler | Not yet run | deep-spin/sigmorphon-seq2seq/joeynmt/builders.py code served (permissive licence) · get_code("c7677be26fa62d12") |
| make_model_dir | Not yet run | jarl93/joeynmt-modified/joeynmt/helpers.py code served (permissive licence) · get_code("d2439dd3cffbf595") |
| token_batch_size_fn | Not yet run | jarl93/joeynmt-modified/joeynmt/data.py code served (permissive licence) · get_code("cb329af957271d21") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
We present Joey NMT, a minimalist neural machine translation toolkit based on PyTorch that is specifically designed for novices. Joey NMT provides many popular NMT features in a small and simple code base, so that novices can easily and quickly learn to use it and adapt it to their needs. Despite its focus on simplicity, Joey NMT supports classic architectures (RNNs, transformers), fast beam search, weight tying, and more, and achieves performance comparable to more complex toolkits on standard benchmarks. We evaluate the accessibility of our toolkit in a user study where novices with general knowledge about Pytorch and NMT and experts work through a self-contained Joey NMT tutorial, showing that novices perform almost as well as experts in a subsequent code quiz. Joey NMT is available at https://github.com/joeynmt/joeynmt .
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("1907.12484")
get_code_for_paper("1907.12484")
have("1907.12484")
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