[−][src]Struct rusoto_sagemaker::CreateNotebookInstanceInput
Fields
accelerator_types: Option<Vec<String>>
A list of Elastic Inference (EI) instance types to associate with this notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
additional_code_repositories: Option<Vec<String>>
An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in AWS CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with Amazon SageMaker Notebook Instances.
default_code_repository: Option<String>
A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in AWS CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with Amazon SageMaker Notebook Instances.
direct_internet_access: Option<String>
Sets whether Amazon SageMaker provides internet access to the notebook instance. If you set this to Disabled
this notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker training and endpoint services unless your configure a NAT Gateway in your VPC.
For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to Disabled
only if you set a value for the SubnetId
parameter.
instance_type: String
The type of ML compute instance to launch for the notebook instance.
kms_key_id: Option<String>
The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the AWS Key Management Service Developer Guide.
lifecycle_config_name: Option<String>
The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
notebook_instance_name: String
The name of the new notebook instance.
role_arn: String
When you send any requests to AWS resources from the notebook instance, Amazon SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so Amazon SageMaker can perform these tasks. The policy must allow the Amazon SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see Amazon SageMaker Roles.
To be able to pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole
permission.
root_access: Option<String>
Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled
.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
security_group_ids: Option<Vec<String>>
The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
subnet_id: Option<String>
The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
volume_size_in_gb: Option<i64>
The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
Trait Implementations
impl Clone for CreateNotebookInstanceInput
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pub fn clone(&self) -> CreateNotebookInstanceInput
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pub fn clone_from(&mut self, source: &Self)
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impl Debug for CreateNotebookInstanceInput
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impl Default for CreateNotebookInstanceInput
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pub fn default() -> CreateNotebookInstanceInput
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impl PartialEq<CreateNotebookInstanceInput> for CreateNotebookInstanceInput
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pub fn eq(&self, other: &CreateNotebookInstanceInput) -> bool
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pub fn ne(&self, other: &CreateNotebookInstanceInput) -> bool
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impl Serialize for CreateNotebookInstanceInput
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pub fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
__S: Serializer,
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__S: Serializer,
impl StructuralPartialEq for CreateNotebookInstanceInput
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Auto Trait Implementations
impl RefUnwindSafe for CreateNotebookInstanceInput
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impl Send for CreateNotebookInstanceInput
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impl Sync for CreateNotebookInstanceInput
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impl Unpin for CreateNotebookInstanceInput
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impl UnwindSafe for CreateNotebookInstanceInput
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Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T
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impl<T> From<T> for T
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impl<T> Instrument for T
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pub fn instrument(self, span: Span) -> Instrumented<Self>
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pub fn in_current_span(self) -> Instrumented<Self>
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> Same<T> for T
type Output = T
Should always be Self
impl<T> ToOwned for T where
T: Clone,
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T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
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pub fn clone_into(&self, target: &mut T)
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impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,