1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
|
# 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_authentication.py
DESCRIPTION:
These samples demonstrate authenticating a client for multiple clouds.
USAGE:
python ml_samples_authentication.py
Set the environment variables with your own values before running the sample:
1) AZURE_SUBSCRIPTION_ID - The subscription id.
2) RESOURCE_GROUP_NAME - Resource group name.
"""
import os
class MLClientSamples(object):
def ml_auth_azure_default_credential(self):
subscription_id = os.environ["AZURE_SUBSCRIPTION_ID"]
resource_group = os.environ["RESOURCE_GROUP_NAME"]
workspace_name = "test-ws1"
# [START create_ml_client_default_credential]
from azure.ai.ml import MLClient
from azure.identity import AzureAuthorityHosts, DefaultAzureCredential
ml_client = MLClient(
subscription_id=subscription_id,
resource_group_name=resource_group,
workspace_name=workspace_name,
credential=DefaultAzureCredential(),
)
# [END create_ml_client_default_credential]
# [START create_ml_client_from_config_default]
from azure.ai.ml import MLClient
client = MLClient.from_config(credential=DefaultAzureCredential(), path="./sdk/ml/azure-ai-ml/samples/src")
# [END create_ml_client_from_config_default]
# [START create_ml_client_from_config_custom_filename]
from azure.ai.ml import MLClient
client = MLClient.from_config(
credential=DefaultAzureCredential(),
file_name="./sdk/ml/azure-ai-ml/samples/team_workspace_configuration.json",
)
# [END create_ml_client_from_config_custom_filename]
# [START ml_client_create_or_update]
from azure.ai.ml import Input, command
from azure.ai.ml.constants import AssetTypes
from azure.ai.ml.entities import ManagedOnlineEndpoint, UserIdentityConfiguration
client = MLClient(
subscription_id=subscription_id,
resource_group_name=resource_group,
workspace_name=workspace_name,
credential=DefaultAzureCredential(),
)
job = command(
code="./sdk/ml/azure-ai-ml/samples/src",
command="echo hello world",
environment="AzureML-sklearn-1.0-ubuntu20.04-py38-cpu:1",
compute="cpu-cluster",
identity=UserIdentityConfiguration(),
)
client.create_or_update(job)
# [END ml_client_create_or_update]
# [START ml_client_begin_create_or_update]
from random import randint
from azure.ai.ml.entities import ManagedOnlineEndpoint
client = MLClient(
subscription_id=subscription_id,
resource_group_name=resource_group,
workspace_name=workspace_name,
credential=DefaultAzureCredential(),
)
endpoint = ManagedOnlineEndpoint(
name=f"online-endpoint-name-{randint(1, 1000)}",
description="this is a sample online endpoint",
auth_mode="key",
)
created_job = client.begin_create_or_update(endpoint)
# [END ml_client_begin_create_or_update]
# [START user_identity_configuration]
from azure.ai.ml import Input, command
from azure.ai.ml.constants import AssetTypes
from azure.ai.ml.entities import UserIdentityConfiguration
job = command(
code="./sdk/ml/azure-ai-ml/samples/src",
command="python read_data.py --input_data ${{inputs.input_data}}",
inputs={"input_data": Input(type=AssetTypes.MLTABLE, path="./sample_data")},
environment="AzureML-sklearn-1.0-ubuntu20.04-py38-cpu:1",
compute="cpu-cluster",
identity=UserIdentityConfiguration(),
)
# [END user_identity_configuration]
# [START aml_token_configuration]
from azure.ai.ml import Input, command
from azure.ai.ml.constants import AssetTypes
from azure.ai.ml.entities._credentials import AmlTokenConfiguration
node = command(
description="description",
environment="AzureML-sklearn-1.0-ubuntu20.04-py38-cpu:33",
code="./tests/test_configs/training/",
command="python read_data.py --input_data ${{inputs.input_data}}",
inputs={"input_data": Input(type=AssetTypes.MLTABLE, path="./sample_data")},
display_name="builder_command_job",
compute="testCompute",
experiment_name="mfe-test1-dataset",
identity=AmlTokenConfiguration(),
)
# [END aml_token_configuration]
# [START create_ml_client_sovereign_cloud]
from azure.ai.ml import MLClient
from azure.identity import AzureAuthorityHosts, DefaultAzureCredential
kwargs = {"cloud": "AzureChinaCloud"}
ml_client = MLClient(
subscription_id=subscription_id,
resource_group_name=resource_group,
credential=DefaultAzureCredential(authority=AzureAuthorityHosts.AZURE_CHINA),
**kwargs,
)
# [END create_ml_client_sovereign_cloud]
if __name__ == "__main__":
sample = MLClientSamples()
sample.ml_auth_azure_default_credential()
|
