text: # coding=utf-8
  # *** WARNING: this file was generated by the Pulumi SDK Generator. ***
  # *** Do not edit by hand unless you're certain you know what you are doing! ***
  
  import warnings
  import pulumi
  import pulumi.runtime
  from typing import Any, Mapping, Optional, Sequence, Union, overload
  from ... import _utilities
  from . import outputs
  from ._enums import *
  from ._inputs import *
  
  __all__ = ['LabelingJobArgs', 'LabelingJob']
  
  @pulumi.input_type
  class LabelingJobArgs:
      def __init__(__self__, *,
                   resource_group_name: pulumi.Input[str],
                   workspace_name: pulumi.Input[str],
                   labeling_job_id: Optional[pulumi.Input[str]] = None,
                   properties: Optional[pulumi.Input['LabelingJobPropertiesArgs']] = None):
          """
          The set of arguments for constructing a LabelingJob resource.
          :param pulumi.Input[str] resource_group_name: Name of the resource group in which workspace is located.
          :param pulumi.Input[str] workspace_name: Name of Azure Machine Learning workspace.
          :param pulumi.Input[str] labeling_job_id: Name and identifier for LabelingJob.
          :param pulumi.Input['LabelingJobPropertiesArgs'] properties: Definition of a labeling job.
          """
          pulumi.set(__self__, "resource_group_name", resource_group_name)
          pulumi.set(__self__, "workspace_name", workspace_name)
          if labeling_job_id is not None:
              pulumi.set(__self__, "labeling_job_id", labeling_job_id)
          if properties is not None:
              pulumi.set(__self__, "properties", properties)
  
      @property
      @pulumi.getter(name="resourceGroupName")
      def resource_group_name(self) -> pulumi.Input[str]:
          """
          Name of the resource group in which workspace is located.
          """
          return pulumi.get(self, "resource_group_name")
  
      @resource_group_name.setter
      def resource_group_name(self, value: pulumi.Input[str]):
          pulumi.set(self, "resource_group_name", value)
  
      @property
      @pulumi.getter(name="workspaceName")
      def workspace_name(self) -> pulumi.Input[str]:
          """
          Name of Azure Machine Learning workspace.
          """
          return pulumi.get(self, "workspace_name")
  
      @workspace_name.setter
      def workspace_name(self, value: pulumi.Input[str]):
          pulumi.set(self, "workspace_name", value)
  
      @property
      @pulumi.getter(name="labelingJobId")
      def labeling_job_id(self) -> Optional[pulumi.Input[str]]:
          """
          Name and identifier for LabelingJob.
          """
          return pulumi.get(self, "labeling_job_id")
  
      @labeling_job_id.setter
      def labeling_job_id(self, value: Optional[pulumi.Input[str]]):
          pulumi.set(self, "labeling_job_id", value)
  
      @property
      @pulumi.getter
      def properties(self) -> Optional[pulumi.Input['LabelingJobPropertiesArgs']]:
          """
          Definition of a labeling job.
          """
          return pulumi.get(self, "properties")
  
      @properties.setter
      def properties(self, value: Optional[pulumi.Input['LabelingJobPropertiesArgs']]):
          pulumi.set(self, "properties", value)
  
  
  class LabelingJob(pulumi.CustomResource):
      @overload
      def __init__(__self__,
                   resource_name: str,
                   opts: Optional[pulumi.ResourceOptions] = None,
                   labeling_job_id: Optional[pulumi.Input[str]] = None,
                   properties: Optional[pulumi.Input[pulumi.InputType['LabelingJobPropertiesArgs']]] = None,
                   resource_group_name: Optional[pulumi.Input[str]] = None,
                   workspace_name: Optional[pulumi.Input[str]] = None,
                   __props__=None):
          """
          Machine Learning labeling job object wrapped into ARM resource envelope.
  
          :param str resource_name: The name of the resource.
          :param pulumi.ResourceOptions opts: Options for the resource.
          :param pulumi.Input[str] labeling_job_id: Name and identifier for LabelingJob.
          :param pulumi.Input[pulumi.InputType['LabelingJobPropertiesArgs']] properties: Definition of a labeling job.
          :param pulumi.Input[str] resource_group_name: Name of the resource group in which workspace is located.
          :param pulumi.Input[str] workspace_name: Name of Azure Machine Learning workspace.
          """
          ...
      @overload
      def __init__(__self__,
                   resource_name: str,
                   args: LabelingJobArgs,
                   opts: Optional[pulumi.ResourceOptions] = None):
          """
          Machine Learning labeling job object wrapped into ARM resource envelope.
  
          :param str resource_name: The name of the resource.
          :param LabelingJobArgs args: The arguments to use to populate this resource's properties.
          :param pulumi.ResourceOptions opts: Options for the resource.
          """
          ...
      def __init__(__self__, resource_name: str, *args, **kwargs):
          resource_args, opts = _utilities.get_resource_args_opts(LabelingJobArgs, pulumi.ResourceOptions, *args, **kwargs)
          if resource_args is not None:
              __self__._internal_init(resource_name, opts, **resource_args.__dict__)
          else:
              __self__._internal_init(resource_name, *args, **kwargs)
  
      def _internal_init(__self__,
                   resource_name: str,
                   opts: Optional[pulumi.ResourceOptions] = None,
                   labeling_job_id: Optional[pulumi.Input[str]] = None,
                   properties: Optional[pulumi.Input[pulumi.InputType['LabelingJobPropertiesArgs']]] = None,
                   resource_group_name: Optional[pulumi.Input[str]] = None,
                   workspace_name: Optional[pulumi.Input[str]] = None,
                   __props__=None):
          if opts is None:
              opts = pulumi.ResourceOptions()
          if not isinstance(opts, pulumi.ResourceOptions):
              raise TypeError('Expected resource options to be a ResourceOptions instance')
          if opts.version is None:
              opts.version = _utilities.get_version()
          if opts.id is None:
              if __props__ is not None:
                  raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
              __props__ = LabelingJobArgs.__new__(LabelingJobArgs)
  
              __props__.__dict__["labeling_job_id"] = labeling_job_id
              __props__.__dict__["properties"] = properties
              if resource_group_name is None and not opts.urn:
                  raise TypeError("Missing required property 'resource_group_name'")
              __props__.__dict__["resource_group_name"] = resource_group_name
              if workspace_name is None and not opts.urn:
                  raise TypeError("Missing required property 'workspace_name'")
              __props__.__dict__["workspace_name"] = workspace_name
              __props__.__dict__["name"] = None
              __props__.__dict__["system_data"] = None
              __props__.__dict__["type"] = None
          alias_opts = pulumi.ResourceOptions(aliases=[pulumi.Alias(type_="azure-nextgen:machinelearningservices/v20200901preview:LabelingJob"), pulumi.Alias(type_="azure-native:machinelearningservices:LabelingJob"), pulumi.Alias(type_="azure-nextgen:machinelearningservices:LabelingJob"), pulumi.Alias(type_="azure-native:machinelearningservices/v20210301preview:LabelingJob"), pulumi.Alias(type_="azure-nextgen:machinelearningservices/v20210301preview:LabelingJob")])
          opts = pulumi.ResourceOptions.merge(opts, alias_opts)
          super(LabelingJob, __self__).__init__(
              'azure-native:machinelearningservices/v20200901preview:LabelingJob',
              resource_name,
              __props__,
              opts)
  
      @staticmethod
      def get(resource_name: str,
              id: pulumi.Input[str],
              opts: Optional[pulumi.ResourceOptions] = None) -> 'LabelingJob':
          """
          Get an existing LabelingJob resource's state with the given name, id, and optional extra
          properties used to qualify the lookup.
  
          :param str resource_name: The unique name of the resulting resource.
          :param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
          :param pulumi.ResourceOptions opts: Options for the resource.
          """
          opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
  
          __props__ = LabelingJobArgs.__new__(LabelingJobArgs)
  
          __props__.__dict__["name"] = None
          __props__.__dict__["properties"] = None
          __props__.__dict__["system_data"] = None
          __props__.__dict__["type"] = None
          return LabelingJob(resource_name, opts=opts, __props__=__props__)
  
      @property
      @pulumi.getter
      def name(self) -> pulumi.Output[str]:
          """
          The name of the resource entity.
          """
          return pulumi.get(self, "name")
  
      @property
      @pulumi.getter
      def properties(self) -> pulumi.Output['outputs.LabelingJobPropertiesResponse']:
          """
          Definition of a labeling job.
          """
          return pulumi.get(self, "properties")
  
      @property
      @pulumi.getter(name="systemData")
      def system_data(self) -> pulumi.Output['outputs.SystemDataResponse']:
          """
          Metadata pertaining to creation and last modification of the resource.
          """
          return pulumi.get(self, "system_data")
  
      @property
      @pulumi.getter
      def type(self) -> pulumi.Output[str]:
          """
          The resource provider and type.
          """
          return pulumi.get(self, "type")
  
  