Struct CreateModelCustomizationJobInput

#[non_exhaustive]
pub struct CreateModelCustomizationJobInput {

    pub job_name: Option<String>,
    pub custom_model_name: Option<String>,
    pub role_arn: Option<String>,
    pub client_request_token: Option<String>,
    pub base_model_identifier: Option<String>,
    pub customization_type: Option<CustomizationType>,
    pub custom_model_kms_key_id: Option<String>,
    pub job_tags: Option<Vec<Tag>>,
    pub custom_model_tags: Option<Vec<Tag>>,
    pub training_data_config: Option<TrainingDataConfig>,
    pub validation_data_config: Option<ValidationDataConfig>,
    pub output_data_config: Option<OutputDataConfig>,
    pub hyper_parameters: Option<HashMap<String, String>>,
    pub vpc_config: Option<VpcConfig>,
    pub customization_config: Option<CustomizationConfig>,
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

job_name: Option<String>

A name for the fine-tuning job.

custom_model_name: Option<String>

A name for the resulting custom model.

role_arn: Option<String>

The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. For example, during model training, Amazon Bedrock needs your permission to read input data from an S3 bucket, write model artifacts to an S3 bucket. To pass this role to Amazon Bedrock, the caller of this API must have the iam:PassRole permission.

client_request_token: Option<String>

A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see Ensuring idempotency.

base_model_identifier: Option<String>

Name of the base model.

customization_type: Option<CustomizationType>

The customization type.

custom_model_kms_key_id: Option<String>

The custom model is encrypted at rest using this key.

job_tags: Option<Vec<Tag>>

Tags to attach to the job.

custom_model_tags: Option<Vec<Tag>>

Tags to attach to the resulting custom model.

training_data_config: Option<TrainingDataConfig>

Information about the training dataset.

validation_data_config: Option<ValidationDataConfig>

Information about the validation dataset.

output_data_config: Option<OutputDataConfig>

S3 location for the output data.

hyper_parameters: Option<HashMap<String, String>>

Parameters related to tuning the model. For details on the format for different models, see Custom model hyperparameters.

vpc_config: Option<VpcConfig>

The configuration of the Virtual Private Cloud (VPC) that contains the resources that you're using for this job. For more information, see Protect your model customization jobs using a VPC.

customization_config: Option<CustomizationConfig>

The customization configuration for the model customization job.

Implementations

impl CreateModelCustomizationJobInput

pub fn job_name(&self) -> Option<&str>

A name for the fine-tuning job.

pub fn custom_model_name(&self) -> Option<&str>

A name for the resulting custom model.

pub fn role_arn(&self) -> Option<&str>

The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. For example, during model training, Amazon Bedrock needs your permission to read input data from an S3 bucket, write model artifacts to an S3 bucket. To pass this role to Amazon Bedrock, the caller of this API must have the iam:PassRole permission.

pub fn client_request_token(&self) -> Option<&str>

A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see Ensuring idempotency.

pub fn base_model_identifier(&self) -> Option<&str>

Name of the base model.

pub fn customization_type(&self) -> Option<&CustomizationType>

The customization type.

pub fn custom_model_kms_key_id(&self) -> Option<&str>

The custom model is encrypted at rest using this key.

pub fn job_tags(&self) -> &[Tag]

Tags to attach to the job.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .job_tags.is_none().

pub fn custom_model_tags(&self) -> &[Tag]

Tags to attach to the resulting custom model.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .custom_model_tags.is_none().

pub fn training_data_config(&self) -> Option<&TrainingDataConfig>

Information about the training dataset.

pub fn validation_data_config(&self) -> Option<&ValidationDataConfig>

Information about the validation dataset.

pub fn output_data_config(&self) -> Option<&OutputDataConfig>

S3 location for the output data.

pub fn hyper_parameters(&self) -> Option<&HashMap<String, String>>

Parameters related to tuning the model. For details on the format for different models, see Custom model hyperparameters.

pub fn vpc_config(&self) -> Option<&VpcConfig>

The configuration of the Virtual Private Cloud (VPC) that contains the resources that you're using for this job. For more information, see Protect your model customization jobs using a VPC.

pub fn customization_config(&self) -> Option<&CustomizationConfig>

The customization configuration for the model customization job.

impl CreateModelCustomizationJobInput

pub fn builder() -> CreateModelCustomizationJobInputBuilder

Creates a new builder-style object to manufacture CreateModelCustomizationJobInput.

Trait Implementations

impl Clone for CreateModelCustomizationJobInput

fn clone(&self) -> CreateModelCustomizationJobInput

Returns a duplicate of the value.

const fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateModelCustomizationJobInput

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for CreateModelCustomizationJobInput

fn eq(&self, other: &CreateModelCustomizationJobInput) -> bool

Tests for self and other values to be equal, and is used by ==.

const fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for CreateModelCustomizationJobInput