{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"bigcodebench","formal_name":"BigCodeBench","introduction":"BigCodeBench poses 1,140 function-level tasks drawn across 139 libraries. It tests whether a model can compose several real APIs correctly rather than write one self-contained function.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://bigcode-bench.github.io/","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"81634f87-f7fa-52a3-ad78-183fd7a39307","task_key":"default--v0~2e1~2e0~5fhf--81634f87-f7fa-52a3-ad78-183fd7a39307","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 81634f87-f7fa-52a3-ad78-183fd7a39307","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import numpy as np\\nfrom scipy.stats import mode\\ndef task_func(list_of_lists):\\n\",\"complete_prompt\":\"import numpy as np\\nfrom scipy.stats import mode\\n\\ndef task_func(list_of_lists):\\n    \\\"\\\"\\\"\\n    Merges a predefined set of lists into a list and finds the mode of the elements in the list.\\n\\n    Parameters:\\n    - list_of_lists (list): The list to be processed.\\n\\n    Returns:\\n    - tuple: The mode and count of the mode in the merged list.\\n        - mode_value (np.array): The value that appears most frequently in the merged array.\\n        - mode_count (int): The frequency count of the mode_value within the merged array.\\n\\n    Requirements:\\n    - numpy\\n    - scipy\\n    \\n    Example:\\n    >>> task_func([[1, 1, 3], [4, 5, 6], [7, 8, 9]])\\n    (array([1]), array([2]))\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Merges a predefined set of lists into a list and finds the mode of the elements in the list.\\nThe function should output with:\\n    tuple: The mode and count of the mode in the merged list.\\n    mode_value (np.array): The value that appears most frequently in the merged array.\\n    mode_count (int): The frequency count of the mode_value within the merged array.\\nYou should write self-contained code starting with:\\n```\\nimport numpy as np\\nfrom scipy.stats import mode\\ndef task_func(list_of_lists):\\n```\",\"libs\":\"['numpy', 'scipy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}