Files
MachineLearningNotebooks/ignore/doc-qa/how-to-set-up-training-targets/dsvm.py
2019-01-04 12:51:11 -06:00

28 lines
1.0 KiB
Python

# Code for Remote virtual machines
compute_target_name = "attach-dsvm"
#<run_dsvm>
import azureml.core
from azureml.core.runconfig import RunConfiguration, DEFAULT_CPU_IMAGE
from azureml.core.conda_dependencies import CondaDependencies
run_dsvm = RunConfiguration(framework = "python")
# Set the compute target to the Linux DSVM
run_dsvm.target = compute_target_name
# Use Docker in the remote VM
run_dsvm.environment.docker.enabled = True
# Use the CPU base image
# To use GPU in DSVM, you must also use the GPU base Docker image "azureml.core.runconfig.DEFAULT_GPU_IMAGE"
run_dsvm.environment.docker.base_image = azureml.core.runconfig.DEFAULT_CPU_IMAGE
print('Base Docker image is:', run_dsvm.environment.docker.base_image)
# Prepare the Docker and conda environment automatically when they're used for the first time
run_dsvm.prepare_environment = True
# Specify the CondaDependencies object
run_dsvm.environment.python.conda_dependencies = CondaDependencies.create(conda_packages=['scikit-learn'])
#</run_dsvm>