Azure / Azure/MachineLearningNotebooks

AzureML Compute Job failed to start

Abierto
#1,389 4 comentarios 0 reacciones 0 asignados Ver en GitHub
ADO Compute product-issue
Lenguaje dominante
Jupyter Notebook
Estrellas
4.4k
Forks
2.6k
Métricas de merge de PR
Sin PR fusionados en 30 d

Descripción

Unable to use dockerfile to create an Environment in the `explain-model-on-amlcompute.ipynb` notebook.

The following is the code

```
from azureml.core import Workspace, Environment
myenv = Environment(name="rapidsenv")

myenv.register(workspace=ws)
myenv.docker.enabled=True

dockerfile = r"""
FROM rapidsai/rapidsai-cloud-ml:0.17-cuda11.0-base-ubuntu18.04-py3.8
RUN echo "success" # I'd like to install different packages here
"""
myenv.docker.base_image = None
myenv.docker.base_dockerfile = dockerfile
myenv.python.user_managed_dependencies=True

from azureml.core import Run
from azureml.core import ScriptRunConfig

src = ScriptRunConfig(source_directory=project_folder,
script='train_explain.py',
compute_target=gpu_cluster,
environment=myenv)
run = experiment.submit(config=src)
run
```

This is what shows up on the Portal.

```
AzureMLCompute job failed.
JobContainerConfigFailed: Container configuration failed unexpectedly
JobContainerConfigFailed: Container configuration failed unexpectedly
err: Docker exec failure when attempting to execute 'containerSetup' task. Error: exit status 126. Indicates a command was found but not executable, likely due to permission issues or missing dependencies.
Reason: Docker exec failure when attempting to execute 'containerSetup' task. Error: exit status 126. Indicates a command was found but not executable, likely due to permission issues or missing dependencies.
Info: Failed to prepare an environment for the job execution: Job environment preparation failed on 10.0.0.4 with err exit status 1.
```

How do I resolve this issue?

Guía de contribución

No hay ninguna guía de contribución indexada para este repositorio

Línea de trabajo

Comienza con explain-model-on-amlcompute.ipynb y ejecuta el ejemplo proporcionado de Environment y ScriptRunConfig contra el GPU compute target. Usa los mensajes JobContainerConfigFailed y containerSetup exit-status-126 del Portal para seguir la preparación del entorno; se considera terminado cuando el trabajo del notebook se inicia correctamente con el entorno basado en Dockerfile.

Escrito por el modelo de indexación a partir del texto del issue.

Evaluación

Stack tecnológico
azure, docker, jupyter-notebook, python
Área
cloud, devops, machine-learning
Tipo de issue
Error
Dificultad
4/5
Tiempo estimado
3-5 días
Estado de actividad
Estancado
Claridad
Bastante claro
Aptitud para principiantes
35/100

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.