diff --git a/neurons/validator.py b/neurons/validator.py index 1e5a0dace..174a17dbe 100644 --- a/neurons/validator.py +++ b/neurons/validator.py @@ -64,13 +64,13 @@ async def spawn_loops(task_queue, scoring_queue, reward_events): logger.info("Starting WeightSetter...") asyncio.create_task(weight_setter.start(reward_events)) - # while True: - # await asyncio.sleep(5) + while True: + await asyncio.sleep(5) - # # Check if all tasks are still running - # logger.debug(f"Number of tasks in Task Queue: {len(task_queue)}") - # logger.debug(f"Number of tasks in Scoring Queue: {len(scoring_queue)}") - # logger.debug(f"Number of tasks in Reward Events: {len(reward_events)}") + # Check if all tasks are still running + logger.debug(f"Number of tasks in Task Queue: {len(task_queue)}") + logger.debug(f"Number of tasks in Scoring Queue: {len(scoring_queue)}") + logger.debug(f"Number of tasks in Reward Events: {len(reward_events)}") asyncio.run(spawn_loops(task_queue, scoring_queue, reward_events)) diff --git a/prompting/llms/hf_llm.py b/prompting/llms/hf_llm.py index 7671a2e6c..3cac61e41 100644 --- a/prompting/llms/hf_llm.py +++ b/prompting/llms/hf_llm.py @@ -2,7 +2,6 @@ import numpy as np import torch -from loguru import logger from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedModel, pipeline from shared.settings import shared_settings @@ -62,14 +61,14 @@ def generate(self, messages: list[str] | list[dict], sampling_params=None, seed= skip_special_tokens=True, )[0] - logger.debug( - f"""{self.__class__.__name__} queried: - prompt: {messages}\n - responses: {results}\n - sampling params: {params}\n - seed: {seed} - """ - ) + # logger.debug( + # f"""{self.__class__.__name__} queried: + # prompt: {messages}\n + # responses: {results}\n + # sampling params: {params}\n + # seed: {seed} + # """ + # ) return results if len(results) > 1 else results[0] diff --git a/shared/epistula.py b/shared/epistula.py index 2ed2d6e07..4c95f76f3 100644 --- a/shared/epistula.py +++ b/shared/epistula.py @@ -152,8 +152,8 @@ async def query_miners( logger.error(f"Unknown response type: {response}") results.append(SynapseStreamResult(uid=uid, exception=f"Unknown response type: {response}")) return results - except Exception as e: - logger.error(f"Error in query_miners: {e}") + except Exception: + # logger.error(f"Error in query_miners: {e}") return []