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# coding: utf-8
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""
FILE: ml_samples_cloud_configurations.py
DESCRIPTION:
These samples demonstrate different ways to configure clouds for the MLClient.
USAGE:
python ml_samples_cloud_configurations.py
"""
import os
from azure.ai.ml import MLClient
from azure.ai.ml.constants._common import ArmConstants
from azure.ai.ml.constants._common import AZUREML_CLOUD_ENV_NAME
from azure.identity import AzureAuthorityHosts, DefaultAzureCredential
class CloudConfigurationOptions(object):
def ml_cloud_config_from_environment_arm(self):
subscription_id = "AZURE_SUBSCRIPTION_ID"
resource_group = "RESOURCE_GROUP_NAME"
credential = DefaultAzureCredential(authority=AzureAuthorityHosts.AZURE_PUBLIC_CLOUD)
# This environment variable should be set when running python. If it is set, and the configured cloud is not
# one of the default ones in _azure_environments.py, it will follow the url to find the cloud config. If it
# does not find it anywhere, it will throw an "Unknown cloud environment" error.
os.environ[ArmConstants.METADATA_URL_ENV_NAME] = (
"https://management.azure.com/metadata/endpoints?api-version=2019-05-01"
)
kwargs = {"cloud": "AzureCloud"}
ml_client = MLClient(
credential=credential,
subscription_id=subscription_id,
resource_group_name=resource_group,
workspace_name="test-ws1",
**kwargs,
)
# The client will use the cloud that we passed in
print("Client is using cloud:", ml_client._cloud)
# In specifying this cloud, we've also set the environment variable to match it
print("Cloud name environment variable:", os.environ[AZUREML_CLOUD_ENV_NAME])
def ml_cloud_config_from_keyword_args(self):
subscription_id = "AZURE_SUBSCRIPTION_ID"
resource_group = "RESOURCE_GROUP_NAME"
credential = DefaultAzureCredential(authority=AzureAuthorityHosts.AZURE_PUBLIC_CLOUD)
# All of these configurations are needed in the kwargs, otherwise the SDK will not recognize the configuration
# and will throw an "Unknown cloud environment" error.
kwargs = {
"cloud": "TestCloud",
"cloud_metadata": {
"azure_portal": "https://test.portal.azure.com/",
"resource_manager": "https://test.management.azure.com/",
"active_directory": "https://test.login.microsoftonline.com/",
"aml_resource_id": "https://test.ml.azure.com/",
"storage_endpoint": "test.core.windows.net",
"registry_discovery_endpoint": "https://test.eastus.api.azureml.ms/",
},
}
ml_client = MLClient(
credential=credential,
subscription_id=subscription_id,
resource_group_name=resource_group,
workspace_name="test-ws1",
**kwargs, # type:ignore
)
# The client will use the cloud that we passed in
print("Client is using cloud:", ml_client._cloud)
# In configuring this cloud, we've also set the environment variable to match it
print("Cloud name environment variable:", os.environ[AZUREML_CLOUD_ENV_NAME])
if __name__ == "__main__":
sample = CloudConfigurationOptions()
sample.ml_cloud_config_from_environment_arm()
sample.ml_cloud_config_from_keyword_args()
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