Integrate reward functions into grpo main

apps/grpo/main.py

@@ -12,8 +12,10 @@
 import torch
 from datasets import load_dataset
 from forge.actors.policy import Policy, PolicyConfig, SamplingOverrides, WorkerConfig
+from forge.actors.replay_buffer import ReplayBuffer
 from forge.controller import ServiceConfig, spawn_service
 from forge.controller.actor import ForgeActor
+from forge.data.rewards import MathReward, ThinkingReward
 from monarch.actor import endpoint
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
@@ -260,15 +262,15 @@ def thinking_scoring_function(prompt: str, response: str, target: str) -> float:
 class RewardActor(ForgeActor):
     """Reward actor that uses a list of scoring functions."""
 
-    def __init__(self, scoring_functions: list[Callable]):
+    def __init__(self, reward_functions: list[Callable]):
         super().__init__()
-        self.scoring_functions = scoring_functions
+        self.reward_functions = reward_functions
 
     @endpoint
     async def evaluate_response(self, prompt: str, response: str, target: str) -> float:
         total_reward = 0.0
-        for scoring_fn in self.scoring_functions:
-            reward = scoring_fn(prompt, response, target)
+        for reward_fn in self.reward_functions:
+            reward = reward_fn(prompt, response, target)
             total_reward += reward
         return total_reward
 
@@ -447,7 +449,7 @@ async def main():
     reward_actor = await spawn_service(
         default_service_cfg,
         RewardActor,
-        scoring_functions=[math_scoring_function, thinking_scoring_function],
+        reward_functions=[MathReward(), ThinkingReward()],
     )
 
     print("All services initialized successfully!")