| 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"] |
|
|