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[pre-commit.ci] auto fixes from pre-commit.com hooks

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pre-commit-ci[bot] 2026-02-06 06:46:14 +00:00 • committed by Jai Suphavadeeprasit
parent d07ab3e3ce
commit 5cfd1929f1
19 changed files with 708 additions and 452 deletions
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4
environments/eval_environments/gsm8k_eval.py
View file

@ -373,7 +373,9 @@ class GSM8KEvalEnv(BaseEnv):
# Create evaluation tasks
async def eval_task(item):
return await self.rollout_and_score_eval(item, self.server.servers[0].config)
return await self.rollout_and_score_eval(
item, self.server.servers[0].config
)
tasks = [eval_task(item) for item in self.eval_items]

15
environments/math_server_zero.py
View file

@ -146,7 +146,7 @@ class MathEnv(BaseEnv):
vllm_url = os.environ.get("MATH_ENV_VLLM_URL", "http://localhost:9001/v1")
wandb_name = os.environ.get("MATH_ENV_WANDB_NAME", "math-zero-env")
max_token_length = int(os.environ.get("MATH_ENV_MAX_TOKENS", "8192"))
env_config = RSConfig(
tokenizer_name=model_name,
group_size=8,
@ -299,6 +299,7 @@ class MathEnv(BaseEnv):
if not self.config.run_evaluation:
return
import time
start_time = time.time()
eval_tasks = []
@ -320,9 +321,7 @@ class MathEnv(BaseEnv):
metrics[f"{subset}_accuracy"] = accuracy
metrics[f"{subset}_total"] = len(scores)
metrics[f"{subset}_correct"] = sum(scores)
self.eval_metrics.append(
(f"eval/{subset}_percent_correct", accuracy)
)
self.eval_metrics.append((f"eval/{subset}_percent_correct", accuracy))
# overall score
all_scores = []
@ -332,9 +331,7 @@ class MathEnv(BaseEnv):
metrics["overall_accuracy"] = overall_accuracy
metrics["overall_total"] = len(all_scores)
metrics["overall_correct"] = sum(all_scores)
self.eval_metrics.append(
("eval/overall_percent_correct", overall_accuracy)
)
self.eval_metrics.append(("eval/overall_percent_correct", overall_accuracy))
end_time = time.time()
@ -342,7 +339,9 @@ class MathEnv(BaseEnv):
print("\n" + "=" * 60)
print("Math Zero Evaluation Results")
print("=" * 60)
print(f"Overall Accuracy: {overall_accuracy:.2%} ({sum(all_scores)}/{len(all_scores)})")
print(
f"Overall Accuracy: {overall_accuracy:.2%} ({sum(all_scores)}/{len(all_scores)})"
)
print("\nPer-subset breakdown:")
for subset, scores in sorted(task_lists.items()):
acc = sum(scores) / len(scores)