Update the candidate for SDK - 0.1.0 (Azure#1721)

* Updating the candidate for SDK - 0.1.0b8 * Replacing path with source for load method * Updating load components parameter for more notebooks * Update sdk target * Update notebooks to wait for result from LROPoller * Fix malformed notebook * Update CLI version * Get result from LROPoller from job-schedule notebook * Update sdk release candidate * Remove extraneous result from schedules notebook * Updating the configurations of notebook for working_with_mltable * Wait for compute operations * Get result from LRO poller in online-endpoints-safe-rollout * Update SDK release candidate * Update CLI extension version * Update SDK version * online_deployments.delete -> online_deployments.begin_delete * Update SDK version * Update SDK version * UserIdentity -> UserIdentityConfiguration * Add missing .result() from online-endpoints-safe-rollout * online_endpoints.(list_keys -> get_keys) * USe publicly available artifacts for SDK and CLI Co-authored-by: Harneet Virk <[email protected]>
rdheekonda · Oct 11, 2022 · c1077bc · c1077bc
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Showing 8 changed files with 14 additions and 14 deletions.
diff --git a/cli/setup.sh b/cli/setup.sh
@@ -1,12 +1,12 @@
 # <az_ml_install>
-# az extension add -n ml -y
+az extension add -n ml -y
 # </az_ml_install>
 
 # rc install - uncomment and adjust below to run all tests on a CLI release candidate
 # az extension remove -n ml
 
 # Use a daily build
-az extension add --source https://azuremlsdktestpypi.blob.core.windows.net/wheels/sdk-cli-v2-public/ml-2.9.0-py3-none-any.whl --yes
+# az extension add --source https://azuremlsdktestpypi.blob.core.windows.net/wheels/sdk-cli-v2-public/ml-2.10.0-py3-none-any.whl --yes
 
 # <set_variables>
 GROUP="azureml-examples"

diff --git a/sdk/python/endpoints/online/custom-container/triton/online-endpoints-triton-cc.ipynb b/sdk/python/endpoints/online/custom-container/triton/online-endpoints-triton-cc.ipynb
@@ -423,7 +423,7 @@
    },
    "outputs": [],
    "source": [
-    "keys = ml_client.online_endpoints.list_keys(endpoint_name)\n",
+    "keys = ml_client.online_endpoints.get_keys(endpoint_name)\n",
     "auth_key = keys.primary_key"
    ]
   },

diff --git a/sdk/python/endpoints/online/kubernetes/kubernetes-online-endpoints-safe-rollout.ipynb b/sdk/python/endpoints/online/kubernetes/kubernetes-online-endpoints-safe-rollout.ipynb
@@ -484,7 +484,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ml_client.online_deployments.delete(name=\"blue\", endpoint_name=online_endpoint_name)"
+    "ml_client.online_deployments.begin_delete(name=\"blue\", endpoint_name=online_endpoint_name).result()"
    ]
   },
   {

diff --git a/sdk/python/endpoints/online/managed/online-endpoints-safe-rollout.ipynb b/sdk/python/endpoints/online/managed/online-endpoints-safe-rollout.ipynb
@@ -406,7 +406,7 @@
    "outputs": [],
    "source": [
     "endpoint.mirror_traffic = {\"green\": 10}\n",
-    "ml_client.begin_create_or_update(endpoint)"
+    "ml_client.begin_create_or_update(endpoint).result()"
    ]
   },
   {
@@ -496,7 +496,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ml_client.online_deployments.delete(name=\"blue\", endpoint_name=online_endpoint_name)"
+    "ml_client.online_deployments.begin_delete(name=\"blue\", endpoint_name=online_endpoint_name).result()"
    ]
   },
   {
@@ -512,7 +512,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# ml_client.online_endpoints.begin_delete(name=online_endpoint_name)"
+    "# ml_client.online_endpoints.begin_delete(name=online_endpoint_name).result()"
    ]
   }
  ],

diff --git a/sdk/python/endpoints/online/triton/single-model/online-endpoints-triton.ipynb b/sdk/python/endpoints/online/triton/single-model/online-endpoints-triton.ipynb
@@ -309,7 +309,7 @@
    },
    "outputs": [],
    "source": [
-    "keys = ml_client.online_endpoints.list_keys(endpoint_name)\n",
+    "keys = ml_client.online_endpoints.get_keys(endpoint_name)\n",
     "auth_key = keys.primary_key"
    ]
   },

diff --git a/...n-hyperparameter-tune-deploy-with-keras/train-hyperparameter-tune-deploy-with-keras.ipynb b/...n-hyperparameter-tune-deploy-with-keras/train-hyperparameter-tune-deploy-with-keras.ipynb
@@ -331,7 +331,7 @@
     "* Note that we are passing the webpath directly as an input\n",
     "* Use the compute created earlier to run this command.\n",
     "* Use the curated environment which was declared earlier. \n",
-    "* In this example, we are using the `UserIdentity` to run the command, which means it will be using your identity to run this command and access the data from the blob\n",
+    "* In this example, we are using the `UserIdentityConfiguration` to run the command, which means it will be using your identity to run this command and access the data from the blob\n",
     "* Configure the command line action itself - in this case, the command is `python tf_mnist.py`. You can access the inputs/outputs in the command via the `${{ ... }}` notation.\n",
     "* Configure some metadata like display name, experiment name etc. An experiment is a container for all the iterations one does on a certain project. All the jobs submitted under the same experiment name would be listed next to each other in Azure ML studio.\n"
    ]
@@ -345,7 +345,7 @@
    "outputs": [],
    "source": [
     "from azure.ai.ml import command\n",
-    "from azure.ai.ml import UserIdentity\n",
+    "from azure.ai.ml import UserIdentityConfiguration\n",
     "from azure.ai.ml import Input\n",
     "\n",
     "web_path = \"wasbs://[email protected]/mnist/\"\n",

diff --git a/...ameter-tune-deploy-with-tensorflow/train-hyperparameter-tune-deploy-with-tensorflow.ipynb b/...ameter-tune-deploy-with-tensorflow/train-hyperparameter-tune-deploy-with-tensorflow.ipynb
@@ -257,7 +257,7 @@
     "* Note that we are passing the webpath directly as an input\n",
     "* Use the compute created earlier to run this command.\n",
     "* Use the curated environment which was declared earlier. \n",
-    "* In this example, we are using the `UserIdentity` to run the command, which means it will be using your identity to run this command and access the data from the blob\n",
+    "* In this example, we are using the `UserIdentityConfiguration` to run the command, which means it will be using your identity to run this command and access the data from the blob\n",
     "* Configure the command line action itself - in this case, the command is `python tf_mnist.py`. You can access the inputs/outputs in the command via the `${{ ... }}` notation.\n",
     "* Configure some metadata like display name, experiment name etc. An experiment is a container for all the iterations one does on a certain project. All the jobs submitted under the same experiment name would be listed next to each other in Azure ML studio.\n"
    ]
@@ -271,7 +271,7 @@
    "outputs": [],
    "source": [
     "from azure.ai.ml import command\n",
-    "from azure.ai.ml import UserIdentity\n",
+    "from azure.ai.ml import UserIdentityConfiguration\n",
     "from azure.ai.ml import Input\n",
     "\n",
     "web_path = \"wasbs://[email protected]/mnist/\"\n",

diff --git a/sdk/python/setup.sh b/sdk/python/setup.sh
@@ -1,7 +1,7 @@
 #!/bin/bash
 
 # <az_ml_sdk_install>
-# pip install --pre azure-ai-ml
+pip install azure-ai-ml
 # </az_ml_sdk_install>
 
 # <mldesigner_install>
@@ -16,7 +16,7 @@ pip install pandas
 
 # <az_ml_sdk_test_install>
 # pip install azure-ai-ml==0.1.0.b6
-pip install https://docsupport.blob.core.windows.net/ml-sample-submissions/1902672/azure_ai_ml-0.1.0b8-py3-none-any.whl
+# pip install https://docsupport.blob.core.windows.net/ml-sample-submissions/1905732/azure_ai_ml-1.0.0-py3-none-any.whl
 # </az_ml_sdk_test_install>
 
 pip list