refactor: refactor base_evaluator

Author: ChenZiHong-Gavin

graphgen/bases/base_evaluator.py

@@ -1,52 +1,10 @@
-import asyncio
-
-from tqdm.asyncio import tqdm as tqdm_async
-
+from abc import ABC, abstractmethod
 from graphgen.bases.datatypes import QAPair
-from graphgen.utils import create_event_loop
 
 
-class BaseEvaluator:
-    def __init__(self, max_concurrent: int = 100):
-        self.max_concurrent = max_concurrent
-        self.results: list[float] = None
-
-    def evaluate(self, pairs: list[QAPair]) -> list[float]:
+class BaseEvaluator(ABC):
+    @abstractmethod
+    def evaluate(self, pair: QAPair) -> float:
         """
         Evaluate the text and return a score.
         """
-        return create_event_loop().run_until_complete(self.async_evaluate(pairs))
-
-    async def async_evaluate(self, pairs: list[QAPair]) -> list[float]:
-        semaphore = asyncio.Semaphore(self.max_concurrent)
-
-        async def evaluate_with_semaphore(pair):
-            async with semaphore:  # 获取Semaphore
-                return await self.evaluate_single(pair)
-
-        results = []
-        for result in tqdm_async(
-            asyncio.as_completed([evaluate_with_semaphore(pair) for pair in pairs]),
-            total=len(pairs),
-        ):
-            results.append(await result)
-        return results
-
-    async def evaluate_single(self, pair: QAPair) -> float:
-        raise NotImplementedError()
-
-    def get_average_score(self, pairs: list[QAPair]) -> float:
-        """
-        Get the average score of a batch of texts.
-        """
-        results = self.evaluate(pairs)
-        self.results = results
-        return sum(self.results) / len(pairs)
-
-    def get_min_max_score(self, pairs: list[QAPair]) -> tuple[float, float]:
-        """
-        Get the min and max score of a batch of texts.
-        """
-        if self.results is None:
-            self.get_average_score(pairs)
-        return min(self.results), max(self.results)