| from typing import List | |
| import numpy as np | |
| try: | |
| import tinyBenchmarks as tb | |
| except ModuleNotFoundError: | |
| raise ModuleNotFoundError( | |
| "`tinyBenchmarks` is required for tinyBenchmarks task metric calculation, install via \ | |
| `pip install git+https://github.com/felipemaiapolo/tinyBenchmarks`" | |
| ) | |
| def agg_pirt(items: List[float], benchmark: str) -> float: | |
| items = np.array(items) | |
| predictions = tb.evaluate(items, benchmark) | |
| return predictions[benchmark]["pirt"] | |
| def agg_gpirt_arc(items: List[float], benchmark: str = "arc") -> float: | |
| items = np.array(items) | |
| predictions = tb.evaluate(items, benchmark) | |
| return predictions[benchmark]["gpirt"] | |
| def agg_gpirt_gsm8k(items: List[float], benchmark: str = "gsm8k") -> float: | |
| items = np.array(items) | |
| predictions = tb.evaluate(items, benchmark) | |
| return predictions[benchmark]["gpirt"] | |
| def agg_gpirt_hellaswag(items: List[float], benchmark: str = "hellaswag") -> float: | |
| items = np.array(items) | |
| predictions = tb.evaluate(items, benchmark) | |
| return predictions[benchmark]["gpirt"] | |
| def agg_gpirt_mmlu(items: List[float], benchmark: str = "mmlu") -> float: | |
| items = np.array(items) | |
| predictions = tb.evaluate(items, benchmark) | |
| return predictions[benchmark]["gpirt"] | |
| def agg_gpirt_truthfulqa(items: List[float], benchmark: str = "truthfulqa") -> float: | |
| items = np.array(items) | |
| predictions = tb.evaluate(items, benchmark) | |
| return predictions[benchmark]["gpirt"] | |
| def agg_gpirt_winogrande(items: List[float], benchmark: str = "winogrande") -> float: | |
| items = np.array(items) | |
| predictions = tb.evaluate(items, benchmark) | |
| return predictions[benchmark]["gpirt"] | |