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A native Pulumi package for creating and managing Azure resources.
// *** WARNING: this file was generated by pulumi-java-gen. ***
// *** Do not edit by hand unless you're certain you know what you are doing! ***
package com.pulumi.azurenative.machinelearningservices.outputs;
import com.pulumi.azurenative.machinelearningservices.outputs.AmlTokenResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.CommandJobLimitsResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.CustomModelJobInputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.CustomModelJobOutputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.JobResourceConfigurationResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.JobServiceResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.LiteralJobInputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.MLFlowModelJobInputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.MLFlowModelJobOutputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.MLTableJobInputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.MLTableJobOutputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.ManagedIdentityResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.MpiResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.PyTorchResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.TensorFlowResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.TritonModelJobInputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.TritonModelJobOutputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.UriFileJobInputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.UriFileJobOutputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.UriFolderJobInputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.UriFolderJobOutputResponse;
import com.pulumi.azurenative.machinelearningservices.outputs.UserIdentityResponse;
import com.pulumi.core.annotations.CustomType;
import com.pulumi.exceptions.MissingRequiredPropertyException;
import java.lang.Boolean;
import java.lang.Object;
import java.lang.String;
import java.util.Map;
import java.util.Objects;
import java.util.Optional;
import javax.annotation.Nullable;
@CustomType
public final class CommandJobResponse {
/**
* @return ARM resource ID of the code asset.
*
*/
private @Nullable String codeId;
/**
* @return [Required] The command to execute on startup of the job. eg. "python train.py"
*
*/
private String command;
/**
* @return ARM resource ID of the component resource.
*
*/
private @Nullable String componentId;
/**
* @return ARM resource ID of the compute resource.
*
*/
private @Nullable String computeId;
/**
* @return The asset description text.
*
*/
private @Nullable String description;
/**
* @return Display name of job.
*
*/
private @Nullable String displayName;
/**
* @return Distribution configuration of the job. If set, this should be one of Mpi, Tensorflow, PyTorch, or null.
*
*/
private @Nullable Object distribution;
/**
* @return [Required] The ARM resource ID of the Environment specification for the job.
*
*/
private String environmentId;
/**
* @return Environment variables included in the job.
*
*/
private @Nullable Map environmentVariables;
/**
* @return The name of the experiment the job belongs to. If not set, the job is placed in the "Default" experiment.
*
*/
private @Nullable String experimentName;
/**
* @return Identity configuration. If set, this should be one of AmlToken, ManagedIdentity, UserIdentity or null.
* Defaults to AmlToken if null.
*
*/
private @Nullable Object identity;
/**
* @return Mapping of input data bindings used in the job.
*
*/
private @Nullable Map inputs;
/**
* @return Is the asset archived?
*
*/
private @Nullable Boolean isArchived;
/**
* @return Enum to determine the type of job.
* Expected value is 'Command'.
*
*/
private String jobType;
/**
* @return Command Job limit.
*
*/
private @Nullable CommandJobLimitsResponse limits;
/**
* @return Mapping of output data bindings used in the job.
*
*/
private @Nullable Map outputs;
/**
* @return Input parameters.
*
*/
private Object parameters;
/**
* @return The asset property dictionary.
*
*/
private @Nullable Map properties;
/**
* @return Compute Resource configuration for the job.
*
*/
private @Nullable JobResourceConfigurationResponse resources;
/**
* @return List of JobEndpoints.
* For local jobs, a job endpoint will have an endpoint value of FileStreamObject.
*
*/
private @Nullable Map services;
/**
* @return Status of the job.
*
*/
private String status;
/**
* @return Tag dictionary. Tags can be added, removed, and updated.
*
*/
private @Nullable Map tags;
private CommandJobResponse() {}
/**
* @return ARM resource ID of the code asset.
*
*/
public Optional codeId() {
return Optional.ofNullable(this.codeId);
}
/**
* @return [Required] The command to execute on startup of the job. eg. "python train.py"
*
*/
public String command() {
return this.command;
}
/**
* @return ARM resource ID of the component resource.
*
*/
public Optional componentId() {
return Optional.ofNullable(this.componentId);
}
/**
* @return ARM resource ID of the compute resource.
*
*/
public Optional computeId() {
return Optional.ofNullable(this.computeId);
}
/**
* @return The asset description text.
*
*/
public Optional description() {
return Optional.ofNullable(this.description);
}
/**
* @return Display name of job.
*
*/
public Optional displayName() {
return Optional.ofNullable(this.displayName);
}
/**
* @return Distribution configuration of the job. If set, this should be one of Mpi, Tensorflow, PyTorch, or null.
*
*/
public Optional
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