2022/05/03 - Amazon SageMaker Service - 8 updated api methods
Changes SageMaker Autopilot adds new metrics for all candidate models generated by Autopilot experiments; RStudio on SageMaker now allows users to bring your own development environment in a custom image.
{'DefaultUserSettings': {'RSessionAppSettings': {'CustomImages': [{'AppImageConfigName': 'string',
'ImageName': 'string',
'ImageVersionNumber': 'integer'}],
'DefaultResourceSpec': {'InstanceType': 'system '
'| '
'ml.t3.micro '
'| '
'ml.t3.small '
'| '
'ml.t3.medium '
'| '
'ml.t3.large '
'| '
'ml.t3.xlarge '
'| '
'ml.t3.2xlarge '
'| '
'ml.m5.large '
'| '
'ml.m5.xlarge '
'| '
'ml.m5.2xlarge '
'| '
'ml.m5.4xlarge '
'| '
'ml.m5.8xlarge '
'| '
'ml.m5.12xlarge '
'| '
'ml.m5.16xlarge '
'| '
'ml.m5.24xlarge '
'| '
'ml.m5d.large '
'| '
'ml.m5d.xlarge '
'| '
'ml.m5d.2xlarge '
'| '
'ml.m5d.4xlarge '
'| '
'ml.m5d.8xlarge '
'| '
'ml.m5d.12xlarge '
'| '
'ml.m5d.16xlarge '
'| '
'ml.m5d.24xlarge '
'| '
'ml.c5.large '
'| '
'ml.c5.xlarge '
'| '
'ml.c5.2xlarge '
'| '
'ml.c5.4xlarge '
'| '
'ml.c5.9xlarge '
'| '
'ml.c5.12xlarge '
'| '
'ml.c5.18xlarge '
'| '
'ml.c5.24xlarge '
'| '
'ml.p3.2xlarge '
'| '
'ml.p3.8xlarge '
'| '
'ml.p3.16xlarge '
'| '
'ml.p3dn.24xlarge '
'| '
'ml.g4dn.xlarge '
'| '
'ml.g4dn.2xlarge '
'| '
'ml.g4dn.4xlarge '
'| '
'ml.g4dn.8xlarge '
'| '
'ml.g4dn.12xlarge '
'| '
'ml.g4dn.16xlarge '
'| '
'ml.r5.large '
'| '
'ml.r5.xlarge '
'| '
'ml.r5.2xlarge '
'| '
'ml.r5.4xlarge '
'| '
'ml.r5.8xlarge '
'| '
'ml.r5.12xlarge '
'| '
'ml.r5.16xlarge '
'| '
'ml.r5.24xlarge',
'LifecycleConfigArn': 'string',
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string'}}}}
Creates a Domain used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. An Amazon Web Services account is limited to one domain per region. Users within a domain can share notebook files and other artifacts with each other.
EFS storage
When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption .
VPC configuration
All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to Studio. The following options are available:
PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.
VpcOnly - All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway. When internet access is disabled, you won't be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
Warning
NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a SageMaker Studio app successfully.
For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC .
See also: AWS API Documentation
Request Syntax
client.create_domain(
DomainName='string',
AuthMode='SSO'|'IAM',
DefaultUserSettings={
'ExecutionRole': 'string',
'SecurityGroups': [
'string',
],
'SharingSettings': {
'NotebookOutputOption': 'Allowed'|'Disabled',
'S3OutputPath': 'string',
'S3KmsKeyId': 'string'
},
'JupyterServerAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'LifecycleConfigArns': [
'string',
]
},
'KernelGatewayAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
],
'LifecycleConfigArns': [
'string',
]
},
'TensorBoardAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
}
},
'RStudioServerProAppSettings': {
'AccessStatus': 'ENABLED'|'DISABLED',
'UserGroup': 'R_STUDIO_ADMIN'|'R_STUDIO_USER'
},
'RSessionAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
]
}
},
SubnetIds=[
'string',
],
VpcId='string',
Tags=[
{
'Key': 'string',
'Value': 'string'
},
],
AppNetworkAccessType='PublicInternetOnly'|'VpcOnly',
HomeEfsFileSystemKmsKeyId='string',
KmsKeyId='string',
AppSecurityGroupManagement='Service'|'Customer',
DomainSettings={
'SecurityGroupIds': [
'string',
],
'RStudioServerProDomainSettings': {
'DomainExecutionRoleArn': 'string',
'RStudioConnectUrl': 'string',
'RStudioPackageManagerUrl': 'string',
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
}
}
}
)
string
[REQUIRED]
A name for the domain.
string
[REQUIRED]
The mode of authentication that members use to access the domain.
dict
[REQUIRED]
The default settings to use to create a user profile when UserSettings isn't specified in the call to the CreateUserProfile API.
SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings , the values specified in CreateUserProfile take precedence over those specified in CreateDomain .
ExecutionRole (string) --
The execution role for the user.
SecurityGroups (list) --
The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly .
Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly .
Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
(string) --
SharingSettings (dict) --
Specifies options for sharing SageMaker Studio notebooks.
NotebookOutputOption (string) --
Whether to include the notebook cell output when sharing the notebook. The default is Disabled .
S3OutputPath (string) --
When NotebookOutputOption is Allowed , the Amazon S3 bucket used to store the shared notebook snapshots.
S3KmsKeyId (string) --
When NotebookOutputOption is Allowed , the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
JupyterServerAppSettings (dict) --
The Jupyter server's app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
KernelGatewayAppSettings (dict) --
The kernel gateway app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
Note
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a KernelGateway app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) -- [REQUIRED]
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) -- [REQUIRED]
The name of the AppImageConfig.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
TensorBoardAppSettings (dict) --
The TensorBoard app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
RStudioServerProAppSettings (dict) --
A collection of settings that configure user interaction with the RStudioServerPro app.
AccessStatus (string) --
Indicates whether the current user has access to the RStudioServerPro app.
UserGroup (string) --
The level of permissions that the user has within the RStudioServerPro app. This value defaults to User. The Admin value allows the user access to the RStudio Administrative Dashboard.
RSessionAppSettings (dict) --
A collection of settings that configure the RSessionGateway app.
DefaultResourceSpec (dict) --
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a RSession app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) -- [REQUIRED]
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) -- [REQUIRED]
The name of the AppImageConfig.
list
[REQUIRED]
The VPC subnets that Studio uses for communication.
(string) --
string
[REQUIRED]
The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
list
Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
Tags that you specify for the Domain are also added to all Apps that the Domain launches.
(dict) --
A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags .
For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources . For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy .
Key (string) -- [REQUIRED]
The tag key. Tag keys must be unique per resource.
Value (string) -- [REQUIRED]
The tag value.
string
Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly .
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access
VpcOnly - All Studio traffic is through the specified VPC and subnets
string
Use KmsKeyId .
string
SageMaker uses Amazon Web Services KMS to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.
string
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.
dict
A collection of Domain settings.
SecurityGroupIds (list) --
The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.
(string) --
RStudioServerProDomainSettings (dict) --
A collection of settings that configure the RStudioServerPro Domain-level app.
DomainExecutionRoleArn (string) -- [REQUIRED]
The ARN of the execution role for the RStudioServerPro Domain-level app.
RStudioConnectUrl (string) --
A URL pointing to an RStudio Connect server.
RStudioPackageManagerUrl (string) --
A URL pointing to an RStudio Package Manager server.
DefaultResourceSpec (dict) --
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
dict
Response Syntax
{
'DomainArn': 'string',
'Url': 'string'
}
Response Structure
(dict) --
DomainArn (string) --
The Amazon Resource Name (ARN) of the created domain.
Url (string) --
The URL to the created domain.
{'UserSettings': {'RSessionAppSettings': {'CustomImages': [{'AppImageConfigName': 'string',
'ImageName': 'string',
'ImageVersionNumber': 'integer'}],
'DefaultResourceSpec': {'InstanceType': 'system '
'| '
'ml.t3.micro '
'| '
'ml.t3.small '
'| '
'ml.t3.medium '
'| '
'ml.t3.large '
'| '
'ml.t3.xlarge '
'| '
'ml.t3.2xlarge '
'| '
'ml.m5.large '
'| '
'ml.m5.xlarge '
'| '
'ml.m5.2xlarge '
'| '
'ml.m5.4xlarge '
'| '
'ml.m5.8xlarge '
'| '
'ml.m5.12xlarge '
'| '
'ml.m5.16xlarge '
'| '
'ml.m5.24xlarge '
'| '
'ml.m5d.large '
'| '
'ml.m5d.xlarge '
'| '
'ml.m5d.2xlarge '
'| '
'ml.m5d.4xlarge '
'| '
'ml.m5d.8xlarge '
'| '
'ml.m5d.12xlarge '
'| '
'ml.m5d.16xlarge '
'| '
'ml.m5d.24xlarge '
'| '
'ml.c5.large '
'| '
'ml.c5.xlarge '
'| '
'ml.c5.2xlarge '
'| '
'ml.c5.4xlarge '
'| '
'ml.c5.9xlarge '
'| '
'ml.c5.12xlarge '
'| '
'ml.c5.18xlarge '
'| '
'ml.c5.24xlarge '
'| '
'ml.p3.2xlarge '
'| '
'ml.p3.8xlarge '
'| '
'ml.p3.16xlarge '
'| '
'ml.p3dn.24xlarge '
'| '
'ml.g4dn.xlarge '
'| '
'ml.g4dn.2xlarge '
'| '
'ml.g4dn.4xlarge '
'| '
'ml.g4dn.8xlarge '
'| '
'ml.g4dn.12xlarge '
'| '
'ml.g4dn.16xlarge '
'| '
'ml.r5.large '
'| '
'ml.r5.xlarge '
'| '
'ml.r5.2xlarge '
'| '
'ml.r5.4xlarge '
'| '
'ml.r5.8xlarge '
'| '
'ml.r5.12xlarge '
'| '
'ml.r5.16xlarge '
'| '
'ml.r5.24xlarge',
'LifecycleConfigArn': 'string',
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string'}}}}
Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System (EFS) home directory.
See also: AWS API Documentation
Request Syntax
client.create_user_profile(
DomainId='string',
UserProfileName='string',
SingleSignOnUserIdentifier='string',
SingleSignOnUserValue='string',
Tags=[
{
'Key': 'string',
'Value': 'string'
},
],
UserSettings={
'ExecutionRole': 'string',
'SecurityGroups': [
'string',
],
'SharingSettings': {
'NotebookOutputOption': 'Allowed'|'Disabled',
'S3OutputPath': 'string',
'S3KmsKeyId': 'string'
},
'JupyterServerAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'LifecycleConfigArns': [
'string',
]
},
'KernelGatewayAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
],
'LifecycleConfigArns': [
'string',
]
},
'TensorBoardAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
}
},
'RStudioServerProAppSettings': {
'AccessStatus': 'ENABLED'|'DISABLED',
'UserGroup': 'R_STUDIO_ADMIN'|'R_STUDIO_USER'
},
'RSessionAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
]
}
}
)
string
[REQUIRED]
The ID of the associated Domain.
string
[REQUIRED]
A name for the UserProfile. This value is not case sensitive.
string
A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is "UserName". If the Domain's AuthMode is SSO, this field is required. If the Domain's AuthMode is not SSO, this field cannot be specified.
string
The username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain's AuthMode is SSO, this field is required, and must match a valid username of a user in your directory. If the Domain's AuthMode is not SSO, this field cannot be specified.
list
Each tag consists of a key and an optional value. Tag keys must be unique per resource.
Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.
(dict) --
A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags .
For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources . For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy .
Key (string) -- [REQUIRED]
The tag key. Tag keys must be unique per resource.
Value (string) -- [REQUIRED]
The tag value.
dict
A collection of settings.
ExecutionRole (string) --
The execution role for the user.
SecurityGroups (list) --
The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly .
Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly .
Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
(string) --
SharingSettings (dict) --
Specifies options for sharing SageMaker Studio notebooks.
NotebookOutputOption (string) --
Whether to include the notebook cell output when sharing the notebook. The default is Disabled .
S3OutputPath (string) --
When NotebookOutputOption is Allowed , the Amazon S3 bucket used to store the shared notebook snapshots.
S3KmsKeyId (string) --
When NotebookOutputOption is Allowed , the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
JupyterServerAppSettings (dict) --
The Jupyter server's app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
KernelGatewayAppSettings (dict) --
The kernel gateway app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
Note
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a KernelGateway app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) -- [REQUIRED]
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) -- [REQUIRED]
The name of the AppImageConfig.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
TensorBoardAppSettings (dict) --
The TensorBoard app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
RStudioServerProAppSettings (dict) --
A collection of settings that configure user interaction with the RStudioServerPro app.
AccessStatus (string) --
Indicates whether the current user has access to the RStudioServerPro app.
UserGroup (string) --
The level of permissions that the user has within the RStudioServerPro app. This value defaults to User. The Admin value allows the user access to the RStudio Administrative Dashboard.
RSessionAppSettings (dict) --
A collection of settings that configure the RSessionGateway app.
DefaultResourceSpec (dict) --
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a RSession app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) -- [REQUIRED]
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) -- [REQUIRED]
The name of the AppImageConfig.
dict
Response Syntax
{
'UserProfileArn': 'string'
}
Response Structure
(dict) --
UserProfileArn (string) --
The user profile Amazon Resource Name (ARN).
{'BestCandidate': {'CandidateProperties': {'CandidateMetrics': {'StandardMetricName': 'Accuracy '
'| '
'MSE '
'| '
'F1 '
'| '
'F1macro '
'| '
'AUC '
'| '
'RMSE '
'| '
'MAE '
'| '
'R2 '
'| '
'BalancedAccuracy '
'| '
'Precision '
'| '
'PrecisionMacro '
'| '
'Recall '
'| '
'RecallMacro '
'| '
'LogLoss'}}}}
Returns information about an Amazon SageMaker AutoML job.
See also: AWS API Documentation
Request Syntax
client.describe_auto_ml_job(
AutoMLJobName='string'
)
string
[REQUIRED]
Requests information about an AutoML job using its unique name.
dict
Response Syntax
{
'AutoMLJobName': 'string',
'AutoMLJobArn': 'string',
'InputDataConfig': [
{
'DataSource': {
'S3DataSource': {
'S3DataType': 'ManifestFile'|'S3Prefix',
'S3Uri': 'string'
}
},
'CompressionType': 'None'|'Gzip',
'TargetAttributeName': 'string',
'ContentType': 'string',
'ChannelType': 'training'|'validation'
},
],
'OutputDataConfig': {
'KmsKeyId': 'string',
'S3OutputPath': 'string'
},
'RoleArn': 'string',
'AutoMLJobObjective': {
'MetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC'
},
'ProblemType': 'BinaryClassification'|'MulticlassClassification'|'Regression',
'AutoMLJobConfig': {
'CompletionCriteria': {
'MaxCandidates': 123,
'MaxRuntimePerTrainingJobInSeconds': 123,
'MaxAutoMLJobRuntimeInSeconds': 123
},
'SecurityConfig': {
'VolumeKmsKeyId': 'string',
'EnableInterContainerTrafficEncryption': True|False,
'VpcConfig': {
'SecurityGroupIds': [
'string',
],
'Subnets': [
'string',
]
}
},
'DataSplitConfig': {
'ValidationFraction': ...
}
},
'CreationTime': datetime(2015, 1, 1),
'EndTime': datetime(2015, 1, 1),
'LastModifiedTime': datetime(2015, 1, 1),
'FailureReason': 'string',
'PartialFailureReasons': [
{
'PartialFailureMessage': 'string'
},
],
'BestCandidate': {
'CandidateName': 'string',
'FinalAutoMLJobObjectiveMetric': {
'Type': 'Maximize'|'Minimize',
'MetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC',
'Value': ...
},
'ObjectiveStatus': 'Succeeded'|'Pending'|'Failed',
'CandidateSteps': [
{
'CandidateStepType': 'AWS::SageMaker::TrainingJob'|'AWS::SageMaker::TransformJob'|'AWS::SageMaker::ProcessingJob',
'CandidateStepArn': 'string',
'CandidateStepName': 'string'
},
],
'CandidateStatus': 'Completed'|'InProgress'|'Failed'|'Stopped'|'Stopping',
'InferenceContainers': [
{
'Image': 'string',
'ModelDataUrl': 'string',
'Environment': {
'string': 'string'
}
},
],
'CreationTime': datetime(2015, 1, 1),
'EndTime': datetime(2015, 1, 1),
'LastModifiedTime': datetime(2015, 1, 1),
'FailureReason': 'string',
'CandidateProperties': {
'CandidateArtifactLocations': {
'Explainability': 'string',
'ModelInsights': 'string'
},
'CandidateMetrics': [
{
'MetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC',
'Value': ...,
'Set': 'Train'|'Validation'|'Test',
'StandardMetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC'|'RMSE'|'MAE'|'R2'|'BalancedAccuracy'|'Precision'|'PrecisionMacro'|'Recall'|'RecallMacro'|'LogLoss'
},
]
}
},
'AutoMLJobStatus': 'Completed'|'InProgress'|'Failed'|'Stopped'|'Stopping',
'AutoMLJobSecondaryStatus': 'Starting'|'AnalyzingData'|'FeatureEngineering'|'ModelTuning'|'MaxCandidatesReached'|'Failed'|'Stopped'|'MaxAutoMLJobRuntimeReached'|'Stopping'|'CandidateDefinitionsGenerated'|'GeneratingExplainabilityReport'|'Completed'|'ExplainabilityError'|'DeployingModel'|'ModelDeploymentError'|'GeneratingModelInsightsReport'|'ModelInsightsError',
'GenerateCandidateDefinitionsOnly': True|False,
'AutoMLJobArtifacts': {
'CandidateDefinitionNotebookLocation': 'string',
'DataExplorationNotebookLocation': 'string'
},
'ResolvedAttributes': {
'AutoMLJobObjective': {
'MetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC'
},
'ProblemType': 'BinaryClassification'|'MulticlassClassification'|'Regression',
'CompletionCriteria': {
'MaxCandidates': 123,
'MaxRuntimePerTrainingJobInSeconds': 123,
'MaxAutoMLJobRuntimeInSeconds': 123
}
},
'ModelDeployConfig': {
'AutoGenerateEndpointName': True|False,
'EndpointName': 'string'
},
'ModelDeployResult': {
'EndpointName': 'string'
}
}
Response Structure
(dict) --
AutoMLJobName (string) --
Returns the name of the AutoML job.
AutoMLJobArn (string) --
Returns the ARN of the AutoML job.
InputDataConfig (list) --
Returns the input data configuration for the AutoML job..
(dict) --
A channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see .
Note
A validation dataset must contain the same headers as the training dataset.
DataSource (dict) --
The data source for an AutoML channel.
S3DataSource (dict) --
The Amazon S3 location of the input data.
Note
The input data must be in CSV format and contain at least 500 rows.
S3DataType (string) --
The data type.
S3Uri (string) --
The URL to the Amazon S3 data source.
CompressionType (string) --
You can use Gzip or None . The default value is None .
TargetAttributeName (string) --
The name of the target variable in supervised learning, usually represented by 'y'.
ContentType (string) --
The content type of the data from the input source. You can use text/csv;header=present or x-application/vnd.amazon+parquet . The default value is text/csv;header=present .
ChannelType (string) --
The channel type (optional) is an enum string. The default value is training . Channels for training and validation must share the same ContentType and TargetAttributeName .
OutputDataConfig (dict) --
Returns the job's output data config.
KmsKeyId (string) --
The Amazon Web Services KMS encryption key ID.
S3OutputPath (string) --
The Amazon S3 output path. Must be 128 characters or less.
RoleArn (string) --
The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.
AutoMLJobObjective (dict) --
Returns the job's objective.
MetricName (string) --
The name of the objective metric used to measure the predictive quality of a machine learning system. This metric is optimized during training to provide the best estimate for model parameter values from data.
Here are the options:
MSE : The mean squared error (MSE) is the average of the squared differences between the predicted and actual values. It is used for regression. MSE values are always positive: the better a model is at predicting the actual values, the smaller the MSE value is. When the data contains outliers, they tend to dominate the MSE, which might cause subpar prediction performance.
Accuracy : The ratio of the number of correctly classified items to the total number of (correctly and incorrectly) classified items. It is used for binary and multiclass classification. It measures how close the predicted class values are to the actual values. Accuracy values vary between zero and one: one indicates perfect accuracy and zero indicates perfect inaccuracy.
F1 : The F1 score is the harmonic mean of the precision and recall. It is used for binary classification into classes traditionally referred to as positive and negative. Predictions are said to be true when they match their actual (correct) class and false when they do not. Precision is the ratio of the true positive predictions to all positive predictions (including the false positives) in a data set and measures the quality of the prediction when it predicts the positive class. Recall (or sensitivity) is the ratio of the true positive predictions to all actual positive instances and measures how completely a model predicts the actual class members in a data set. The standard F1 score weighs precision and recall equally. But which metric is paramount typically depends on specific aspects of a problem. F1 scores vary between zero and one: one indicates the best possible performance and zero the worst.
AUC : The area under the curve (AUC) metric is used to compare and evaluate binary classification by algorithms such as logistic regression that return probabilities. A threshold is needed to map the probabilities into classifications. The relevant curve is the receiver operating characteristic curve that plots the true positive rate (TPR) of predictions (or recall) against the false positive rate (FPR) as a function of the threshold value, above which a prediction is considered positive. Increasing the threshold results in fewer false positives but more false negatives. AUC is the area under this receiver operating characteristic curve and so provides an aggregated measure of the model performance across all possible classification thresholds. The AUC score can also be interpreted as the probability that a randomly selected positive data point is more likely to be predicted positive than a randomly selected negative example. AUC scores vary between zero and one: a score of one indicates perfect accuracy and a score of one half indicates that the prediction is not better than a random classifier. Values under one half predict less accurately than a random predictor. But such consistently bad predictors can simply be inverted to obtain better than random predictors.
F1macro : The F1macro score applies F1 scoring to multiclass classification. In this context, you have multiple classes to predict. You just calculate the precision and recall for each class as you did for the positive class in binary classification. Then, use these values to calculate the F1 score for each class and average them to obtain the F1macro score. F1macro scores vary between zero and one: one indicates the best possible performance and zero the worst.
If you do not specify a metric explicitly, the default behavior is to automatically use:
MSE : for regression.
F1 : for binary classification
Accuracy : for multiclass classification.
ProblemType (string) --
Returns the job's problem type.
AutoMLJobConfig (dict) --
Returns the configuration for the AutoML job.
CompletionCriteria (dict) --
How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
MaxCandidates (integer) --
The maximum number of times a training job is allowed to run.
MaxRuntimePerTrainingJobInSeconds (integer) --
The maximum time, in seconds, that each training job is allowed to run as part of a hyperparameter tuning job. For more information, see the used by the action.
MaxAutoMLJobRuntimeInSeconds (integer) --
The maximum runtime, in seconds, an AutoML job has to complete.
If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, will not be completed.
SecurityConfig (dict) --
The security configuration for traffic encryption or Amazon VPC settings.
VolumeKmsKeyId (string) --
The key used to encrypt stored data.
EnableInterContainerTrafficEncryption (boolean) --
Whether to use traffic encryption between the container layers.
VpcConfig (dict) --
The VPC configuration.
SecurityGroupIds (list) --
The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
(string) --
Subnets (list) --
The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones .
(string) --
DataSplitConfig (dict) --
The configuration for splitting the input training dataset.
Type: AutoMLDataSplitConfig
ValidationFraction (float) --
The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values can range from 0 to 1. We recommend setting this value to be less than 0.5.
CreationTime (datetime) --
Returns the creation time of the AutoML job.
EndTime (datetime) --
Returns the end time of the AutoML job.
LastModifiedTime (datetime) --
Returns the job's last modified time.
FailureReason (string) --
Returns the failure reason for an AutoML job, when applicable.
PartialFailureReasons (list) --
Returns a list of reasons for partial failures within an AutoML job.
(dict) --
The reason for a partial failure of an AutoML job.
PartialFailureMessage (string) --
The message containing the reason for a partial failure of an AutoML job.
BestCandidate (dict) --
Returns the job's best AutoMLCandidate .
CandidateName (string) --
The name of the candidate.
FinalAutoMLJobObjectiveMetric (dict) --
The best candidate result from an AutoML training job.
Type (string) --
The type of metric with the best result.
MetricName (string) --
The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName .
Value (float) --
The value of the metric with the best result.
ObjectiveStatus (string) --
The objective's status.
CandidateSteps (list) --
Information about the candidate's steps.
(dict) --
Information about the steps for a candidate and what step it is working on.
CandidateStepType (string) --
Whether the candidate is at the transform, training, or processing step.
CandidateStepArn (string) --
The ARN for the candidate's step.
CandidateStepName (string) --
The name for the candidate's step.
CandidateStatus (string) --
The candidate's status.
InferenceContainers (list) --
Information about the inference container definitions.
(dict) --
A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see .
Image (string) --
The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see .
ModelDataUrl (string) --
The location of the model artifacts. For more information, see .
Environment (dict) --
The environment variables to set in the container. For more information, see .
(string) --
(string) --
CreationTime (datetime) --
The creation time.
EndTime (datetime) --
The end time.
LastModifiedTime (datetime) --
The last modified time.
FailureReason (string) --
The failure reason.
CandidateProperties (dict) --
The properties of an AutoML candidate job.
CandidateArtifactLocations (dict) --
The Amazon S3 prefix to the artifacts generated for an AutoML candidate.
Explainability (string) --
The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate.
ModelInsights (string) --
The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate.
CandidateMetrics (list) --
Information about the candidate metrics for an AutoML job.
(dict) --
Information about the metric for a candidate produced by an AutoML job.
MetricName (string) --
The name of the metric.
Value (float) --
The value of the metric.
Set (string) --
The dataset split from which the AutoML job produced the metric.
StandardMetricName (string) --
The name of the standard metric.
AutoMLJobStatus (string) --
Returns the status of the AutoML job.
AutoMLJobSecondaryStatus (string) --
Returns the secondary status of the AutoML job.
GenerateCandidateDefinitionsOnly (boolean) --
Indicates whether the output for an AutoML job generates candidate definitions only.
AutoMLJobArtifacts (dict) --
Returns information on the job's artifacts found in AutoMLJobArtifacts .
CandidateDefinitionNotebookLocation (string) --
The URL of the notebook location.
DataExplorationNotebookLocation (string) --
The URL of the notebook location.
ResolvedAttributes (dict) --
This contains ProblemType , AutoMLJobObjective , and CompletionCriteria . If you do not provide these values, they are auto-inferred. If you do provide them, the values used are the ones you provide.
AutoMLJobObjective (dict) --
Specifies a metric to minimize or maximize as the objective of a job.
MetricName (string) --
The name of the objective metric used to measure the predictive quality of a machine learning system. This metric is optimized during training to provide the best estimate for model parameter values from data.
Here are the options:
MSE : The mean squared error (MSE) is the average of the squared differences between the predicted and actual values. It is used for regression. MSE values are always positive: the better a model is at predicting the actual values, the smaller the MSE value is. When the data contains outliers, they tend to dominate the MSE, which might cause subpar prediction performance.
Accuracy : The ratio of the number of correctly classified items to the total number of (correctly and incorrectly) classified items. It is used for binary and multiclass classification. It measures how close the predicted class values are to the actual values. Accuracy values vary between zero and one: one indicates perfect accuracy and zero indicates perfect inaccuracy.
F1 : The F1 score is the harmonic mean of the precision and recall. It is used for binary classification into classes traditionally referred to as positive and negative. Predictions are said to be true when they match their actual (correct) class and false when they do not. Precision is the ratio of the true positive predictions to all positive predictions (including the false positives) in a data set and measures the quality of the prediction when it predicts the positive class. Recall (or sensitivity) is the ratio of the true positive predictions to all actual positive instances and measures how completely a model predicts the actual class members in a data set. The standard F1 score weighs precision and recall equally. But which metric is paramount typically depends on specific aspects of a problem. F1 scores vary between zero and one: one indicates the best possible performance and zero the worst.
AUC : The area under the curve (AUC) metric is used to compare and evaluate binary classification by algorithms such as logistic regression that return probabilities. A threshold is needed to map the probabilities into classifications. The relevant curve is the receiver operating characteristic curve that plots the true positive rate (TPR) of predictions (or recall) against the false positive rate (FPR) as a function of the threshold value, above which a prediction is considered positive. Increasing the threshold results in fewer false positives but more false negatives. AUC is the area under this receiver operating characteristic curve and so provides an aggregated measure of the model performance across all possible classification thresholds. The AUC score can also be interpreted as the probability that a randomly selected positive data point is more likely to be predicted positive than a randomly selected negative example. AUC scores vary between zero and one: a score of one indicates perfect accuracy and a score of one half indicates that the prediction is not better than a random classifier. Values under one half predict less accurately than a random predictor. But such consistently bad predictors can simply be inverted to obtain better than random predictors.
F1macro : The F1macro score applies F1 scoring to multiclass classification. In this context, you have multiple classes to predict. You just calculate the precision and recall for each class as you did for the positive class in binary classification. Then, use these values to calculate the F1 score for each class and average them to obtain the F1macro score. F1macro scores vary between zero and one: one indicates the best possible performance and zero the worst.
If you do not specify a metric explicitly, the default behavior is to automatically use:
MSE : for regression.
F1 : for binary classification
Accuracy : for multiclass classification.
ProblemType (string) --
The problem type.
CompletionCriteria (dict) --
How long a job is allowed to run, or how many candidates a job is allowed to generate.
MaxCandidates (integer) --
The maximum number of times a training job is allowed to run.
MaxRuntimePerTrainingJobInSeconds (integer) --
The maximum time, in seconds, that each training job is allowed to run as part of a hyperparameter tuning job. For more information, see the used by the action.
MaxAutoMLJobRuntimeInSeconds (integer) --
The maximum runtime, in seconds, an AutoML job has to complete.
If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, will not be completed.
ModelDeployConfig (dict) --
Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
AutoGenerateEndpointName (boolean) --
Set to True to automatically generate an endpoint name for a one-click Autopilot model deployment; set to False otherwise. The default value is False .
Note
If you set AutoGenerateEndpointName to True , do not specify the EndpointName ; otherwise a 400 error is thrown.
EndpointName (string) --
Specifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically.
Note
Specify the EndpointName if and only if you set AutoGenerateEndpointName to False ; otherwise a 400 error is thrown.
ModelDeployResult (dict) --
Provides information about endpoint for the model deployment.
EndpointName (string) --
The name of the endpoint to which the model has been deployed.
Note
If model deployment fails, this field is omitted from the response.
{'DefaultUserSettings': {'RSessionAppSettings': {'CustomImages': [{'AppImageConfigName': 'string',
'ImageName': 'string',
'ImageVersionNumber': 'integer'}],
'DefaultResourceSpec': {'InstanceType': 'system '
'| '
'ml.t3.micro '
'| '
'ml.t3.small '
'| '
'ml.t3.medium '
'| '
'ml.t3.large '
'| '
'ml.t3.xlarge '
'| '
'ml.t3.2xlarge '
'| '
'ml.m5.large '
'| '
'ml.m5.xlarge '
'| '
'ml.m5.2xlarge '
'| '
'ml.m5.4xlarge '
'| '
'ml.m5.8xlarge '
'| '
'ml.m5.12xlarge '
'| '
'ml.m5.16xlarge '
'| '
'ml.m5.24xlarge '
'| '
'ml.m5d.large '
'| '
'ml.m5d.xlarge '
'| '
'ml.m5d.2xlarge '
'| '
'ml.m5d.4xlarge '
'| '
'ml.m5d.8xlarge '
'| '
'ml.m5d.12xlarge '
'| '
'ml.m5d.16xlarge '
'| '
'ml.m5d.24xlarge '
'| '
'ml.c5.large '
'| '
'ml.c5.xlarge '
'| '
'ml.c5.2xlarge '
'| '
'ml.c5.4xlarge '
'| '
'ml.c5.9xlarge '
'| '
'ml.c5.12xlarge '
'| '
'ml.c5.18xlarge '
'| '
'ml.c5.24xlarge '
'| '
'ml.p3.2xlarge '
'| '
'ml.p3.8xlarge '
'| '
'ml.p3.16xlarge '
'| '
'ml.p3dn.24xlarge '
'| '
'ml.g4dn.xlarge '
'| '
'ml.g4dn.2xlarge '
'| '
'ml.g4dn.4xlarge '
'| '
'ml.g4dn.8xlarge '
'| '
'ml.g4dn.12xlarge '
'| '
'ml.g4dn.16xlarge '
'| '
'ml.r5.large '
'| '
'ml.r5.xlarge '
'| '
'ml.r5.2xlarge '
'| '
'ml.r5.4xlarge '
'| '
'ml.r5.8xlarge '
'| '
'ml.r5.12xlarge '
'| '
'ml.r5.16xlarge '
'| '
'ml.r5.24xlarge',
'LifecycleConfigArn': 'string',
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string'}}}}
The description of the domain.
See also: AWS API Documentation
Request Syntax
client.describe_domain(
DomainId='string'
)
string
[REQUIRED]
The domain ID.
dict
Response Syntax
{
'DomainArn': 'string',
'DomainId': 'string',
'DomainName': 'string',
'HomeEfsFileSystemId': 'string',
'SingleSignOnManagedApplicationInstanceId': 'string',
'Status': 'Deleting'|'Failed'|'InService'|'Pending'|'Updating'|'Update_Failed'|'Delete_Failed',
'CreationTime': datetime(2015, 1, 1),
'LastModifiedTime': datetime(2015, 1, 1),
'FailureReason': 'string',
'AuthMode': 'SSO'|'IAM',
'DefaultUserSettings': {
'ExecutionRole': 'string',
'SecurityGroups': [
'string',
],
'SharingSettings': {
'NotebookOutputOption': 'Allowed'|'Disabled',
'S3OutputPath': 'string',
'S3KmsKeyId': 'string'
},
'JupyterServerAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'LifecycleConfigArns': [
'string',
]
},
'KernelGatewayAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
],
'LifecycleConfigArns': [
'string',
]
},
'TensorBoardAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
}
},
'RStudioServerProAppSettings': {
'AccessStatus': 'ENABLED'|'DISABLED',
'UserGroup': 'R_STUDIO_ADMIN'|'R_STUDIO_USER'
},
'RSessionAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
]
}
},
'AppNetworkAccessType': 'PublicInternetOnly'|'VpcOnly',
'HomeEfsFileSystemKmsKeyId': 'string',
'SubnetIds': [
'string',
],
'Url': 'string',
'VpcId': 'string',
'KmsKeyId': 'string',
'DomainSettings': {
'SecurityGroupIds': [
'string',
],
'RStudioServerProDomainSettings': {
'DomainExecutionRoleArn': 'string',
'RStudioConnectUrl': 'string',
'RStudioPackageManagerUrl': 'string',
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
}
}
},
'AppSecurityGroupManagement': 'Service'|'Customer',
'SecurityGroupIdForDomainBoundary': 'string'
}
Response Structure
(dict) --
DomainArn (string) --
The domain's Amazon Resource Name (ARN).
DomainId (string) --
The domain ID.
DomainName (string) --
The domain name.
HomeEfsFileSystemId (string) --
The ID of the Amazon Elastic File System (EFS) managed by this Domain.
SingleSignOnManagedApplicationInstanceId (string) --
The SSO managed application instance ID.
Status (string) --
The status.
CreationTime (datetime) --
The creation time.
LastModifiedTime (datetime) --
The last modified time.
FailureReason (string) --
The failure reason.
AuthMode (string) --
The domain's authentication mode.
DefaultUserSettings (dict) --
Settings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile.
ExecutionRole (string) --
The execution role for the user.
SecurityGroups (list) --
The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly .
Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly .
Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
(string) --
SharingSettings (dict) --
Specifies options for sharing SageMaker Studio notebooks.
NotebookOutputOption (string) --
Whether to include the notebook cell output when sharing the notebook. The default is Disabled .
S3OutputPath (string) --
When NotebookOutputOption is Allowed , the Amazon S3 bucket used to store the shared notebook snapshots.
S3KmsKeyId (string) --
When NotebookOutputOption is Allowed , the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
JupyterServerAppSettings (dict) --
The Jupyter server's app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
KernelGatewayAppSettings (dict) --
The kernel gateway app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
Note
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a KernelGateway app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) --
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) --
The name of the AppImageConfig.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
TensorBoardAppSettings (dict) --
The TensorBoard app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
RStudioServerProAppSettings (dict) --
A collection of settings that configure user interaction with the RStudioServerPro app.
AccessStatus (string) --
Indicates whether the current user has access to the RStudioServerPro app.
UserGroup (string) --
The level of permissions that the user has within the RStudioServerPro app. This value defaults to User. The Admin value allows the user access to the RStudio Administrative Dashboard.
RSessionAppSettings (dict) --
A collection of settings that configure the RSessionGateway app.
DefaultResourceSpec (dict) --
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a RSession app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) --
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) --
The name of the AppImageConfig.
AppNetworkAccessType (string) --
Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly .
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access
VpcOnly - All Studio traffic is through the specified VPC and subnets
HomeEfsFileSystemKmsKeyId (string) --
Use KmsKeyId .
SubnetIds (list) --
The VPC subnets that Studio uses for communication.
(string) --
Url (string) --
The domain's URL.
VpcId (string) --
The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
KmsKeyId (string) --
The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.
DomainSettings (dict) --
A collection of Domain settings.
SecurityGroupIds (list) --
The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.
(string) --
RStudioServerProDomainSettings (dict) --
A collection of settings that configure the RStudioServerPro Domain-level app.
DomainExecutionRoleArn (string) --
The ARN of the execution role for the RStudioServerPro Domain-level app.
RStudioConnectUrl (string) --
A URL pointing to an RStudio Connect server.
RStudioPackageManagerUrl (string) --
A URL pointing to an RStudio Package Manager server.
DefaultResourceSpec (dict) --
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
AppSecurityGroupManagement (string) --
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.
SecurityGroupIdForDomainBoundary (string) --
The ID of the security group that authorizes traffic between the RSessionGateway apps and the RStudioServerPro app.
{'UserSettings': {'RSessionAppSettings': {'CustomImages': [{'AppImageConfigName': 'string',
'ImageName': 'string',
'ImageVersionNumber': 'integer'}],
'DefaultResourceSpec': {'InstanceType': 'system '
'| '
'ml.t3.micro '
'| '
'ml.t3.small '
'| '
'ml.t3.medium '
'| '
'ml.t3.large '
'| '
'ml.t3.xlarge '
'| '
'ml.t3.2xlarge '
'| '
'ml.m5.large '
'| '
'ml.m5.xlarge '
'| '
'ml.m5.2xlarge '
'| '
'ml.m5.4xlarge '
'| '
'ml.m5.8xlarge '
'| '
'ml.m5.12xlarge '
'| '
'ml.m5.16xlarge '
'| '
'ml.m5.24xlarge '
'| '
'ml.m5d.large '
'| '
'ml.m5d.xlarge '
'| '
'ml.m5d.2xlarge '
'| '
'ml.m5d.4xlarge '
'| '
'ml.m5d.8xlarge '
'| '
'ml.m5d.12xlarge '
'| '
'ml.m5d.16xlarge '
'| '
'ml.m5d.24xlarge '
'| '
'ml.c5.large '
'| '
'ml.c5.xlarge '
'| '
'ml.c5.2xlarge '
'| '
'ml.c5.4xlarge '
'| '
'ml.c5.9xlarge '
'| '
'ml.c5.12xlarge '
'| '
'ml.c5.18xlarge '
'| '
'ml.c5.24xlarge '
'| '
'ml.p3.2xlarge '
'| '
'ml.p3.8xlarge '
'| '
'ml.p3.16xlarge '
'| '
'ml.p3dn.24xlarge '
'| '
'ml.g4dn.xlarge '
'| '
'ml.g4dn.2xlarge '
'| '
'ml.g4dn.4xlarge '
'| '
'ml.g4dn.8xlarge '
'| '
'ml.g4dn.12xlarge '
'| '
'ml.g4dn.16xlarge '
'| '
'ml.r5.large '
'| '
'ml.r5.xlarge '
'| '
'ml.r5.2xlarge '
'| '
'ml.r5.4xlarge '
'| '
'ml.r5.8xlarge '
'| '
'ml.r5.12xlarge '
'| '
'ml.r5.16xlarge '
'| '
'ml.r5.24xlarge',
'LifecycleConfigArn': 'string',
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string'}}}}
Describes a user profile. For more information, see CreateUserProfile .
See also: AWS API Documentation
Request Syntax
client.describe_user_profile(
DomainId='string',
UserProfileName='string'
)
string
[REQUIRED]
The domain ID.
string
[REQUIRED]
The user profile name. This value is not case sensitive.
dict
Response Syntax
{
'DomainId': 'string',
'UserProfileArn': 'string',
'UserProfileName': 'string',
'HomeEfsFileSystemUid': 'string',
'Status': 'Deleting'|'Failed'|'InService'|'Pending'|'Updating'|'Update_Failed'|'Delete_Failed',
'LastModifiedTime': datetime(2015, 1, 1),
'CreationTime': datetime(2015, 1, 1),
'FailureReason': 'string',
'SingleSignOnUserIdentifier': 'string',
'SingleSignOnUserValue': 'string',
'UserSettings': {
'ExecutionRole': 'string',
'SecurityGroups': [
'string',
],
'SharingSettings': {
'NotebookOutputOption': 'Allowed'|'Disabled',
'S3OutputPath': 'string',
'S3KmsKeyId': 'string'
},
'JupyterServerAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'LifecycleConfigArns': [
'string',
]
},
'KernelGatewayAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
],
'LifecycleConfigArns': [
'string',
]
},
'TensorBoardAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
}
},
'RStudioServerProAppSettings': {
'AccessStatus': 'ENABLED'|'DISABLED',
'UserGroup': 'R_STUDIO_ADMIN'|'R_STUDIO_USER'
},
'RSessionAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
]
}
}
}
Response Structure
(dict) --
DomainId (string) --
The ID of the domain that contains the profile.
UserProfileArn (string) --
The user profile Amazon Resource Name (ARN).
UserProfileName (string) --
The user profile name.
HomeEfsFileSystemUid (string) --
The ID of the user's profile in the Amazon Elastic File System (EFS) volume.
Status (string) --
The status.
LastModifiedTime (datetime) --
The last modified time.
CreationTime (datetime) --
The creation time.
FailureReason (string) --
The failure reason.
SingleSignOnUserIdentifier (string) --
The SSO user identifier.
SingleSignOnUserValue (string) --
The SSO user value.
UserSettings (dict) --
A collection of settings.
ExecutionRole (string) --
The execution role for the user.
SecurityGroups (list) --
The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly .
Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly .
Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
(string) --
SharingSettings (dict) --
Specifies options for sharing SageMaker Studio notebooks.
NotebookOutputOption (string) --
Whether to include the notebook cell output when sharing the notebook. The default is Disabled .
S3OutputPath (string) --
When NotebookOutputOption is Allowed , the Amazon S3 bucket used to store the shared notebook snapshots.
S3KmsKeyId (string) --
When NotebookOutputOption is Allowed , the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
JupyterServerAppSettings (dict) --
The Jupyter server's app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
KernelGatewayAppSettings (dict) --
The kernel gateway app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
Note
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a KernelGateway app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) --
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) --
The name of the AppImageConfig.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
TensorBoardAppSettings (dict) --
The TensorBoard app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
RStudioServerProAppSettings (dict) --
A collection of settings that configure user interaction with the RStudioServerPro app.
AccessStatus (string) --
Indicates whether the current user has access to the RStudioServerPro app.
UserGroup (string) --
The level of permissions that the user has within the RStudioServerPro app. This value defaults to User. The Admin value allows the user access to the RStudio Administrative Dashboard.
RSessionAppSettings (dict) --
A collection of settings that configure the RSessionGateway app.
DefaultResourceSpec (dict) --
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a RSession app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) --
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) --
The name of the AppImageConfig.
{'Candidates': {'CandidateProperties': {'CandidateMetrics': {'StandardMetricName': 'Accuracy '
'| '
'MSE '
'| '
'F1 '
'| '
'F1macro '
'| '
'AUC '
'| '
'RMSE '
'| '
'MAE '
'| '
'R2 '
'| '
'BalancedAccuracy '
'| '
'Precision '
'| '
'PrecisionMacro '
'| '
'Recall '
'| '
'RecallMacro '
'| '
'LogLoss'}}}}
List the candidates created for the job.
See also: AWS API Documentation
Request Syntax
client.list_candidates_for_auto_ml_job(
AutoMLJobName='string',
StatusEquals='Completed'|'InProgress'|'Failed'|'Stopped'|'Stopping',
CandidateNameEquals='string',
SortOrder='Ascending'|'Descending',
SortBy='CreationTime'|'Status'|'FinalObjectiveMetricValue',
MaxResults=123,
NextToken='string'
)
string
[REQUIRED]
List the candidates created for the job by providing the job's name.
string
List the candidates for the job and filter by status.
string
List the candidates for the job and filter by candidate name.
string
The sort order for the results. The default is Ascending .
string
The parameter by which to sort the results. The default is Descending .
integer
List the job's candidates up to a specified limit.
string
If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
dict
Response Syntax
{
'Candidates': [
{
'CandidateName': 'string',
'FinalAutoMLJobObjectiveMetric': {
'Type': 'Maximize'|'Minimize',
'MetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC',
'Value': ...
},
'ObjectiveStatus': 'Succeeded'|'Pending'|'Failed',
'CandidateSteps': [
{
'CandidateStepType': 'AWS::SageMaker::TrainingJob'|'AWS::SageMaker::TransformJob'|'AWS::SageMaker::ProcessingJob',
'CandidateStepArn': 'string',
'CandidateStepName': 'string'
},
],
'CandidateStatus': 'Completed'|'InProgress'|'Failed'|'Stopped'|'Stopping',
'InferenceContainers': [
{
'Image': 'string',
'ModelDataUrl': 'string',
'Environment': {
'string': 'string'
}
},
],
'CreationTime': datetime(2015, 1, 1),
'EndTime': datetime(2015, 1, 1),
'LastModifiedTime': datetime(2015, 1, 1),
'FailureReason': 'string',
'CandidateProperties': {
'CandidateArtifactLocations': {
'Explainability': 'string',
'ModelInsights': 'string'
},
'CandidateMetrics': [
{
'MetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC',
'Value': ...,
'Set': 'Train'|'Validation'|'Test',
'StandardMetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC'|'RMSE'|'MAE'|'R2'|'BalancedAccuracy'|'Precision'|'PrecisionMacro'|'Recall'|'RecallMacro'|'LogLoss'
},
]
}
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Candidates (list) --
Summaries about the AutoMLCandidates .
(dict) --
Information about a candidate produced by an AutoML training job, including its status, steps, and other properties.
CandidateName (string) --
The name of the candidate.
FinalAutoMLJobObjectiveMetric (dict) --
The best candidate result from an AutoML training job.
Type (string) --
The type of metric with the best result.
MetricName (string) --
The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName .
Value (float) --
The value of the metric with the best result.
ObjectiveStatus (string) --
The objective's status.
CandidateSteps (list) --
Information about the candidate's steps.
(dict) --
Information about the steps for a candidate and what step it is working on.
CandidateStepType (string) --
Whether the candidate is at the transform, training, or processing step.
CandidateStepArn (string) --
The ARN for the candidate's step.
CandidateStepName (string) --
The name for the candidate's step.
CandidateStatus (string) --
The candidate's status.
InferenceContainers (list) --
Information about the inference container definitions.
(dict) --
A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see .
Image (string) --
The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see .
ModelDataUrl (string) --
The location of the model artifacts. For more information, see .
Environment (dict) --
The environment variables to set in the container. For more information, see .
(string) --
(string) --
CreationTime (datetime) --
The creation time.
EndTime (datetime) --
The end time.
LastModifiedTime (datetime) --
The last modified time.
FailureReason (string) --
The failure reason.
CandidateProperties (dict) --
The properties of an AutoML candidate job.
CandidateArtifactLocations (dict) --
The Amazon S3 prefix to the artifacts generated for an AutoML candidate.
Explainability (string) --
The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate.
ModelInsights (string) --
The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate.
CandidateMetrics (list) --
Information about the candidate metrics for an AutoML job.
(dict) --
Information about the metric for a candidate produced by an AutoML job.
MetricName (string) --
The name of the metric.
Value (float) --
The value of the metric.
Set (string) --
The dataset split from which the AutoML job produced the metric.
StandardMetricName (string) --
The name of the standard metric.
NextToken (string) --
If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
{'DefaultUserSettings': {'RSessionAppSettings': {'CustomImages': [{'AppImageConfigName': 'string',
'ImageName': 'string',
'ImageVersionNumber': 'integer'}],
'DefaultResourceSpec': {'InstanceType': 'system '
'| '
'ml.t3.micro '
'| '
'ml.t3.small '
'| '
'ml.t3.medium '
'| '
'ml.t3.large '
'| '
'ml.t3.xlarge '
'| '
'ml.t3.2xlarge '
'| '
'ml.m5.large '
'| '
'ml.m5.xlarge '
'| '
'ml.m5.2xlarge '
'| '
'ml.m5.4xlarge '
'| '
'ml.m5.8xlarge '
'| '
'ml.m5.12xlarge '
'| '
'ml.m5.16xlarge '
'| '
'ml.m5.24xlarge '
'| '
'ml.m5d.large '
'| '
'ml.m5d.xlarge '
'| '
'ml.m5d.2xlarge '
'| '
'ml.m5d.4xlarge '
'| '
'ml.m5d.8xlarge '
'| '
'ml.m5d.12xlarge '
'| '
'ml.m5d.16xlarge '
'| '
'ml.m5d.24xlarge '
'| '
'ml.c5.large '
'| '
'ml.c5.xlarge '
'| '
'ml.c5.2xlarge '
'| '
'ml.c5.4xlarge '
'| '
'ml.c5.9xlarge '
'| '
'ml.c5.12xlarge '
'| '
'ml.c5.18xlarge '
'| '
'ml.c5.24xlarge '
'| '
'ml.p3.2xlarge '
'| '
'ml.p3.8xlarge '
'| '
'ml.p3.16xlarge '
'| '
'ml.p3dn.24xlarge '
'| '
'ml.g4dn.xlarge '
'| '
'ml.g4dn.2xlarge '
'| '
'ml.g4dn.4xlarge '
'| '
'ml.g4dn.8xlarge '
'| '
'ml.g4dn.12xlarge '
'| '
'ml.g4dn.16xlarge '
'| '
'ml.r5.large '
'| '
'ml.r5.xlarge '
'| '
'ml.r5.2xlarge '
'| '
'ml.r5.4xlarge '
'| '
'ml.r5.8xlarge '
'| '
'ml.r5.12xlarge '
'| '
'ml.r5.16xlarge '
'| '
'ml.r5.24xlarge',
'LifecycleConfigArn': 'string',
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string'}}}}
Updates the default settings for new user profiles in the domain.
See also: AWS API Documentation
Request Syntax
client.update_domain(
DomainId='string',
DefaultUserSettings={
'ExecutionRole': 'string',
'SecurityGroups': [
'string',
],
'SharingSettings': {
'NotebookOutputOption': 'Allowed'|'Disabled',
'S3OutputPath': 'string',
'S3KmsKeyId': 'string'
},
'JupyterServerAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'LifecycleConfigArns': [
'string',
]
},
'KernelGatewayAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
],
'LifecycleConfigArns': [
'string',
]
},
'TensorBoardAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
}
},
'RStudioServerProAppSettings': {
'AccessStatus': 'ENABLED'|'DISABLED',
'UserGroup': 'R_STUDIO_ADMIN'|'R_STUDIO_USER'
},
'RSessionAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
]
}
},
DomainSettingsForUpdate={
'RStudioServerProDomainSettingsForUpdate': {
'DomainExecutionRoleArn': 'string',
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
}
}
}
)
string
[REQUIRED]
The ID of the domain to be updated.
dict
A collection of settings.
ExecutionRole (string) --
The execution role for the user.
SecurityGroups (list) --
The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly .
Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly .
Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
(string) --
SharingSettings (dict) --
Specifies options for sharing SageMaker Studio notebooks.
NotebookOutputOption (string) --
Whether to include the notebook cell output when sharing the notebook. The default is Disabled .
S3OutputPath (string) --
When NotebookOutputOption is Allowed , the Amazon S3 bucket used to store the shared notebook snapshots.
S3KmsKeyId (string) --
When NotebookOutputOption is Allowed , the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
JupyterServerAppSettings (dict) --
The Jupyter server's app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
KernelGatewayAppSettings (dict) --
The kernel gateway app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
Note
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a KernelGateway app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) -- [REQUIRED]
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) -- [REQUIRED]
The name of the AppImageConfig.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
TensorBoardAppSettings (dict) --
The TensorBoard app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
RStudioServerProAppSettings (dict) --
A collection of settings that configure user interaction with the RStudioServerPro app.
AccessStatus (string) --
Indicates whether the current user has access to the RStudioServerPro app.
UserGroup (string) --
The level of permissions that the user has within the RStudioServerPro app. This value defaults to User. The Admin value allows the user access to the RStudio Administrative Dashboard.
RSessionAppSettings (dict) --
A collection of settings that configure the RSessionGateway app.
DefaultResourceSpec (dict) --
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a RSession app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) -- [REQUIRED]
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) -- [REQUIRED]
The name of the AppImageConfig.
dict
A collection of DomainSettings configuration values to update.
RStudioServerProDomainSettingsForUpdate (dict) --
A collection of RStudioServerPro Domain-level app settings to update.
DomainExecutionRoleArn (string) -- [REQUIRED]
The execution role for the RStudioServerPro Domain-level app.
DefaultResourceSpec (dict) --
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
dict
Response Syntax
{
'DomainArn': 'string'
}
Response Structure
(dict) --
DomainArn (string) --
The Amazon Resource Name (ARN) of the domain.
{'UserSettings': {'RSessionAppSettings': {'CustomImages': [{'AppImageConfigName': 'string',
'ImageName': 'string',
'ImageVersionNumber': 'integer'}],
'DefaultResourceSpec': {'InstanceType': 'system '
'| '
'ml.t3.micro '
'| '
'ml.t3.small '
'| '
'ml.t3.medium '
'| '
'ml.t3.large '
'| '
'ml.t3.xlarge '
'| '
'ml.t3.2xlarge '
'| '
'ml.m5.large '
'| '
'ml.m5.xlarge '
'| '
'ml.m5.2xlarge '
'| '
'ml.m5.4xlarge '
'| '
'ml.m5.8xlarge '
'| '
'ml.m5.12xlarge '
'| '
'ml.m5.16xlarge '
'| '
'ml.m5.24xlarge '
'| '
'ml.m5d.large '
'| '
'ml.m5d.xlarge '
'| '
'ml.m5d.2xlarge '
'| '
'ml.m5d.4xlarge '
'| '
'ml.m5d.8xlarge '
'| '
'ml.m5d.12xlarge '
'| '
'ml.m5d.16xlarge '
'| '
'ml.m5d.24xlarge '
'| '
'ml.c5.large '
'| '
'ml.c5.xlarge '
'| '
'ml.c5.2xlarge '
'| '
'ml.c5.4xlarge '
'| '
'ml.c5.9xlarge '
'| '
'ml.c5.12xlarge '
'| '
'ml.c5.18xlarge '
'| '
'ml.c5.24xlarge '
'| '
'ml.p3.2xlarge '
'| '
'ml.p3.8xlarge '
'| '
'ml.p3.16xlarge '
'| '
'ml.p3dn.24xlarge '
'| '
'ml.g4dn.xlarge '
'| '
'ml.g4dn.2xlarge '
'| '
'ml.g4dn.4xlarge '
'| '
'ml.g4dn.8xlarge '
'| '
'ml.g4dn.12xlarge '
'| '
'ml.g4dn.16xlarge '
'| '
'ml.r5.large '
'| '
'ml.r5.xlarge '
'| '
'ml.r5.2xlarge '
'| '
'ml.r5.4xlarge '
'| '
'ml.r5.8xlarge '
'| '
'ml.r5.12xlarge '
'| '
'ml.r5.16xlarge '
'| '
'ml.r5.24xlarge',
'LifecycleConfigArn': 'string',
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string'}}}}
Updates a user profile.
See also: AWS API Documentation
Request Syntax
client.update_user_profile(
DomainId='string',
UserProfileName='string',
UserSettings={
'ExecutionRole': 'string',
'SecurityGroups': [
'string',
],
'SharingSettings': {
'NotebookOutputOption': 'Allowed'|'Disabled',
'S3OutputPath': 'string',
'S3KmsKeyId': 'string'
},
'JupyterServerAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'LifecycleConfigArns': [
'string',
]
},
'KernelGatewayAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
],
'LifecycleConfigArns': [
'string',
]
},
'TensorBoardAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
}
},
'RStudioServerProAppSettings': {
'AccessStatus': 'ENABLED'|'DISABLED',
'UserGroup': 'R_STUDIO_ADMIN'|'R_STUDIO_USER'
},
'RSessionAppSettings': {
'DefaultResourceSpec': {
'SageMakerImageArn': 'string',
'SageMakerImageVersionArn': 'string',
'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'LifecycleConfigArn': 'string'
},
'CustomImages': [
{
'ImageName': 'string',
'ImageVersionNumber': 123,
'AppImageConfigName': 'string'
},
]
}
}
)
string
[REQUIRED]
The domain ID.
string
[REQUIRED]
The user profile name.
dict
A collection of settings.
ExecutionRole (string) --
The execution role for the user.
SecurityGroups (list) --
The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly .
Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly .
Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
(string) --
SharingSettings (dict) --
Specifies options for sharing SageMaker Studio notebooks.
NotebookOutputOption (string) --
Whether to include the notebook cell output when sharing the notebook. The default is Disabled .
S3OutputPath (string) --
When NotebookOutputOption is Allowed , the Amazon S3 bucket used to store the shared notebook snapshots.
S3KmsKeyId (string) --
When NotebookOutputOption is Allowed , the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
JupyterServerAppSettings (dict) --
The Jupyter server's app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
KernelGatewayAppSettings (dict) --
The kernel gateway app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
Note
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a KernelGateway app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) -- [REQUIRED]
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) -- [REQUIRED]
The name of the AppImageConfig.
LifecycleConfigArns (list) --
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
Note
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
(string) --
TensorBoardAppSettings (dict) --
The TensorBoard app settings.
DefaultResourceSpec (dict) --
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
RStudioServerProAppSettings (dict) --
A collection of settings that configure user interaction with the RStudioServerPro app.
AccessStatus (string) --
Indicates whether the current user has access to the RStudioServerPro app.
UserGroup (string) --
The level of permissions that the user has within the RStudioServerPro app. This value defaults to User. The Admin value allows the user access to the RStudio Administrative Dashboard.
RSessionAppSettings (dict) --
A collection of settings that configure the RSessionGateway app.
DefaultResourceSpec (dict) --
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SageMakerImageArn (string) --
The ARN of the SageMaker image that the image version belongs to.
SageMakerImageVersionArn (string) --
The ARN of the image version created on the instance.
InstanceType (string) --
The instance type that the image version runs on.
Note
JupyterServer Apps only support the system value. KernelGateway Apps do not support the system value, but support all other values for available instance types.
LifecycleConfigArn (string) --
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
CustomImages (list) --
A list of custom SageMaker images that are configured to run as a RSession app.
(dict) --
A custom SageMaker image. For more information, see Bring your own SageMaker image .
ImageName (string) -- [REQUIRED]
The name of the CustomImage. Must be unique to your account.
ImageVersionNumber (integer) --
The version number of the CustomImage.
AppImageConfigName (string) -- [REQUIRED]
The name of the AppImageConfig.
dict
Response Syntax
{
'UserProfileArn': 'string'
}
Response Structure
(dict) --
UserProfileArn (string) --
The user profile Amazon Resource Name (ARN).