| --- |
| license: apache-2.0 |
| pretty_name: HumanEvalPack |
| language: |
| - code |
| --- |
| # Dataset Card for CommitPackFT |
|
|
| ## Table of Contents |
| - [Table of Contents](#table-of-contents) |
| - [Dataset Description](#dataset-description) |
| - [Dataset Summary](#dataset-summary) |
| - [Languages](#languages) |
| - [Dataset Structure](#dataset-structure) |
| - [Data Instances](#data-instances) |
| - [Data Fields](#data-fields) |
| - [Data Splits](#data-splits) |
| - [Dataset Creation](#dataset-creation) |
| - [Curation Rationale](#curation-rationale) |
| - [Source Data](#source-data) |
| - [Annotations](#annotations) |
| - [Additional Information](#additional-information) |
| - [Licensing Information](#licensing-information) |
| - [Citation Information](#citation-information) |
| - [Contributions](#contributions) |
|
|
| ## Dataset Description |
|
|
| - **Repository:** https://github.com/bigcode-project/octopack |
| - **Paper:** WIP |
| - **Point of Contact:** [Niklas Muennighoff](mailto:n.muennighoff@gmail.com) |
|
|
| ### Dataset Summary |
|
|
| > HumanEvalPack is ... |
| > |
| - **Languages:** 6 |
| - **OctoPack:** |
| - |
|
|
| ## Dataset Structure |
|
|
|
|
| ### Data Instances |
|
|
|
|
| An example looks as follows: |
|
|
| ```json |
| { |
| "task_id": "Python/0", |
| "prompt": "from typing import List\n\n\ndef has_close_elements(numbers: List[float], threshold: float) -> bool:\n \"\"\" Check if in given list of numbers, are any two numbers closer to each other than\n given threshold.\n >>> has_close_elements([1.0, 2.0, 3.0], 0.5)\n False\n >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\n True\n \"\"\"\n", |
| "canonical_solution": " for idx, elem in enumerate(numbers):\n for idx2, elem2 in enumerate(numbers):\n if idx != idx2:\n distance = abs(elem - elem2)\n if distance < threshold:\n return True\n\n return False\n", |
| "test": "\n\n\n\n\ndef check(has_close_elements):\n assert has_close_elements([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.3) == True\n assert has_close_elements([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.05) == False\n assert has_close_elements([1.0, 2.0, 5.9, 4.0, 5.0], 0.95) == True\n assert has_close_elements([1.0, 2.0, 5.9, 4.0, 5.0], 0.8) == False\n assert has_close_elements([1.0, 2.0, 3.0, 4.0, 5.0, 2.0], 0.1) == True\n assert has_close_elements([1.1, 2.2, 3.1, 4.1, 5.1], 1.0) == True\n assert has_close_elements([1.1, 2.2, 3.1, 4.1, 5.1], 0.5) == False\n\ncheck(has_close_elements)", |
| "text": " Check if in given list of numbers, are any two numbers closer to each other than\n given threshold.\n >>> has_close_elements([1.0, 2.0, 3.0], 0.5)\n False\n >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\n True", |
| "declaration": "from typing import List\n\n\ndef has_close_elements(numbers: List[float], threshold: float) -> bool:\n", |
| "example_test": "def check(has_close_elements):\n assert has_close_elements([1.0, 2.0, 3.0], 0.5) == False\n assert has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3) == True\ncheck(has_close_elements)\n", |
| "buggy_solution": " for idx, elem in enumerate(numbers):\n for idx2, elem2 in enumerate(numbers):\n if idx != idx2:\n distance = elem - elem2\n if distance < threshold:\n return True\n\n return False\n", |
| "bug_type": "missing logic", |
| "failure_symptoms": "incorrect output", |
| "entry_point": "has_close_elements", |
| "signature": "has_close_elements(numbers: List[float], threshold: float) -> bool", |
| "docstring": "Check if in given list of numbers, are any two numbers closer to each other than\ngiven threshold.\n>>> has_close_elements([1.0, 2.0, 3.0], 0.5)\nFalse\n>>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\nTrue", |
| "instruction": "Write a Python function `has_close_elements(numbers: List[float], threshold: float) -> bool` to solve the following problem:\nCheck if in given list of numbers, are any two numbers closer to each other than\ngiven threshold.\n>>> has_close_elements([1.0, 2.0, 3.0], 0.5)\nFalse\n>>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\nTrue" |
| } |
| ``` |
|
|
| ### Data Fields |
|
|
| The data fields are the same among all splits: |
| - `task_id`: task id (from 0 to 163) |
| - `prompt`: the prompt for models relying on code continuation |
| - `canonical_solution`: the correct solution passing all unit tests for the problem |
| - `test`: the unit tests for the problem |
| - `text`: ??? |
| - `declaration`: the declaration of the function (same as prompt but without the docstring) |
| - `example_test`: ??? Same as test but fewer tests |
| - `buggy_solution`: same as `canonical_solution` but with a subtle human-written bug causing the unit tests to fail |
| - `bug_type`: the type of the bug in `buggy_solution` (one of [`missing logic`, `excess logic`, `value misuse`, `operator misuse`, `variable misuse`, `function misuse`]) |
| - `failure_symptoms`: the problem the bug causes (one of [`incorrect output`, `stackoverflow`, `infinite loop`]) |
| - `entry_point`: the name of the function |
| - `signature`: the signature of the function |
| - `docstring`: the docstring describing the problem |
| - `instruction`: an instruction for HumanEvalSynthesize in the form `Write a {language_name} function {signature} to solve the following problem:\n{docstring}` |
|
|
| ### Data Splits |
|
|
| ## Additional Information |
|
|
| ### Licensing Information |
|
|
| Each sample has comes from a code repository with a permissive license. The license is provided by the `license` field for each sample. |
|
|
| ### Citation Information |
|
|
| ```bibtex |
| ``` |
