Comments (6)
Can you give me more details about your system info?
You can get them by running:
import platform
print("Platform Version: {0}, {1}".format(platform.platform(), platform.architecture()[0]))
print("Python Version:", platform.python_version())
import abess
print("Package Version:", abess.__version__)
from abess.
Platform Version: macOS-10.16-x86_64-i386-64bit, 64bit
Python Version: 3.9.7
Package Version: 0.3.6
from abess.
Thanks.
It is a tough issue. We have to pay some time to fix it. If you are urgent to use abess
on Mac with M1 chip, you can refer to: tensorflow/tensorflow#45404, tensorflow/tensorflow#46044, or https://www.tensorflow.org/install/source#bazel_build_options, https://stackoverflow.com/questions/65770132/python3-install-of-tensorflow-on-apple-silicon-m1. Another option is using it in Windows or Linux.
from abess.
The following is a step-by-step procedure for solving this issue.
-
Download
miniforge
from github: https://github.com/conda-forge/miniforge
-
Install it in terminal by commands:
mv Miniforge3-MacOSX-arm64.sh ~/
Chmod +x Miniforge3-MacOSX-arm64.sh
./Miniforge3-MacOSX-arm64.sh
- Activate and start a new environment named
abess
in terminal via:
conda create --name abess python=3.8
conda activate abess
- Follow the instruction to install the latest version of
abess
Python package.
After executing these steps, I believe the illegal hardware instruction python
would be resolved.
If you meet any questions, feel free to contact us.
from abess.
Hi @JiaqiHu2021 ,we have updated a new version in Pypi. We believe the newest version can successfully executed the following code:
>>> from abess.linear import abessLogistic
>>> from sklearn.datasets import load_breast_cancer
>>> from sklearn.pipeline import Pipeline
>>> from sklearn.metrics import make_scorer, roc_auc_score
>>> from sklearn.preprocessing import PolynomialFeatures
>>> from sklearn.model_selection import GridSearchCV
>>> pipe = Pipeline([('poly', PolynomialFeatures(include_bias=False)), ('alogistic', abessLogistic())])
>>> param_grid = {'poly__interaction_only': [True, False],'poly__degree': [1, 2, 3]}
>>> scorer = make_scorer(roc_auc_score, greater_is_better=True)
>>> grid_search = GridSearchCV(pipe, param_grid, scoring=scorer, cv=5)
>>> X, y = load_breast_cancer(return_X_y=True)
>>> grid_search.fit(X, y)
You can run
pip uninstall abess
pip install --no-cache-dir abess==0.4.2
to reinstall the latest abess
library.
If you still meet any problem, feel free to contact us.
from abess.
After upgrading to the latest version, I successfully ran the above code.
Thank you very much for your help!
from abess.
Related Issues (20)
- Is it possible to combine `group` and `always_select` to always select a whole group? HOT 3
- [Bug] No termination within reasonable time for Poisson regression in a specific case HOT 6
- Incorporation of `fit_intercept` to `LinearRegression`? HOT 9
- Why the data generator funciton `make_glm_data` for gamma will define n shape parameters for a data set HOT 2
- Incorrect optimal support size in a multitask learning problem with nonnegativity constraints HOT 15
- How I can aviod intercept when I do abess in R HOT 1
- Provide any option for inference? HOT 12
- Risk Score Card Develope HOT 3
- How to set test data HOT 1
- [Feature] Release new version of `abess` on PyPI and Conda HOT 2
- Any way to work with preselected sets of variables in abess & with MBIC criterion? HOT 8
- Version 0.4.7 crashing when LinearRegression.fit() invoked HOT 3
- Colname errors HOT 1
- different results on Mac, Linux, Windows HOT 2
- [Feature] add a Wikipedia page about `abess` HOT 1
- Failed to build abess HOT 2
- What do multiple sets of coefficients mean? HOT 2
- Error in x_y_matching.glm(para, data) : Rows of x must be the same as rows of y! HOT 1
- 风险评分优化
- Compilation Fails on AARCH64 / ARM64 Due to x86 Specific Compiler Flags
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