def record_eval_results(eval_results, metrics_logger):
"""
Create a callback function that records evaluation results.
"""
return picklable_exception_safe_function(
functools.partial(_autolog_callback,
metrics_logger=metrics_logger,
eval_results=eval_results))
def record_eval_results(eval_results, metrics_logger):
"""
Create a callback function that records evaluation results.
"""
# TODO: Remove `replace("SNAPSHOT", "dev")` once the following issue is addressed:
# https://github.com/dmlc/xgboost/issues/6984
from mlflow.xgboost._autolog import IS_TRAINING_CALLBACK_SUPPORTED
if IS_TRAINING_CALLBACK_SUPPORTED:
from mlflow.xgboost._autolog import AutologCallback
# In xgboost >= 1.3.0, user-defined callbacks should inherit
# `xgboost.callback.TrainingCallback`:
# https://xgboost.readthedocs.io/en/latest/python/callbacks.html#defining-your-own-callback
return AutologCallback(metrics_logger, eval_results)
else:
from mlflow.xgboost._autolog import autolog_callback
return picklable_exception_safe_function(
functools.partial(autolog_callback,
metrics_logger=metrics_logger,
eval_results=eval_results))
def test_callback_func_is_pickable():
cb = picklable_exception_safe_function(
functools.partial(autolog_callback,
BatchMetricsLogger(run_id="1234"),
eval_results={}))
pickle.dumps(cb)
