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CreateInferenceSchedulerRequest

Source code in docs_src/capo_lookoutequipment/types/create_inference_scheduler_request.py
class CreateInferenceSchedulerRequest(TypedDict, closed=True):
    model_name: "capo_lookoutequipment.types.model_name.ModelName"
    """<p>The name of the previously trained machine learning model being used to create the inference scheduler. </p>"""
    inference_scheduler_name: (
        "capo_lookoutequipment.types.inference_scheduler_name.InferenceSchedulerName"
    )
    """<p>The name of the inference scheduler being created. </p>"""
    data_delay_offset_in_minutes: NotRequired[
        "capo_lookoutequipment.types.data_delay_offset_in_minutes.DataDelayOffsetInMinutes"
    ]
    """<p>The interval (in minutes) of planned delay at the start of each inference segment. For example, if inference is set to run every ten minutes, the delay is set to five minutes and the time is 09:08. The inference scheduler will wake up at the configured interval (which, without a delay configured, would be 09:10) plus the additional five minute delay time (so 09:15) to check your Amazon S3 bucket. The delay provides a buffer for you to upload data at the same frequency, so that you don't have to stop and restart the scheduler when uploading new data.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-inference-process.html">Understanding the inference process</a>.</p>"""
    data_upload_frequency: (
        "capo_lookoutequipment.types.data_upload_frequency.DataUploadFrequency"
    )
    """<p> How often data is uploaded to the source Amazon S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment runs inference on your data.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-inference-process.html">Understanding the inference process</a>.</p>"""
    data_input_configuration: "capo_lookoutequipment.types.inference_input_configuration.InferenceInputConfiguration"
    """<p>Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location. </p>"""
    data_output_configuration: "capo_lookoutequipment.types.inference_output_configuration.InferenceOutputConfiguration"
    """<p>Specifies configuration information for the output results for the inference scheduler, including the S3 location for the output. </p>"""
    role_arn: "capo_lookoutequipment.types.iam_role_arn.IamRoleArn"
    """<p>The Amazon Resource Name (ARN) of a role with permission to access the data source being used for the inference. </p>"""
    server_side_kms_key_id: NotRequired[
        "capo_lookoutequipment.types.name_or_arn.NameOrArn"
    ]
    """<p>Provides the identifier of the KMS key used to encrypt inference scheduler data by Amazon Lookout for Equipment. </p>"""
    client_token: "capo_lookoutequipment.types.idempotence_token.IdempotenceToken"
    """<p> A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. </p>"""
    tags: NotRequired["capo_lookoutequipment.types.tag_list.TagList"]
    """<p>Any tags associated with the inference scheduler. </p>"""

client_token instance-attribute

client_token: IdempotenceToken

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

data_delay_offset_in_minutes instance-attribute

data_delay_offset_in_minutes: NotRequired[DataDelayOffsetInMinutes]

The interval (in minutes) of planned delay at the start of each inference segment. For example, if inference is set to run every ten minutes, the delay is set to five minutes and the time is 09:08. The inference scheduler will wake up at the configured interval (which, without a delay configured, would be 09:10) plus the additional five minute delay time (so 09:15) to check your Amazon S3 bucket. The delay provides a buffer for you to upload data at the same frequency, so that you don't have to stop and restart the scheduler when uploading new data.

For more information, see Understanding the inference process.

data_input_configuration instance-attribute

data_input_configuration: InferenceInputConfiguration

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

data_output_configuration instance-attribute

data_output_configuration: InferenceOutputConfiguration

Specifies configuration information for the output results for the inference scheduler, including the S3 location for the output.

data_upload_frequency instance-attribute

data_upload_frequency: DataUploadFrequency

How often data is uploaded to the source Amazon S3 bucket for the input data. The value chosen is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment runs inference on your data.

For more information, see Understanding the inference process.

inference_scheduler_name instance-attribute

inference_scheduler_name: InferenceSchedulerName

The name of the inference scheduler being created.

model_name instance-attribute

model_name: ModelName

The name of the previously trained machine learning model being used to create the inference scheduler.

role_arn instance-attribute

role_arn: IamRoleArn

The Amazon Resource Name (ARN) of a role with permission to access the data source being used for the inference.

server_side_kms_key_id instance-attribute

server_side_kms_key_id: NotRequired[NameOrArn]

Provides the identifier of the KMS key used to encrypt inference scheduler data by Amazon Lookout for Equipment.

tags instance-attribute

tags: NotRequired[TagList]

Any tags associated with the inference scheduler.