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Class: Aws::SageMaker::Types::DescribeProcessingJobResponse
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::DescribeProcessingJobResponse
- Defined in:
- (unknown)
Overview
Returned by:
Instance Attribute Summary collapse
-
#app_specification ⇒ Types::AppSpecification
Configures the processing job to run a specified container image.
-
#auto_ml_job_arn ⇒ String
The ARN of an AutoML job associated with this processing job.
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#creation_time ⇒ Time
The time at which the processing job was created.
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#environment ⇒ Hash<String,String>
The environment variables set in the Docker container.
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#exit_message ⇒ String
An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
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#experiment_config ⇒ Types::ExperimentConfig
The configuration information used to create an experiment.
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#failure_reason ⇒ String
A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
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#last_modified_time ⇒ Time
The time at which the processing job was last modified.
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#monitoring_schedule_arn ⇒ String
The ARN of a monitoring schedule for an endpoint associated with this processing job.
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#network_config ⇒ Types::NetworkConfig
Networking options for a processing job.
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#processing_end_time ⇒ Time
The time at which the processing job completed.
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#processing_inputs ⇒ Array<Types::ProcessingInput>
The inputs for a processing job.
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#processing_job_arn ⇒ String
The Amazon Resource Name (ARN) of the processing job.
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#processing_job_name ⇒ String
The name of the processing job.
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#processing_job_status ⇒ String
Provides the status of a processing job.
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#processing_output_config ⇒ Types::ProcessingOutputConfig
Output configuration for the processing job.
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#processing_resources ⇒ Types::ProcessingResources
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job.
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#processing_start_time ⇒ Time
The time at which the processing job started.
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#role_arn ⇒ String
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
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#stopping_condition ⇒ Types::ProcessingStoppingCondition
The time limit for how long the processing job is allowed to run.
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#training_job_arn ⇒ String
The ARN of a training job associated with this processing job.
Instance Attribute Details
#app_specification ⇒ Types::AppSpecification
Configures the processing job to run a specified container image.
#auto_ml_job_arn ⇒ String
The ARN of an AutoML job associated with this processing job.
#creation_time ⇒ Time
The time at which the processing job was created.
#environment ⇒ Hash<String,String>
The environment variables set in the Docker container.
#exit_message ⇒ String
An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
#experiment_config ⇒ Types::ExperimentConfig
The configuration information used to create an experiment.
#failure_reason ⇒ String
A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
#last_modified_time ⇒ Time
The time at which the processing job was last modified.
#monitoring_schedule_arn ⇒ String
The ARN of a monitoring schedule for an endpoint associated with this processing job.
#network_config ⇒ Types::NetworkConfig
Networking options for a processing job.
#processing_end_time ⇒ Time
The time at which the processing job completed.
#processing_inputs ⇒ Array<Types::ProcessingInput>
The inputs for a processing job.
#processing_job_arn ⇒ String
The Amazon Resource Name (ARN) of the processing job.
#processing_job_name ⇒ String
The name of the processing job. The name must be unique within an AWS Region in the AWS account.
#processing_job_status ⇒ String
Provides the status of a processing job.
Possible values:
- InProgress
- Completed
- Failed
- Stopping
- Stopped
#processing_output_config ⇒ Types::ProcessingOutputConfig
Output configuration for the processing job.
#processing_resources ⇒ Types::ProcessingResources
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
#processing_start_time ⇒ Time
The time at which the processing job started.
#role_arn ⇒ String
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
#stopping_condition ⇒ Types::ProcessingStoppingCondition
The time limit for how long the processing job is allowed to run.
#training_job_arn ⇒ String
The ARN of a training job associated with this processing job.