| from typing import Optional | |
| TASKS_PRETTY = { | |
| "library_based_code_generation": "Library-based code generation", | |
| "ci_builds_repair": "CI builds repair", | |
| "project_code_completion": "Project-level code completion", | |
| "commit_message_generation": "Commit message generation", | |
| "bug_localization": "Bug localization", | |
| "module_summarization": "Module Summarization", | |
| } | |
| TASKS_PRETTY_REVERSE = {value: key for key, value in TASKS_PRETTY.items()} | |
| TASKS_DESCRIPTIONS = { | |
| "library_based_code_generation": """# Library-Based Code Generation\n | |
| Our Library-Based Code Generation benchmark 🤗 [JetBrains-Research/lca-library-based-code-generation](https://huggingface.co/datasets/JetBrains-Research/lca-library-based-code-generation) includes 150 manually curated instructions asking model to generate Python code using a particular library. Samples come from 62 Python repositories. All the samples in the dataset are based on reference example programs written by authors of the respective libraries. | |
| For evaluation we use two metrics: | |
| * `API Recall`: share of library-specific API calls used in the reference program that appear in the generated code, | |
| * `ChrF`: textual similarity between the generated code and the reference program. | |
| For further details on the dataset and the baselines from 🏟️ Long Code Arena Team, refer to `library_based_code_generation` folder in [our baselines repository](https://github.com/JetBrains-Research/lca-baselines) or to our preprint (TODO). | |
| """, | |
| "ci_builds_repair": """# CI Builds Repair\n | |
| Our CI Builds Repair benchmark 🤗 [JetBrains-Research/lca-ci-builds-repair](https://huggingface.co/datasets/JetBrains-Research/lca-ci-builds-repair) includes 77 data points. | |
| We use Pass@1 metric for CI repair. | |
| We evaluate Exact Match for different line categories: | |
| For further details on the dataset and the baselines from 🏟️ Long Code Arena Team, refer to `ci-builds-repair` folder in [our baselines repository](https://github.com/JetBrains-Research/lca-baselines) or to our preprint. | |
| """, | |
| "project_code_completion": """# Project-Level Code Completion\n | |
| Our Project-Level Code Completion benchmark 🤗 [JetBrains-Research/lca-project-level-code-completion](https://huggingface.co/datasets/JetBrains-Research/lca-project-level-code-completion) includes four datasets: | |
| * `small-context`: 144 data points, | |
| * `medium-context`: 224 data points, | |
| * `large-context`: 270 data points, | |
| * `huge-context`: 296 data points. | |
| We use standard Exact Match (EM) metric for one-line code completion. | |
| We evaluate Exact Match for different line categories: | |
| * *infile* – functions and classes are from the completion file; | |
| * *inproject* – functions and files are from the repository snapshot; | |
| * *committed* – functions and classes are from the files that were added on the completion file commit; | |
| * *common* – functions and classes with common names, e.g., `main`, `get`, etc.; | |
| * *non-informative* – short/long lines, import/print lines, or comment lines; | |
| * *random* – lines that doesn't fit to any of previous categories. | |
| For further details on the dataset and the baselines from 🏟️ Long Code Arena Team, refer to `code_completion` folder in [our baselines repository](https://github.com/JetBrains-Research/lca-baselines) or to our preprint (TODO). | |
| """, | |
| "commit_message_generation": """# Commit Message Generation\n | |
| Our Commit Message Generation benchmark 🤗 [JetBrains-Research/lca-commit-message-generation](https://huggingface.co/datasets/JetBrains-Research/lca-commit-message-generation) includes 163 manually curated commits from Python projects. | |
| We use the following metrics for evaluation: | |
| * [BLEU](https://huggingface.co/spaces/evaluate-metric/sacrebleu) | |
| * [ROUGE](https://huggingface.co/spaces/evaluate-metric/rouge) | |
| * [ChrF](https://huggingface.co/spaces/evaluate-metric/chrf) | |
| * [BERTScore](https://huggingface.co/spaces/evaluate-metric/bertscore) | |
| For further details on the dataset and the baselines from 🏟️ Long Code Arena Team, refer to `commit_message_generation` folder in [our baselines repository](https://github.com/JetBrains-Research/lca-baselines) or to our preprint (TODO). | |
| **Note.** The leaderboard is sorted by ROUGE-1 metric by default. | |
| """, | |
| "bug_localization": """# Bug Localization\n | |
| Our Module-to-Text benchmark 🤗 [JetBrains-Research/lca-bug-localization](https://huggingface.co/datasets/JetBrains-Research/lca-bug-localization) includes 7,479 bug issue descriptions with information about pull request that fix them for Python, Java and Kotlin projects. | |
| Moreover, 150 data points from the test split were manually verified and can be used for bug localization approaches evaluation. | |
| We used information retrieval metrics such as R@k, P@k and F1-score for evaluation, taking k equal to 1 and 2. | |
| """, | |
| "module_summarization": """# Module Summarization\n | |
| Our Module Summarization benchmark 🤗 [JetBrains-Research/lca-module-summarization](https://huggingface.co/datasets/JetBrains-Research/lca-module-summarization) includes 216 manually curated text files describing different documentation of opensource permissive Python projects. | |
| We use new metric for evaluation: | |
| * `CompScore`: New metric proposed for this task. More details in [our baselines repository](https://github.com/JetBrains-Research/lca-baselines/blob/main/module_summarization/README.md) | |
| For further details on the dataset and the baselines from 🏟️ Long Code Arena Team, refer to `module_summarization` folder in [our baselines repository](https://github.com/JetBrains-Research/lca-baselines/blob/main/module_summarization/). | |
| """, | |
| } | |
| def get_submission_text_files_for_task(task_pretty: Optional[str]) -> str: | |
| if not task_pretty: | |
| return "Please, select a specific task to see more detailed instructions regarding submitting files." | |
| task_id = TASKS_PRETTY_REVERSE[task_pretty] | |
| if task_id == "commit_message_generation": | |
| return f"""**{task_pretty} Instructions:**\n\n* Please, attach files in [JSONLines format](https://jsonlines.org/). For an example, check the predictions provided by 🏟️ Long Code Arena Team in 🤗 [JetBrains-Research/lca-results](https://huggingface.co/datasets/JetBrains-Research/lca-results/tree/main/commit_message_generation/predictions). Make sure to include `"prediction"` and `"reference"` fields for each example, the rest are optional.""" | |
| return f"**{task_pretty} Instructions:**\n\n* 🚧 There are no instructions for the current task yet." | |