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update samples from Release-11 as a part of 1.5.0 SDK stable release

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vizhur
2020-05-11 18:59:22 +00:00
parent e98131729e
commit 553fa43e17
76 changed files with 3818 additions and 622 deletions
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7
how-to-use-azureml/deployment/deploy-to-local/register-model-deploy-local.ipynb
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@@ -82,7 +82,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"You can add tags and descriptions to your models. we are using `sklearn_regression_model.pkl` file in the current directory as a model with the name `sklearn_regression_model_local` in the workspace.\n",
"You can add tags and descriptions to your models. we are using `sklearn_regression_model.pkl` file in the current directory as a model with the name `sklearn_regression_model` in the workspace.\n",
"\n",
"Using tags, you can track useful information such as the name and version of the machine learning library used to train the model, framework, category, target customer etc. Note that tags must be alphanumeric."
]
@@ -100,7 +100,7 @@
"from azureml.core.model import Model\n",
"\n",
"model = Model.register(model_path=\"sklearn_regression_model.pkl\",\n",
" model_name=\"sklearn_regression_model_local\",\n",
" model_name=\"sklearn_regression_model\",\n",
" tags={'area': \"diabetes\", 'type': \"regression\"},\n",
" description=\"Ridge regression model to predict diabetes\",\n",
" workspace=ws)"
@@ -159,6 +159,8 @@
"- an inference configuration\n",
"- a single column tabular dataset, where each row contains a string representing sample request data sent to the service.\n",
"\n",
"Please, note that profiling is a long running operation and can take up to 25 minutes depending on the size of the dataset.\n",
"\n",
"At this point we only support profiling of services that expect their request data to be a string, for example: string serialized json, text, string serialized image, etc. The content of each row of the dataset (string) will be put into the body of the HTTP request and sent to the service encapsulating the model for scoring.\n",
"\n",
"Below is an example of how you can construct an input dataset to profile a service which expects its incoming requests to contain serialized json. In this case we created a dataset based one hundred instances of the same request data. In real world scenarios however, we suggest that you use larger datasets with various inputs, especially if your model resource usage/behavior is input dependent."
@@ -245,6 +247,7 @@
" cpu=1.0,\n",
" memory_in_gb=0.5)\n",
"\n",
"# profiling is a long running operation and may take up to 25 min\n",
"profile.wait_for_completion(True)\n",
"details = profile.get_details()"
]