gavindiaz/NexQuant
1
0
Fork 0
mirror of https://github.com/NicolasBohn/NexQuant.git synced 2026-08-09 21:10:56 +00:00
Code Issues Packages Projects Releases Wiki Activity

feat: use unified pickle cacher & move llm config into a isolated config (#424)

Browse Source 
* simplify RDAgent conf

* add unified cacher(untested)

* fix small bugs

* fix a bug

* fix a small bug in runner

* use hash_key = None to skip cache

* fix CI

* in factor execution, ignore cache when raise exception

* add file locker to avoid mp calling

* fix CI

* use function __module__ name as folder in cache
This commit is contained in:
Xu Yang
2024-10-14 17:34:09 +08:00
committed by GitHub
parent 8341430bc9
commit 25472fc1e3
25 changed files with 299 additions and 346 deletions
Download Patch File Download Diff File Expand all files Collapse all files
rdagent/components/coder/model_coder/CoSTEER/evaluators.py
+13 -8
View File
@@ -19,6 +19,7 @@ from rdagent.core.experiment import Task, Workspace
from rdagent.core.prompts import Prompts
from rdagent.core.utils import multiprocessing_wrapper
from rdagent.log import rdagent_logger as logger
from rdagent.oai.llm_conf import LLM_SETTINGS
from rdagent.oai.llm_utils import APIBackend
evaluate_prompts = Prompts(file_path=Path(__file__).parent.parent / "prompts.yaml")
@@ -90,9 +91,11 @@ class ModelCodeEvaluator(Evaluator):
Environment(undefined=StrictUndefined)
.from_string(evaluate_prompts["evaluator_code_feedback"]["system"])
.render(
scenario=self.scen.get_scenario_all_desc(target_task)
if self.scen is not None
else "No scenario description."
scenario=(
self.scen.get_scenario_all_desc(target_task)
if self.scen is not None
else "No scenario description."
)
)
)
@@ -116,7 +119,7 @@ class ModelCodeEvaluator(Evaluator):
user_prompt=user_prompt,
system_prompt=system_prompt,
)
> RD_AGENT_SETTINGS.chat_token_limit
> LLM_SETTINGS.chat_token_limit
):
execution_feedback_to_render = execution_feedback_to_render[len(execution_feedback_to_render) // 2 :]
else:
@@ -150,9 +153,11 @@ class ModelFinalEvaluator(Evaluator):
Environment(undefined=StrictUndefined)
.from_string(evaluate_prompts["evaluator_final_feedback"]["system"])
.render(
scenario=self.scen.get_scenario_all_desc(target_task)
if self.scen is not None
else "No scenario description."
scenario=(
self.scen.get_scenario_all_desc(target_task)
if self.scen is not None
else "No scenario description."
)
)
)
@@ -176,7 +181,7 @@ class ModelFinalEvaluator(Evaluator):
user_prompt=user_prompt,
system_prompt=system_prompt,
)
> RD_AGENT_SETTINGS.chat_token_limit
> LLM_SETTINGS.chat_token_limit
):
execution_feedback_to_render = execution_feedback_to_render[len(execution_feedback_to_render) // 2 :]
else:
rdagent/components/coder/model_coder/CoSTEER/evolving_strategy.py
+2 -1
View File
@@ -20,6 +20,7 @@ from rdagent.core.conf import RD_AGENT_SETTINGS
from rdagent.core.evolving_framework import EvolvingStrategy
from rdagent.core.prompts import Prompts
from rdagent.core.utils import multiprocessing_wrapper
from rdagent.oai.llm_conf import LLM_SETTINGS
from rdagent.oai.llm_utils import APIBackend
from rdagent.scenarios.kaggle.experiment.kaggle_experiment import KG_MODEL_MAPPING
@@ -100,7 +101,7 @@ class ModelCoderEvolvingStrategy(EvolvingStrategy):
user_prompt=user_prompt,
system_prompt=system_prompt,
)
< RD_AGENT_SETTINGS.chat_token_limit
< LLM_SETTINGS.chat_token_limit
):
break
elif len(queried_former_failed_knowledge_to_render) > 1: