ValueError: sklearn.tree._splitter.Splitter size changed, may indicate binary incompatibility.

[ramm777]

Describe the bug

The new version (scikit-survival==0.19) gives an a ValueError:

ValueError: sklearn.tree._splitter.Splitter size changed, may indicate binary incompatibility. Expected 1160 from C header, got 360 from PyObject

If I downgrade version to 0.18 it's fine.

Code Sample to Reproduce the Bug

!pip install scikit-survival==0.19
from sksurv.ensemble import RandomSurvivalForest

Expected Results
Expect to the module to be loaded

Actual Results
ValueError: sklearn.tree._splitter.Splitter size changed, may indicate binary incompatibility. Expected 1160 from C header, got 360 from PyObject

Versions
Please execute the following snippet and paste the output below.

System:
python: 3.8.13 | packaged by conda-forge | (default, Mar 25 2022, 06:04:18) [GCC 10.3.0]
executable: /opt/conda/envs/py38/bin/python
machine: Linux-4.14.225-169.362.amzn2.x86_64-x86_64-with-glibc2.10

Python dependencies:
sklearn: 1.1.1
pip: 22.2.1
setuptools: 57.5.0
numpy: 1.19.5
scipy: 1.5.2
Cython: None
pandas: 1.3.4
matplotlib: 3.4.1
joblib: 1.0.1
threadpoolctl: 3.1.0

Built with OpenMP: True

threadpoolctl info:
user_api: openmp
internal_api: openmp
prefix: libgomp
filepath: /opt/conda/envs/py38/lib/python3.8/site-packages/scikit_learn.libs/libgomp-a34b3233.so.1.0.0
version: None
num_threads: 8

   user_api: blas

internal_api: openblas
prefix: libopenblas
filepath: /opt/conda/envs/py38/lib/python3.8/site-packages/numpy.libs/libopenblasp-r0-09e95953.3.13.so
version: 0.3.13
threading_layer: pthreads
architecture: SkylakeX
num_threads: 8

   user_api: blas

internal_api: openblas
prefix: libopenblas
filepath: /opt/conda/envs/py38/lib/python3.8/site-packages/scipy.libs/libopenblasp-r0-085ca80a.3.9.so
version: 0.3.9
threading_layer: pthreads
architecture: Haswell
num_threads: 8
sksurv: 0.19.0
cvxopt: 1.3.0
cvxpy: 1.2.1
numexpr: 2.7.3
osqp: 0.6.2

[sebp]

sksurv was built against sklearn 1.1.2, but this version is not binary compatible with version 1.1.1, which you have installed. I should probably adjust the requirements to explicitly require sklearn =1.1.2

[ramm777]

Thanks a lot!