MachineLearningServices.Autorest/custom/New-AzMLWorkspaceCommandJobObject.ps1
# ---------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # http://www.apache.org/licenses/LICENSE-2.0 # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # Code generated by Microsoft (R) AutoRest Code Generator.Changes may cause incorrect behavior and will be lost if the code # is regenerated. # ---------------------------------------------------------------------------------- <# .Synopsis Create an in-memory object for CommandJob. .Description Create an in-memory object for CommandJob. .Outputs Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.CommandJob .Link https://learn.microsoft.com/powershell/module/Az.MachineLearningServices/new-AzMLWorkspaceCommandJobObject #> function New-AzMLWorkspaceCommandJobObject { [OutputType('Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.CommandJob')] [CmdletBinding(PositionalBinding=$false)] Param( [Parameter(HelpMessage="ARM resource ID of the code asset.")] [string] $CodeId, [Parameter(Mandatory, HelpMessage="[Required] The command to execute on startup of the job. eg. `"python train.py`".")] [string] $Command, [Parameter(HelpMessage="[Required] Specifies the type of distribution framework.")] [ArgumentCompleter([Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Support.DistributionType])] [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Support.DistributionType] $DistributionType, [Parameter(Mandatory, HelpMessage="[Required] The ARM resource ID of the Environment specification for the job.")] [string] $EnvironmentId, [Parameter(HelpMessage="Environment variables included in the job.")] # [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ICommandJobEnvironmentVariables] [hashtable] $EnvironmentVariable, [Parameter(HelpMessage="Mapping of input data bindings used in the job.")] [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ICommandJobInputs] $JobInput, [Parameter(HelpMessage="The max run duration in ISO 8601 format, after which the job will be cancelled. Only supports duration with precision as low as Seconds.")] [System.TimeSpan] $LimitTimeout, [Parameter(HelpMessage="Mapping of output data bindings used in the job.")] [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ICommandJobOutputs] $JobOutput, [Parameter(HelpMessage="Optional number of instances or nodes used by the compute target.")] [int] $ResourceInstanceCount, [Parameter(HelpMessage="Optional type of VM used as supported by the compute target.")] [string] $ResourceInstanceType, [Parameter(HelpMessage="Additional properties bag.")] [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.IResourceConfigurationProperties] $ResourceProperty, [Parameter(HelpMessage="ARM resource ID of the compute resource.")] [string] $ComputeId, [Parameter(HelpMessage="Display name of job.")] [string] $DisplayName, [Parameter(HelpMessage="The name of the experiment the job belongs to. If not set, the job is placed in the `"Default`" experiment.")] [string] $ExperimentName, [Parameter(HelpMessage="[Required] Specifies the type of identity framework.")] [ArgumentCompleter([Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Support.IdentityConfigurationType])] [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Support.IdentityConfigurationType] $IdentityType, [Parameter(HelpMessage="Is the asset archived?.")] [bool] $IsArchived, # [Parameter(HelpMessage="List of JobEndpoints. # For local jobs, a job endpoint will have an endpoint value of FileStreamObject.")] # [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.IJobBaseServices] # $Service, [Parameter(HelpMessage="Url for endpoint.")] [string] $ServiceEndpoint, [Parameter(HelpMessage="Port for endpoint.")] [int] $ServicePort, [Parameter(HelpMessage="Additional properties to set on the endpoint.")] [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.IJobServiceProperties] $ServiceProperty, [Parameter(HelpMessage="Endpoint type.")] [string] $ServiceType, [Parameter(HelpMessage="The asset description text.")] [string] $Description, [Parameter(HelpMessage="The asset property dictionary.")] [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.IResourceBaseProperties] $Property, [Parameter(HelpMessage="Tag dictionary. Tags can be added, removed, and updated.")] [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.IResourceBaseTags] $Tag ) process { $Object = [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.CommandJob]::New() $Object.JobType = 'Command' $Object.LimitJobLimitsType = 'Command' # Required define in swagger. $Service = [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.JobBaseServices]::New() if ($PSBoundParameters.ContainsKey('CodeId')) { $Object.CodeId = $CodeId } if ($PSBoundParameters.ContainsKey('Command')) { $Object.Command = $Command } if ($PSBoundParameters.ContainsKey('DistributionType')) { $Object.DistributionType = $DistributionType } if ($PSBoundParameters.ContainsKey('EnvironmentId')) { $Object.EnvironmentId = $EnvironmentId } if ($PSBoundParameters.ContainsKey('EnvironmentVariable')) { $EnvironmentVariableObj = [Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ICommandJobEnvironmentVariables]::New() $EnvironmentVariableObj.CopyFrom($EnvironmentVariable); $Object.EnvironmentVariable = $EnvironmentVariableObj } if ($PSBoundParameters.ContainsKey('JobInput')) { $Object.Input = $JobInput } if ($PSBoundParameters.ContainsKey('LimitJobLimitsType')) { } if ($PSBoundParameters.ContainsKey('LimitTimeout')) { $Object.LimitTimeout = $LimitTimeout } if ($PSBoundParameters.ContainsKey('JobOutput')) { $Object.Output = $JobOutput } if ($PSBoundParameters.ContainsKey('ResourceInstanceCount')) { $Object.ResourceInstanceCount = $ResourceInstanceCount } if ($PSBoundParameters.ContainsKey('ResourceInstanceType')) { $Object.ResourceInstanceType = $ResourceInstanceType } if ($PSBoundParameters.ContainsKey('ResourceProperty')) { $Object.ResourceProperty = $ResourceProperty } if ($PSBoundParameters.ContainsKey('ComputeId')) { $Object.ComputeId = $ComputeId } if ($PSBoundParameters.ContainsKey('DisplayName')) { $Object.DisplayName = $DisplayName } if ($PSBoundParameters.ContainsKey('ExperimentName')) { $Object.ExperimentName = $ExperimentName } if ($PSBoundParameters.ContainsKey('IdentityType')) { $Object.IdentityType = $IdentityType } if ($PSBoundParameters.ContainsKey('IsArchived')) { $Object.IsArchived = $IsArchived } # if ($PSBoundParameters.ContainsKey('Service')) { # $Object.Service = $Service # } if ($PSBoundParameters.ContainsKey('ServiceEndpoint')) { $Service.Endpoint = $ServiceEndpoint } if ($PSBoundParameters.ContainsKey('ServicePort')) { $Service.Port = $ServicePort } if ($PSBoundParameters.ContainsKey('ServiceProperty')) { $Service.Property = $ServiceProperty } if ($PSBoundParameters.ContainsKey('ServiceType')) { $Service.Type = $ServiceType } if ($PSBoundParameters.ContainsKey('Description')) { $Object.Description = $Description } if ($PSBoundParameters.ContainsKey('Property')) { $Object.Property = $Property } if ($PSBoundParameters.ContainsKey('Tag')) { $Object.Tag = $Tag } $Object.Service = $Service return $Object } } # SIG # Begin signature block # MIIoPAYJKoZIhvcNAQcCoIIoLTCCKCkCAQExDzANBglghkgBZQMEAgEFADB5Bgor # BgEEAYI3AgEEoGswaTA0BgorBgEEAYI3AgEeMCYCAwEAAAQQH8w7YFlLCE63JNLG # KX7zUQIBAAIBAAIBAAIBAAIBADAxMA0GCWCGSAFlAwQCAQUABCC8cizm63FaxJcr # GT6a8iyr3daVturjVrWoTWoag5SX7KCCDYUwggYDMIID66ADAgECAhMzAAADri01 # 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