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Command-line install for Machine Learning Server for Windows

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Important

This content is being retired and may not be updated in the future. The support for Machine Learning Server will end on July 1, 2022. For more information, see What's happening to Machine Learning Server?

Applies to: Machine Learning Server 9.2.1 | 9.3 | 9.4

This article provides syntax and examples for running Machine Learning Server ServerSetup.exe from the command line. You can use command-line parameters for an internet-connected or offline installation. A command-line installation requires administrator permissions.

Before you start, review Install Machine Learning Server on Windows for:

  • System and operational requirements
  • Download and file extraction information
  • A summary of what is installed
  • Steps for validating your installation

This article assumes you have already downloaded and extracted the setup program.

Command-line options

You can run ServerSetup.exe from the command line with options to expose or hide the wizard, set an install mode, or specify options for adding features or using custom folder locations.

User Interaction Options

Parameter Description
/full Invokes the wizard.
/quiet Hides the wizard, running a silent installation with no interaction or prompts. EULA acceptance is automatic for both the server and all open-source distributions of R and Python.
/passive Equivalent to /quiet in this release.

Install Modes

Parameter Description
/install Runs ServerSetup.exe in install mode, used to add R_SERVER, PYTHON_SERVER, or the pre-trained machine learning models
/uninstall Removes an existing installation of any component previously installed.
/modify Runs ServerSetup.exe in modify mode. Setup looks for an existing installation and offers options for changing an installation (for example, you could add the pre-trained models). Use this option if you want to rerun (or repair) an installation.

Install Options

Parameter Description
/r Install just the R feature. Use with /install. Applies to version 9.3 and 9.4 only.
/python Install just the Python feature. Use with /install. Applies to version 9.3 and 9.4 only.
/offline Instructs setup to find .cab files on the local system in the mediadir location. This option requires that the server is disconnected from the internet.
/installdir="" Specifies the installation directory. By default, this is C:\Program Files\Microsoft\R Server\R_SERVER.
/cachedir="" A download location for the .cab files. By default, setup uses %temp% for the local admin user. Assuming an online installation scenario, you can set this parameter to have setup download the .cabs to the folder you specify.
/mediadir="" The .cab file location setup uses to find .cab files in an offline installation. By default, setup uses %temp% for local admin.
/models Adds the pre-trained machine learning models. Use with /install.

Default installation

A default installation includes R and Python, but not the pre-trained models. You must explicitly add /models to an installation to add this feature.

The command-line equivalent of a double-click invocation of ServerSetup.exe is serversetup.exe /install /full.

Examples

  1. Run setup in unattended mode with no prompts or user interaction, to install everything. For version 9.2.1, both R Server and Python Server are included in every installation; the pre-trained models are optional and have to be explicitly specified to include them in the installation. For version 9.3 and 9.4 only, you can set flags to install individual components: R, Python, pre-trained models:

    • serversetup.exe /quiet /r
    • serversetup.exe /quiet /python
    • serversetup.exe /quiet /models

  2. Add the pre-trained machine learning models to an existing installation. You cannot install them as a standalone component. The models require R or Python. During installation, the pre-trained models are inserted into the MicrosoftML (R) and microsoftml (Python) libraries, or both if you add both languages. Once installed, you cannot incrementally remove them. Removal will require uninstall and reinstall of Python or R Server.

    serversetup.exe /install /models

  3. Uninstall the software in unattended mode.

    serversetup.exe /quiet /uninstall

  4. Unattended offline install requires .cab files that provide open-source distributions and other dependencies. The /offline parameter instructs setup to look for the .cab files on the local system. By default, setup looks for the .cab files in the %temp% directory of local admin, but you could also set the media directory if the .cab files are in a different folder. For more information and .cab download links, see Offline installation.

    serversetup.exe /quiet /offline /mediadir="D:/Public/CABS

9.4 CAB file list

For unattended setup or offline setup, copy the .cab files to either the setup user's temp directory (C:\Users<user-name>\AppData\Local\Temp) or to a folder specified via the /mediadir flag.

Component Download Used for
MLM MLM_9.4.7.0_1033.cab Pre-trained models, R or Python
Microsoft R Open SRO_3.5.2.0_1033.cab R
Microsoft Python Open SPO_4.5.12.0_1033.cab Python
Microsoft Python Server SPS_9.4.7.0_1033.cab Python
Python script Install-PyForMLS Python

9.3 CAB file list

For unattended setup or offline setup, copy the .cab files to either the setup user's temp directory (C:\Users<user-name>\AppData\Local\Temp) or to a folder specified via the /mediadir flag.

Component Download Used for
MLM MLM_9.3.0.0_1033.cab Pre-trained models, R or Python
Microsoft R Open SRO_3.4.3.0_1033.cab R
Microsoft Python Open SPO_9.3.0.0_1033.cab Python

There is no separate Python Server package in the 9.3 version.

9.2.1 CAB file list

For unattended setup or offline setup, copy the .cab files to either the setup user's temp directory (C:\Users<user-name>\AppData\Local\Temp) or to a folder specified via the /mediadir flag.

Component Download Used for
MLM MLM_9.2.1.0_1033.cab Pre-trained models, R or Python
Microsoft R Open SRO_3.4.1.0_1033.cab R
Microsoft Python Open SPO_9.2.1.0_1033.cab Python
Microsoft Python Server SPS_9.2.1.0_1033.cab Python

Next steps

We recommend continuing with any Quickstart tutorial listed in the contents pane.

See also