You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I installed the libary using pypi (pip install pip install mf-prior-bench) and I am working with the PD1 model lm1b_transformer_2048.
When executing the follwoing basic example
importmfpbenchbenchmark=mfpbench.get("lm1b_transformer_2048") # example pd1 benchmark# This example is based on https://github.com/automl/mf-prior-bench/blob/main/docs/quickstart.mdprint(benchmark.name)# There is a list of attributes accessible from the benchmark object config=benchmark.sample(n=1, seed=0)[0]
print(config)
result=benchmark.query(config)
print(result)
the following warnings are raised
ARNING: ../src/learner.cc:888: Found JSON model saved before XGBoost 1.6, please save the model using current version again. The support for old JSON model will be discontinued in XGBoost 2.3.
[10:38:01] WARNING: ../src/learner.cc:888: Found JSON model saved before XGBoost 1.6, please save the model using current version again. The support for old JSON model will be discontinued in XGBoost 2.3.
/home/lukas/anaconda3/envs/automatic_stopping/lib/python3.9/site-packages/xgboost/data.py:312: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.
if is_sparse(dtype):
/home/lukas/anaconda3/envs/automatic_stopping/lib/python3.9/site-packages/xgboost/data.py:314: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
elif is_categorical_dtype(dtype) and enable_categorical:
/home/lukas/anaconda3/envs/automatic_stopping/lib/python3.9/site-packages/xgboost/data.py:345: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
if is_categorical_dtype(dtype)
/home/lukas/anaconda3/envs/automatic_stopping/lib/python3.9/site-packages/xgboost/data.py:336: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
return is_int or is_bool or is_float or is_categorical_dtype(dtype)
/home/lukas/anaconda3/envs/automatic_stopping/lib/python3.9/site-packages/xgboost/data.py:312: FutureWarning: is_sparse is deprecated and will be removed in a future version. Check `isinstance(dtype, pd.SparseDtype)` instead.
if is_sparse(dtype):
/home/lukas/anaconda3/envs/automatic_stopping/lib/python3.9/site-packages/xgboost/data.py:314: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
elif is_categorical_dtype(dtype) and enable_categorical:
/home/lukas/anaconda3/envs/automatic_stopping/lib/python3.9/site-packages/xgboost/data.py:345: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
if is_categorical_dtype(dtype)
/home/lukas/anaconda3/envs/automatic_stopping/lib/python3.9/site-packages/xgboost/data.py:336: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
return is_int or is_bool or is_float or is_categorical_dtype(dtype)
The text was updated successfully, but these errors were encountered:
Sorry, I somehow completely missed this notification. Thanks for the heads up.
This should be doable by loading and saving the current surrogate models so I can try doing that soon.
I installed the libary using pypi (pip install pip install mf-prior-bench) and I am working with the PD1 model lm1b_transformer_2048.
When executing the follwoing basic example
the following warnings are raised
The text was updated successfully, but these errors were encountered: