Azure offers several ways of deploying a deep-learning model (e.g. CNTK): Windows Web App, Linux (Docker) Web App, and Azure Container Services (Docker). Both of the Docker methods are perhaps more convenient, however they are not publicly available at the time of writing. Hence, in this post we will deploy a ResNet-18 model to Azure Web Apps and then submit some test pictures to it using a sample HTML interface and also via python.
HTML
Python
The above screenshot is taken from this notebook. If you wish to run some speed-tests then this notebook shows how to submit asyncrochonous requests to the created API to get an idea of how long it takes to classify images in bulk.
-
Download the contents of this repo and open a Command Prompt in the folder
-
Run the following commands to check you have git and azure-cli installed:
az --version # time-of-writing: 2.0.1 pip install azure-cli # otherwise install azure-cli git --version # time of writing: 2.9.2.windows.1 -
Set your username and password for local git deployment (you only need to do this once) e.g.:
set uname=<username_for_local_git_deployment> set pass=<password_for_local_git_deployment> # Create a user-name and password for git deployment of all your apps az appservice web deployment user set --user-name %uname% --password %pass% -
Create your web-app by running the below commands:
# Name for your web-app set appn=<app_name> # Name for resource-group containing web-app set rgname=<name_for_resource_group_that_contains_app> # Login to azure az login # Create a resource-group az group create --location westeurope --name %rgname% # Create a paid 'S2' plan to support your app # The standard paid plans are: S1, S2, S3 az appservice plan create --name %appn% --resource-group %rgname% --sku S2 # Create the web-app az appservice web create --name %appn% --resource-group %rgname% --plan %appn% # Configure for local git deployment (SAVE URL) az appservice web source-control config-local-git --name %appn% --resource-group %rgname% --query url --output tsv # Initialise your git repo git init # Add the azure endpoint git remote add azure <PASTE_URL_FROM_ABOVE> # e.g. git remote add azure https://[email protected]/wincntkdemo.git -
We will now install Python. Navigate to your web-app on Azure Portal, scroll down to the "Extensions" blade and select it:
Then, click on "Add", locate "Python 3.5.3 x64" and add it (you must use this extension)
Make sure you get a notification that this installed successfully:
-
(Optional) Under the "Application settings" blade set "Always On" to "On" to reduce the response time (since your model will be kept loaded)
-
Deploy this demo by running:
git add -A git commit -m "init" git push azure masterIf everything has gone successfully you should see the following line in the script output:
remote: Successfully installed cntk-2.0rc1 remote: .. remote: 2.0rc1
You should now be able to navigate to your web-app address and upload a photo that will be classified according to the CNN: ResNet-18
-
You can include references to other modules (e.g. pandas or opencv) in your model.py file, however you must add the module to the "requirements.txt" file so that python installs the module. If the module needs to be built you can you can go to http://www.lfd.uci.edu/~gohlke/pythonlibs/ to download the pre-built wheel file (to the wheels folder). Don't forget to add the wheel path to the "requirements.txt" file at the root of the directory. Note: Numpy, Scipy, and CNTK wheels are automatically installed inside the "deploy.cmd" script; to change this you can edit the deploy.cmd file to point to whichever numpy wheel you require
-
Editing deploy.cmd - the install script automatically adds the binaries for CNTK v2.0 rc1. However if you want to use Python 3.6 or CNTK v2.0 rc1+ then alter the below in the "deploy.cmd" script:
:: VARIABLES echo "ATTENTION" echo "USER MUST CHECK/SET THESE VARIABLES:" SET PYTHON_EXE=%SYSTEMDRIVE%\home\python353x64\python.exe SET NUMPY_WHEEL=https://azurewebappcntk.blob.core.windows.net/wheels/numpy-1.12.1+mkl-cp35-cp35m-win_amd64.whl SET SCIPY_WHEEL=https://azurewebappcntk.blob.core.windows.net/wheels/scipy-0.19.0-cp35-cp35m-win_amd64.whl SET CNTK_WHEEL=https://azurewebappcntk.blob.core.windows.net/cntkrc/cntk-2.0rc1-cp35-cp35m-win_amd64.whl SET CNTK_BIN=https://azurewebappcntk.blob.core.windows.net/cntkrc/cntk.zipTo create the 'cntk.zip' file you just need to extract the cntk/cntk folder (i.e. the folder that contains 'CNTK.exe' and DLLs; you can remove the python sub-folder which contains the wheels, if it exists) and then reference it with the %CTNK_BIN% environmental variable above.
-
You can also install a different python extension if you wish, however make sure to reference it properly (and also to get the Numpy, Scipy and CNTK Wheels for it). For example, the "Python 3.5.3 x64" extension is installed in the directory "D:\home\python353x64", and thus the script references:
SET PYTHON_EXE=%SYSTEMDRIVE%\home\python353x64\python.exe -
Finally, alter the "model.py" script as desired in the folder "WebApp", along with the HTMl template, "index.html" in "templates" and then push your changes to the repo:
git add -A git commit -m "modified some script" git push azure master
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent