linkedin / linkedin/FastTreeSHAP
Cannot build fasttreeshap in linux environment
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- Lenguaje dominante
- Python
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Descripción
We would like to use fasttreeshap to calculate explainability values for our machine learning model.
To run our model we create a linux container with a venv for the model. All the requirements are specified in a file and installed in the venv with pip -r requirements.txt.
Our model depends on numpy==1.21.4 and when we try to install fasttreeshap we incur into this issue:
```
ERROR: Cannot install oldest-supported-numpy==0.12, oldest-supported-numpy==0.14, oldest-supported-numpy==0.15, oldest-supported-numpy==2022.1.30, oldest-supported-numpy==2022.3.27, oldest-supported-numpy==2022.4.10, oldest-supported-numpy==2022.4.18, oldest-supported-numpy==2022.4.8, oldest-supported-numpy==2022.5.27, oldest-supported-numpy==2022.5.28 and oldest-supported-numpy==2022.8.16 because these package versions have conflicting dependencies.
The conflict is caused by:
oldest-supported-numpy 2022.8.16 depends on numpy==1.17.3; python_version == "3.8" and platform_machine not in "arm64|aarch64|s390x|loongarch64" and platform_python_implementation != "PyPy"
oldest-supported-numpy 2022.5.28 depends on numpy==1.17.3; python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64" and platform_machine != "s390x" and platform_machine != "loongarch64" and platform_python_implementation != "PyPy"
oldest-supported-numpy 2022.5.27 depends on numpy==1.17.3; python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64" and platform_machine != "s390x" and platform_machine != "loongarch64" and platform_python_implementation != "PyPy"
oldest-supported-numpy 2022.4.18 depends on numpy==1.17.3; python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64" and platform_machine != "s390x" and platform_machine != "loongarch64" and platform_python_implementation != "PyPy"
oldest-supported-numpy 2022.4.10 depends on numpy==1.17.3; python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64" and platform_machine != "s390x" and platform_machine != "loongarch64" and platform_python_implementation != "PyPy"
oldest-supported-numpy 2022.4.8 depends on numpy==1.17.3; python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64" and platform_machine != "s390x" and platform_machine != "loongarch64" and platform_python_implementation != "PyPy"
oldest-supported-numpy 2022.3.27 depends on numpy==1.17.3; python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64" and platform_machine != "s390x" and platform_machine != "loongarch64" and platform_python_implementation != "PyPy"
oldest-supported-numpy 2022.1.30 depends on numpy==1.17.3; python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64" and platform_machine != "s390x" and platform_python_implementation != "PyPy"
oldest-supported-numpy 0.15 depends on numpy==1.17.3; python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64" and platform_machine != "s390x" and platform_python_implementation != "PyPy"
oldest-supported-numpy 0.14 depends on numpy==1.17.3; python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64" and platform_machine != "s390x" and platform_python_implementation != "PyPy"
oldest-supported-numpy 0.12 depends on numpy==1.17.3; python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64" and platform_python_implementation != "PyPy"
```
I can volunteer time and resources to add a wheel file for linux. Would you be interested in distributing a wheel file created by us ?
Guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
Línea de trabajo
Comienza reproduciendo la instalación en un contenedor Linux descrita en el issue, utilizando la versión fijada numpy==1.21.4 y requirements.txt. Investiga el conflicto de dependencias y determina si se puede compilar y distribuir un wheel de Linux para este entorno; el trabajo estará terminado cuando pip pueda instalar fasttreeshap sin el fallo de resolución informado.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- numpy, python
- Área
- build-system, machine-learning
- Tipo de issue
- Nueva funcionalidad
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Estado de actividad
- Estancado
- Claridad
- Bastante claro
- Aptitud para principiantes
- 35/100