BatchTransformInput ¶

class BatchTransformInput(TypedDict, closed=True):
    data_captured_destination_s3_uri: NotRequired[
        "capo_sagemaker.types.destination_s3_uri.DestinationS3Uri"
    ]
    """<p>The Amazon S3 location being used to capture the data.</p>"""
    dataset_format: NotRequired[
        "capo_sagemaker.types.monitoring_dataset_format.MonitoringDatasetFormat"
    ]
    """<p>The dataset format for your batch transform job.</p>"""
    local_path: NotRequired[
        "capo_sagemaker.types.processing_local_path.ProcessingLocalPath"
    ]
    """<p>Path to the filesystem where the batch transform data is available to the container.</p>"""
    s3_input_mode: NotRequired[
        "capo_sagemaker.types.processing_s3_input_mode.ProcessingS3InputMode"
    ]
    """<p>Whether the <code>Pipe</code> or <code>File</code> is used as the input mode for transferring data for the monitoring job. <code>Pipe</code> mode is recommended for large datasets. <code>File</code> mode is useful for small files that fit in memory. Defaults to <code>File</code>.</p>"""
    s3_data_distribution_type: NotRequired[
        "capo_sagemaker.types.processing_s3_data_distribution_type.ProcessingS3DataDistributionType"
    ]
    """<p>Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to <code>FullyReplicated</code> </p>"""
    features_attribute: NotRequired["capo_sagemaker.types.string.String"]
    """<p>The attributes of the input data that are the input features.</p>"""
    inference_attribute: NotRequired["capo_sagemaker.types.string.String"]
    """<p>The attribute of the input data that represents the ground truth label.</p>"""
    probability_attribute: NotRequired["capo_sagemaker.types.string.String"]
    """<p>In a classification problem, the attribute that represents the class probability.</p>"""
    probability_threshold_attribute: NotRequired[
        "capo_sagemaker.types.probability_threshold_attribute.ProbabilityThresholdAttribute"
    ]
    """<p>The threshold for the class probability to be evaluated as a positive result.</p>"""
    start_time_offset: NotRequired[
        "capo_sagemaker.types.monitoring_time_offset_string.MonitoringTimeOffsetString"
    ]
    """<p>If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html">Schedule Model Quality Monitoring Jobs</a>.</p>"""
    end_time_offset: NotRequired[
        "capo_sagemaker.types.monitoring_time_offset_string.MonitoringTimeOffsetString"
    ]
    """<p>If specified, monitoring jobs subtract this time from the end time. For information about using offsets for scheduling monitoring jobs, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html">Schedule Model Quality Monitoring Jobs</a>.</p>"""
    exclude_features_attribute: NotRequired[
        "capo_sagemaker.types.exclude_features_attribute.ExcludeFeaturesAttribute"
    ]
    """<p>The attributes of the input data to exclude from the analysis.</p>"""