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Roope Astala
2018-09-21 16:03:50 -04:00
parent 48f037d6dd
commit 87bb03f7a3
23 changed files with 2724 additions and 247 deletions
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tutorials/02.deploy-models.ipynb
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@@ -15,7 +15,7 @@
"source": [
"# Tutorial #2: Deploy an image classification model in Azure Container Instance (ACI)\n",
"\n",
"This tutorial is **part two of a two-part tutorial series**. In the [previous tutorial](01.train-models.ipynb), you trained machine learning models and then registered the best one in your workspace on the cloud. \n",
"This tutorial is **part two of a two-part tutorial series**. In the [previous tutorial](01.train-models.ipynb), you trained machine learning models and then registered a model in your workspace on the cloud. \n",
"\n",
"Now, you're ready to deploy the model as a web service in [Azure Container Instances](https://docs.microsoft.com/azure/container-instances/) (ACI). A web service is an image, in this case a Docker image, that encapsulates the scoring logic and the model itself. \n",
"\n",
@@ -33,8 +33,7 @@
"## Prerequisites\n",
"\n",
"Complete the model training in the [Tutorial #1: Train an image classification model with Azure Machine Learning](01.train-models.ipynb) notebook. \n",
"\n",
"If you did NOT complete the tutorial, you can instead run this cell to create a model and download the data needed for this tutorial:"
"\n"
]
},
{
@@ -43,6 +42,8 @@
"metadata": {},
"outputs": [],
"source": [
"# If you did NOT complete the tutorial, you can instead run this cell \n",
"# This will register a model and download the data needed for this tutorial\n",
"# These prerequisites are created in the training tutorial\n",
"# Feel free to skip this cell if you completed the training tutorial \n",
"\n",
@@ -251,9 +252,9 @@
"Create the scoring script, called score.py, used by the web service call to show how to use the model.\n",
"\n",
"You must include two required functions into the scoring script:\n",
"* The `init()` function, which typically loads the model into a global object. This function is executed only once when the Docker container is started. \n",
"* The `init()` function, which typically loads the model into a global object. This function is run only once when the Docker container is started. \n",
"\n",
"* The `run(input_data)` function uses the model to predict a value based on the input data. Inputs and outputs to the run typically use JSON for serialization and de-serialization, but other formats are supported."
"* The `run(input_data)` function uses the model to predict a value based on the input data. Inputs and outputs to the run typically use JSON for serialization and de-serialization, but other formats are supported.\n"
]
},
{
@@ -332,7 +333,7 @@
"source": [
"### Create configuration file\n",
"\n",
"Create a deployment configuration file and specify the number of CPUs and gigabyte of RAM needed for your ACI container. While it depends on your model, the default of 1 core and 1 gigabyte of RAM is usually sufficient for many models. If you feel you need more later, you can always modify the configuration and redeploy the service."
"Create a deployment configuration file and specify the number of CPUs and gigabyte of RAM needed for your ACI container. While it depends on your model, the default of 1 core and 1 gigabyte of RAM is usually sufficient for many models. If you feel you need more later, you would have to recreate the image and redeploy the service."
]
},
{