copilot-swe-agent[bot]
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
"""
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Benchmark Data Loader Template
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================================
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Copy this file and implement the TODO sections to load your benchmark data.
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The SplitDataLoader is responsible for:
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1. Loading raw data from disk for ratio split mode
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2. Loading items from train/val/test directories for split_dir mode
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3. Returning list[dict] items used by the training loop
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"""
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from __future__ import annotations
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from skillopt.datasets.base import SplitDataLoader
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class TemplateBenchmarkDataLoader(SplitDataLoader):
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"""
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Data loader for <Your Benchmark Name>.
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Rename this class and implement the methods below.
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"""
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def load_raw_items(self, data_path: str) -> list[dict]:
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"""
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Parse raw benchmark data for split_mode="ratio".
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Return a list of normalized item dicts.
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"""
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# TODO: customize when your raw source format differs.
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return super().load_raw_items(data_path)
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def load_split_items(self, split_path: str) -> list[dict]:
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"""
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Parse one split directory for split_mode="split_dir".
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split_path points to train/, val/, or test/.
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"""
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# TODO: customize when each split directory has a custom layout.
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return super().load_split_items(split_path)
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