2023/05/24 - Amazon SageMaker Service - 2 updated api methods
Changes SageMaker now provides an instantaneous deployment recommendation through the DescribeModel API
{'DeploymentRecommendation': {'RealTimeInferenceRecommendations': [{'Environment': {'string': 'string'},
'InstanceType': 'ml.t2.medium '
'| '
'ml.t2.large '
'| '
'ml.t2.xlarge '
'| '
'ml.t2.2xlarge '
'| '
'ml.m4.xlarge '
'| '
'ml.m4.2xlarge '
'| '
'ml.m4.4xlarge '
'| '
'ml.m4.10xlarge '
'| '
'ml.m4.16xlarge '
'| '
'ml.m5.large '
'| '
'ml.m5.xlarge '
'| '
'ml.m5.2xlarge '
'| '
'ml.m5.4xlarge '
'| '
'ml.m5.12xlarge '
'| '
'ml.m5.24xlarge '
'| '
'ml.m5d.large '
'| '
'ml.m5d.xlarge '
'| '
'ml.m5d.2xlarge '
'| '
'ml.m5d.4xlarge '
'| '
'ml.m5d.12xlarge '
'| '
'ml.m5d.24xlarge '
'| '
'ml.c4.large '
'| '
'ml.c4.xlarge '
'| '
'ml.c4.2xlarge '
'| '
'ml.c4.4xlarge '
'| '
'ml.c4.8xlarge '
'| '
'ml.p2.xlarge '
'| '
'ml.p2.8xlarge '
'| '
'ml.p2.16xlarge '
'| '
'ml.p3.2xlarge '
'| '
'ml.p3.8xlarge '
'| '
'ml.p3.16xlarge '
'| '
'ml.c5.large '
'| '
'ml.c5.xlarge '
'| '
'ml.c5.2xlarge '
'| '
'ml.c5.4xlarge '
'| '
'ml.c5.9xlarge '
'| '
'ml.c5.18xlarge '
'| '
'ml.c5d.large '
'| '
'ml.c5d.xlarge '
'| '
'ml.c5d.2xlarge '
'| '
'ml.c5d.4xlarge '
'| '
'ml.c5d.9xlarge '
'| '
'ml.c5d.18xlarge '
'| '
'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.r5.12xlarge '
'| '
'ml.r5.24xlarge '
'| '
'ml.r5d.large '
'| '
'ml.r5d.xlarge '
'| '
'ml.r5d.2xlarge '
'| '
'ml.r5d.4xlarge '
'| '
'ml.r5d.12xlarge '
'| '
'ml.r5d.24xlarge '
'| '
'ml.inf1.xlarge '
'| '
'ml.inf1.2xlarge '
'| '
'ml.inf1.6xlarge '
'| '
'ml.inf1.24xlarge '
'| '
'ml.c6i.large '
'| '
'ml.c6i.xlarge '
'| '
'ml.c6i.2xlarge '
'| '
'ml.c6i.4xlarge '
'| '
'ml.c6i.8xlarge '
'| '
'ml.c6i.12xlarge '
'| '
'ml.c6i.16xlarge '
'| '
'ml.c6i.24xlarge '
'| '
'ml.c6i.32xlarge '
'| '
'ml.g5.xlarge '
'| '
'ml.g5.2xlarge '
'| '
'ml.g5.4xlarge '
'| '
'ml.g5.8xlarge '
'| '
'ml.g5.12xlarge '
'| '
'ml.g5.16xlarge '
'| '
'ml.g5.24xlarge '
'| '
'ml.g5.48xlarge '
'| '
'ml.p4d.24xlarge '
'| '
'ml.c7g.large '
'| '
'ml.c7g.xlarge '
'| '
'ml.c7g.2xlarge '
'| '
'ml.c7g.4xlarge '
'| '
'ml.c7g.8xlarge '
'| '
'ml.c7g.12xlarge '
'| '
'ml.c7g.16xlarge '
'| '
'ml.m6g.large '
'| '
'ml.m6g.xlarge '
'| '
'ml.m6g.2xlarge '
'| '
'ml.m6g.4xlarge '
'| '
'ml.m6g.8xlarge '
'| '
'ml.m6g.12xlarge '
'| '
'ml.m6g.16xlarge '
'| '
'ml.m6gd.large '
'| '
'ml.m6gd.xlarge '
'| '
'ml.m6gd.2xlarge '
'| '
'ml.m6gd.4xlarge '
'| '
'ml.m6gd.8xlarge '
'| '
'ml.m6gd.12xlarge '
'| '
'ml.m6gd.16xlarge '
'| '
'ml.c6g.large '
'| '
'ml.c6g.xlarge '
'| '
'ml.c6g.2xlarge '
'| '
'ml.c6g.4xlarge '
'| '
'ml.c6g.8xlarge '
'| '
'ml.c6g.12xlarge '
'| '
'ml.c6g.16xlarge '
'| '
'ml.c6gd.large '
'| '
'ml.c6gd.xlarge '
'| '
'ml.c6gd.2xlarge '
'| '
'ml.c6gd.4xlarge '
'| '
'ml.c6gd.8xlarge '
'| '
'ml.c6gd.12xlarge '
'| '
'ml.c6gd.16xlarge '
'| '
'ml.c6gn.large '
'| '
'ml.c6gn.xlarge '
'| '
'ml.c6gn.2xlarge '
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'ml.c6gn.4xlarge '
'| '
'ml.c6gn.8xlarge '
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'ml.c6gn.12xlarge '
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'ml.c6gn.16xlarge '
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'ml.r6g.large '
'| '
'ml.r6g.xlarge '
'| '
'ml.r6g.2xlarge '
'| '
'ml.r6g.4xlarge '
'| '
'ml.r6g.8xlarge '
'| '
'ml.r6g.12xlarge '
'| '
'ml.r6g.16xlarge '
'| '
'ml.r6gd.large '
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'ml.r6gd.xlarge '
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'ml.r6gd.2xlarge '
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'ml.r6gd.4xlarge '
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'ml.r6gd.8xlarge '
'| '
'ml.r6gd.12xlarge '
'| '
'ml.r6gd.16xlarge '
'| '
'ml.p4de.24xlarge '
'| '
'ml.trn1.2xlarge '
'| '
'ml.trn1.32xlarge '
'| '
'ml.inf2.xlarge '
'| '
'ml.inf2.8xlarge '
'| '
'ml.inf2.24xlarge '
'| '
'ml.inf2.48xlarge',
'RecommendationId': 'string'}],
'RecommendationStatus': 'IN_PROGRESS | COMPLETED '
'| FAILED | '
'NOT_APPLICABLE'}}
Describes a model that you created using the CreateModel API.
See also: AWS API Documentation
Request Syntax
client.describe_model(
ModelName='string'
)
string
[REQUIRED]
The name of the model.
dict
Response Syntax
{
'ModelName': 'string',
'PrimaryContainer': {
'ContainerHostname': 'string',
'Image': 'string',
'ImageConfig': {
'RepositoryAccessMode': 'Platform'|'Vpc',
'RepositoryAuthConfig': {
'RepositoryCredentialsProviderArn': 'string'
}
},
'Mode': 'SingleModel'|'MultiModel',
'ModelDataUrl': 'string',
'Environment': {
'string': 'string'
},
'ModelPackageName': 'string',
'InferenceSpecificationName': 'string',
'MultiModelConfig': {
'ModelCacheSetting': 'Enabled'|'Disabled'
}
},
'Containers': [
{
'ContainerHostname': 'string',
'Image': 'string',
'ImageConfig': {
'RepositoryAccessMode': 'Platform'|'Vpc',
'RepositoryAuthConfig': {
'RepositoryCredentialsProviderArn': 'string'
}
},
'Mode': 'SingleModel'|'MultiModel',
'ModelDataUrl': 'string',
'Environment': {
'string': 'string'
},
'ModelPackageName': 'string',
'InferenceSpecificationName': 'string',
'MultiModelConfig': {
'ModelCacheSetting': 'Enabled'|'Disabled'
}
},
],
'InferenceExecutionConfig': {
'Mode': 'Serial'|'Direct'
},
'ExecutionRoleArn': 'string',
'VpcConfig': {
'SecurityGroupIds': [
'string',
],
'Subnets': [
'string',
]
},
'CreationTime': datetime(2015, 1, 1),
'ModelArn': 'string',
'EnableNetworkIsolation': True|False,
'DeploymentRecommendation': {
'RecommendationStatus': 'IN_PROGRESS'|'COMPLETED'|'FAILED'|'NOT_APPLICABLE',
'RealTimeInferenceRecommendations': [
{
'RecommendationId': 'string',
'InstanceType': 'ml.t2.medium'|'ml.t2.large'|'ml.t2.xlarge'|'ml.t2.2xlarge'|'ml.m4.xlarge'|'ml.m4.2xlarge'|'ml.m4.4xlarge'|'ml.m4.10xlarge'|'ml.m4.16xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.12xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.12xlarge'|'ml.m5d.24xlarge'|'ml.c4.large'|'ml.c4.xlarge'|'ml.c4.2xlarge'|'ml.c4.4xlarge'|'ml.c4.8xlarge'|'ml.p2.xlarge'|'ml.p2.8xlarge'|'ml.p2.16xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.18xlarge'|'ml.c5d.large'|'ml.c5d.xlarge'|'ml.c5d.2xlarge'|'ml.c5d.4xlarge'|'ml.c5d.9xlarge'|'ml.c5d.18xlarge'|'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.r5.12xlarge'|'ml.r5.24xlarge'|'ml.r5d.large'|'ml.r5d.xlarge'|'ml.r5d.2xlarge'|'ml.r5d.4xlarge'|'ml.r5d.12xlarge'|'ml.r5d.24xlarge'|'ml.inf1.xlarge'|'ml.inf1.2xlarge'|'ml.inf1.6xlarge'|'ml.inf1.24xlarge'|'ml.c6i.large'|'ml.c6i.xlarge'|'ml.c6i.2xlarge'|'ml.c6i.4xlarge'|'ml.c6i.8xlarge'|'ml.c6i.12xlarge'|'ml.c6i.16xlarge'|'ml.c6i.24xlarge'|'ml.c6i.32xlarge'|'ml.g5.xlarge'|'ml.g5.2xlarge'|'ml.g5.4xlarge'|'ml.g5.8xlarge'|'ml.g5.12xlarge'|'ml.g5.16xlarge'|'ml.g5.24xlarge'|'ml.g5.48xlarge'|'ml.p4d.24xlarge'|'ml.c7g.large'|'ml.c7g.xlarge'|'ml.c7g.2xlarge'|'ml.c7g.4xlarge'|'ml.c7g.8xlarge'|'ml.c7g.12xlarge'|'ml.c7g.16xlarge'|'ml.m6g.large'|'ml.m6g.xlarge'|'ml.m6g.2xlarge'|'ml.m6g.4xlarge'|'ml.m6g.8xlarge'|'ml.m6g.12xlarge'|'ml.m6g.16xlarge'|'ml.m6gd.large'|'ml.m6gd.xlarge'|'ml.m6gd.2xlarge'|'ml.m6gd.4xlarge'|'ml.m6gd.8xlarge'|'ml.m6gd.12xlarge'|'ml.m6gd.16xlarge'|'ml.c6g.large'|'ml.c6g.xlarge'|'ml.c6g.2xlarge'|'ml.c6g.4xlarge'|'ml.c6g.8xlarge'|'ml.c6g.12xlarge'|'ml.c6g.16xlarge'|'ml.c6gd.large'|'ml.c6gd.xlarge'|'ml.c6gd.2xlarge'|'ml.c6gd.4xlarge'|'ml.c6gd.8xlarge'|'ml.c6gd.12xlarge'|'ml.c6gd.16xlarge'|'ml.c6gn.large'|'ml.c6gn.xlarge'|'ml.c6gn.2xlarge'|'ml.c6gn.4xlarge'|'ml.c6gn.8xlarge'|'ml.c6gn.12xlarge'|'ml.c6gn.16xlarge'|'ml.r6g.large'|'ml.r6g.xlarge'|'ml.r6g.2xlarge'|'ml.r6g.4xlarge'|'ml.r6g.8xlarge'|'ml.r6g.12xlarge'|'ml.r6g.16xlarge'|'ml.r6gd.large'|'ml.r6gd.xlarge'|'ml.r6gd.2xlarge'|'ml.r6gd.4xlarge'|'ml.r6gd.8xlarge'|'ml.r6gd.12xlarge'|'ml.r6gd.16xlarge'|'ml.p4de.24xlarge'|'ml.trn1.2xlarge'|'ml.trn1.32xlarge'|'ml.inf2.xlarge'|'ml.inf2.8xlarge'|'ml.inf2.24xlarge'|'ml.inf2.48xlarge',
'Environment': {
'string': 'string'
}
},
]
}
}
Response Structure
(dict) --
ModelName (string) --
Name of the SageMaker model.
PrimaryContainer (dict) --
The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.
ContainerHostname (string) --
This parameter is ignored for models that contain only a PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline. If you don't specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.
Image (string) --
The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
ImageConfig (dict) --
Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers.
RepositoryAccessMode (string) --
Set this to one of the following values:
Platform - The model image is hosted in Amazon ECR.
Vpc - The model image is hosted in a private Docker registry in your VPC.
RepositoryAuthConfig (dict) --
(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field, and the private Docker registry where the model image is hosted requires authentication.
RepositoryCredentialsProviderArn (string) --
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see Create a Lambda function with the console in the Amazon Web Services Lambda Developer Guide.
Mode (string) --
Whether the container hosts a single model or multiple models.
ModelDataUrl (string) --
The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
Environment (dict) --
The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.
(string) --
(string) --
ModelPackageName (string) --
The name or Amazon Resource Name (ARN) of the model package to use to create the model.
InferenceSpecificationName (string) --
The inference specification name in the model package version.
MultiModelConfig (dict) --
Specifies additional configuration for multi-model endpoints.
ModelCacheSetting (string) --
Whether to cache models for a multi-model endpoint. By default, multi-model endpoints cache models so that a model does not have to be loaded into memory each time it is invoked. Some use cases do not benefit from model caching. For example, if an endpoint hosts a large number of models that are each invoked infrequently, the endpoint might perform better if you disable model caching. To disable model caching, set the value of this parameter to Disabled.
Containers (list) --
The containers in the inference pipeline.
(dict) --
Describes the container, as part of model definition.
ContainerHostname (string) --
This parameter is ignored for models that contain only a PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline. If you don't specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.
Image (string) --
The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
ImageConfig (dict) --
Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers.
RepositoryAccessMode (string) --
Set this to one of the following values:
Platform - The model image is hosted in Amazon ECR.
Vpc - The model image is hosted in a private Docker registry in your VPC.
RepositoryAuthConfig (dict) --
(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field, and the private Docker registry where the model image is hosted requires authentication.
RepositoryCredentialsProviderArn (string) --
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see Create a Lambda function with the console in the Amazon Web Services Lambda Developer Guide.
Mode (string) --
Whether the container hosts a single model or multiple models.
ModelDataUrl (string) --
The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
Environment (dict) --
The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.
(string) --
(string) --
ModelPackageName (string) --
The name or Amazon Resource Name (ARN) of the model package to use to create the model.
InferenceSpecificationName (string) --
The inference specification name in the model package version.
MultiModelConfig (dict) --
Specifies additional configuration for multi-model endpoints.
ModelCacheSetting (string) --
Whether to cache models for a multi-model endpoint. By default, multi-model endpoints cache models so that a model does not have to be loaded into memory each time it is invoked. Some use cases do not benefit from model caching. For example, if an endpoint hosts a large number of models that are each invoked infrequently, the endpoint might perform better if you disable model caching. To disable model caching, set the value of this parameter to Disabled.
InferenceExecutionConfig (dict) --
Specifies details of how containers in a multi-container endpoint are called.
Mode (string) --
How containers in a multi-container are run. The following values are valid.
SERIAL - Containers run as a serial pipeline.
DIRECT - Only the individual container that you specify is run.
ExecutionRoleArn (string) --
The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
VpcConfig (dict) --
A VpcConfig object that specifies the VPC that this model has access to. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud
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) --
CreationTime (datetime) --
A timestamp that shows when the model was created.
ModelArn (string) --
The Amazon Resource Name (ARN) of the model.
EnableNetworkIsolation (boolean) --
If True, no inbound or outbound network calls can be made to or from the model container.
DeploymentRecommendation (dict) --
A set of recommended deployment configurations for the model.
RecommendationStatus (string) --
Status of the deployment recommendation. NOT_APPLICABLE means that SageMaker is unable to provide a default recommendation for the model using the information provided.
RealTimeInferenceRecommendations (list) --
A list of RealTimeInferenceRecommendation items.
(dict) --
The recommended configuration to use for Real-Time Inference.
RecommendationId (string) --
The recommendation ID which uniquely identifies each recommendation.
InstanceType (string) --
The recommended instance type for Real-Time Inference.
Environment (dict) --
The recommended environment variables to set in the model container for Real-Time Inference.
(string) --
(string) --
{'Results': {'Model': {'Model': {'DeploymentRecommendation': {'RealTimeInferenceRecommendations': [{'Environment': {'string': 'string'},
'InstanceType': 'ml.t2.medium '
'| '
'ml.t2.large '
'| '
'ml.t2.xlarge '
'| '
'ml.t2.2xlarge '
'| '
'ml.m4.xlarge '
'| '
'ml.m4.2xlarge '
'| '
'ml.m4.4xlarge '
'| '
'ml.m4.10xlarge '
'| '
'ml.m4.16xlarge '
'| '
'ml.m5.large '
'| '
'ml.m5.xlarge '
'| '
'ml.m5.2xlarge '
'| '
'ml.m5.4xlarge '
'| '
'ml.m5.12xlarge '
'| '
'ml.m5.24xlarge '
'| '
'ml.m5d.large '
'| '
'ml.m5d.xlarge '
'| '
'ml.m5d.2xlarge '
'| '
'ml.m5d.4xlarge '
'| '
'ml.m5d.12xlarge '
'| '
'ml.m5d.24xlarge '
'| '
'ml.c4.large '
'| '
'ml.c4.xlarge '
'| '
'ml.c4.2xlarge '
'| '
'ml.c4.4xlarge '
'| '
'ml.c4.8xlarge '
'| '
'ml.p2.xlarge '
'| '
'ml.p2.8xlarge '
'| '
'ml.p2.16xlarge '
'| '
'ml.p3.2xlarge '
'| '
'ml.p3.8xlarge '
'| '
'ml.p3.16xlarge '
'| '
'ml.c5.large '
'| '
'ml.c5.xlarge '
'| '
'ml.c5.2xlarge '
'| '
'ml.c5.4xlarge '
'| '
'ml.c5.9xlarge '
'| '
'ml.c5.18xlarge '
'| '
'ml.c5d.large '
'| '
'ml.c5d.xlarge '
'| '
'ml.c5d.2xlarge '
'| '
'ml.c5d.4xlarge '
'| '
'ml.c5d.9xlarge '
'| '
'ml.c5d.18xlarge '
'| '
'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.r5.12xlarge '
'| '
'ml.r5.24xlarge '
'| '
'ml.r5d.large '
'| '
'ml.r5d.xlarge '
'| '
'ml.r5d.2xlarge '
'| '
'ml.r5d.4xlarge '
'| '
'ml.r5d.12xlarge '
'| '
'ml.r5d.24xlarge '
'| '
'ml.inf1.xlarge '
'| '
'ml.inf1.2xlarge '
'| '
'ml.inf1.6xlarge '
'| '
'ml.inf1.24xlarge '
'| '
'ml.c6i.large '
'| '
'ml.c6i.xlarge '
'| '
'ml.c6i.2xlarge '
'| '
'ml.c6i.4xlarge '
'| '
'ml.c6i.8xlarge '
'| '
'ml.c6i.12xlarge '
'| '
'ml.c6i.16xlarge '
'| '
'ml.c6i.24xlarge '
'| '
'ml.c6i.32xlarge '
'| '
'ml.g5.xlarge '
'| '
'ml.g5.2xlarge '
'| '
'ml.g5.4xlarge '
'| '
'ml.g5.8xlarge '
'| '
'ml.g5.12xlarge '
'| '
'ml.g5.16xlarge '
'| '
'ml.g5.24xlarge '
'| '
'ml.g5.48xlarge '
'| '
'ml.p4d.24xlarge '
'| '
'ml.c7g.large '
'| '
'ml.c7g.xlarge '
'| '
'ml.c7g.2xlarge '
'| '
'ml.c7g.4xlarge '
'| '
'ml.c7g.8xlarge '
'| '
'ml.c7g.12xlarge '
'| '
'ml.c7g.16xlarge '
'| '
'ml.m6g.large '
'| '
'ml.m6g.xlarge '
'| '
'ml.m6g.2xlarge '
'| '
'ml.m6g.4xlarge '
'| '
'ml.m6g.8xlarge '
'| '
'ml.m6g.12xlarge '
'| '
'ml.m6g.16xlarge '
'| '
'ml.m6gd.large '
'| '
'ml.m6gd.xlarge '
'| '
'ml.m6gd.2xlarge '
'| '
'ml.m6gd.4xlarge '
'| '
'ml.m6gd.8xlarge '
'| '
'ml.m6gd.12xlarge '
'| '
'ml.m6gd.16xlarge '
'| '
'ml.c6g.large '
'| '
'ml.c6g.xlarge '
'| '
'ml.c6g.2xlarge '
'| '
'ml.c6g.4xlarge '
'| '
'ml.c6g.8xlarge '
'| '
'ml.c6g.12xlarge '
'| '
'ml.c6g.16xlarge '
'| '
'ml.c6gd.large '
'| '
'ml.c6gd.xlarge '
'| '
'ml.c6gd.2xlarge '
'| '
'ml.c6gd.4xlarge '
'| '
'ml.c6gd.8xlarge '
'| '
'ml.c6gd.12xlarge '
'| '
'ml.c6gd.16xlarge '
'| '
'ml.c6gn.large '
'| '
'ml.c6gn.xlarge '
'| '
'ml.c6gn.2xlarge '
'| '
'ml.c6gn.4xlarge '
'| '
'ml.c6gn.8xlarge '
'| '
'ml.c6gn.12xlarge '
'| '
'ml.c6gn.16xlarge '
'| '
'ml.r6g.large '
'| '
'ml.r6g.xlarge '
'| '
'ml.r6g.2xlarge '
'| '
'ml.r6g.4xlarge '
'| '
'ml.r6g.8xlarge '
'| '
'ml.r6g.12xlarge '
'| '
'ml.r6g.16xlarge '
'| '
'ml.r6gd.large '
'| '
'ml.r6gd.xlarge '
'| '
'ml.r6gd.2xlarge '
'| '
'ml.r6gd.4xlarge '
'| '
'ml.r6gd.8xlarge '
'| '
'ml.r6gd.12xlarge '
'| '
'ml.r6gd.16xlarge '
'| '
'ml.p4de.24xlarge '
'| '
'ml.trn1.2xlarge '
'| '
'ml.trn1.32xlarge '
'| '
'ml.inf2.xlarge '
'| '
'ml.inf2.8xlarge '
'| '
'ml.inf2.24xlarge '
'| '
'ml.inf2.48xlarge',
'RecommendationId': 'string'}],
'RecommendationStatus': 'IN_PROGRESS '
'| '
'COMPLETED '
'| '
'FAILED '
'| '
'NOT_APPLICABLE'}}}}}
Finds SageMaker resources that match a search query. Matching resources are returned as a list of SearchRecord objects in the response. You can sort the search results by any resource property in a ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and timestamp.
See also: AWS API Documentation
Request Syntax
client.search(
Resource='TrainingJob'|'Experiment'|'ExperimentTrial'|'ExperimentTrialComponent'|'Endpoint'|'ModelPackage'|'ModelPackageGroup'|'Pipeline'|'PipelineExecution'|'FeatureGroup'|'Project'|'FeatureMetadata'|'HyperParameterTuningJob'|'ModelCard'|'Model',
SearchExpression={
'Filters': [
{
'Name': 'string',
'Operator': 'Equals'|'NotEquals'|'GreaterThan'|'GreaterThanOrEqualTo'|'LessThan'|'LessThanOrEqualTo'|'Contains'|'Exists'|'NotExists'|'In',
'Value': 'string'
},
],
'NestedFilters': [
{
'NestedPropertyName': 'string',
'Filters': [
{
'Name': 'string',
'Operator': 'Equals'|'NotEquals'|'GreaterThan'|'GreaterThanOrEqualTo'|'LessThan'|'LessThanOrEqualTo'|'Contains'|'Exists'|'NotExists'|'In',
'Value': 'string'
},
]
},
],
'SubExpressions': [
{'... recursive ...'},
],
'Operator': 'And'|'Or'
},
SortBy='string',
SortOrder='Ascending'|'Descending',
NextToken='string',
MaxResults=123
)
string
[REQUIRED]
The name of the SageMaker resource to search for.
dict
A Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive SubExpressions, NestedFilters, and Filters that can be included in a SearchExpression object is 50.
Filters (list) --
A list of filter objects.
(dict) --
A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API.
If you specify a Value, but not an Operator, SageMaker uses the equals operator.
In search, there are several property types:
Metrics
To define a metric filter, enter a value using the form "Metrics.<name>", where <name> is a metric name. For example, the following filter searches for training jobs with an "accuracy" metric greater than "0.9":
{
"Name": "Metrics.accuracy",
"Operator": "GreaterThan",
"Value": "0.9"
}
HyperParameters
To define a hyperparameter filter, enter a value with the form "HyperParameters.<name>". Decimal hyperparameter values are treated as a decimal in a comparison if the specified Value is also a decimal value. If the specified Value is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a "learning_rate" hyperparameter that is less than "0.5":
{
"Name": "HyperParameters.learning_rate",
"Operator": "LessThan",
"Value": "0.5"
}
Tags
To define a tag filter, enter a value with the form Tags.<key>.
Name (string) -- [REQUIRED]
A resource property name. For example, TrainingJobName. For valid property names, see SearchRecord. You must specify a valid property for the resource.
Operator (string) --
A Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values:
Equals
The value of Name equals Value.
NotEquals
The value of Name doesn't equal Value.
Exists
The Name property exists.
NotExists
The Name property does not exist.
GreaterThan
The value of Name is greater than Value. Not supported for text properties.
GreaterThanOrEqualTo
The value of Name is greater than or equal to Value. Not supported for text properties.
LessThan
The value of Name is less than Value. Not supported for text properties.
LessThanOrEqualTo
The value of Name is less than or equal to Value. Not supported for text properties.
In
The value of Name is one of the comma delimited strings in Value. Only supported for text properties.
Contains
The value of Name contains the string Value. Only supported for text properties.
A SearchExpression can include the Contains operator multiple times when the value of Name is one of the following:
Experiment.DisplayName
Experiment.ExperimentName
Experiment.Tags
Trial.DisplayName
Trial.TrialName
Trial.Tags
TrialComponent.DisplayName
TrialComponent.TrialComponentName
TrialComponent.Tags
TrialComponent.InputArtifacts
TrialComponent.OutputArtifacts
A SearchExpression can include only one Contains operator for all other values of Name. In these cases, if you include multiple Contains operators in the SearchExpression, the result is the following error message: " 'CONTAINS' operator usage limit of 1 exceeded."
Value (string) --
A value used with Name and Operator to determine which resources satisfy the filter's condition. For numerical properties, Value must be an integer or floating-point decimal. For timestamp properties, Value must be an ISO 8601 date-time string of the following format: YYYY-mm-dd'T'HH:MM:SS.
NestedFilters (list) --
A list of nested filter objects.
(dict) --
A list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API.
For example, to filter on a training job's InputDataConfig property with a specific channel name and S3Uri prefix, define the following filters:
'{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"}',
'{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains", "Value":"mybucket/catdata"}'
NestedPropertyName (string) -- [REQUIRED]
The name of the property to use in the nested filters. The value must match a listed property name, such as InputDataConfig.
Filters (list) -- [REQUIRED]
A list of filters. Each filter acts on a property. Filters must contain at least one Filters value. For example, a NestedFilters call might include a filter on the PropertyName parameter of the InputDataConfig property: InputDataConfig.DataSource.S3DataSource.S3Uri.
(dict) --
A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API.
If you specify a Value, but not an Operator, SageMaker uses the equals operator.
In search, there are several property types:
Metrics
To define a metric filter, enter a value using the form "Metrics.<name>", where <name> is a metric name. For example, the following filter searches for training jobs with an "accuracy" metric greater than "0.9":
{
"Name": "Metrics.accuracy",
"Operator": "GreaterThan",
"Value": "0.9"
}
HyperParameters
To define a hyperparameter filter, enter a value with the form "HyperParameters.<name>". Decimal hyperparameter values are treated as a decimal in a comparison if the specified Value is also a decimal value. If the specified Value is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a "learning_rate" hyperparameter that is less than "0.5":
{
"Name": "HyperParameters.learning_rate",
"Operator": "LessThan",
"Value": "0.5"
}
Tags
To define a tag filter, enter a value with the form Tags.<key>.
Name (string) -- [REQUIRED]
A resource property name. For example, TrainingJobName. For valid property names, see SearchRecord. You must specify a valid property for the resource.
Operator (string) --
A Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values:
Equals
The value of Name equals Value.
NotEquals
The value of Name doesn't equal Value.
Exists
The Name property exists.
NotExists
The Name property does not exist.
GreaterThan
The value of Name is greater than Value. Not supported for text properties.
GreaterThanOrEqualTo
The value of Name is greater than or equal to Value. Not supported for text properties.
LessThan
The value of Name is less than Value. Not supported for text properties.
LessThanOrEqualTo
The value of Name is less than or equal to Value. Not supported for text properties.
In
The value of Name is one of the comma delimited strings in Value. Only supported for text properties.
Contains
The value of Name contains the string Value. Only supported for text properties.
A SearchExpression can include the Contains operator multiple times when the value of Name is one of the following:
Experiment.DisplayName
Experiment.ExperimentName
Experiment.Tags
Trial.DisplayName
Trial.TrialName
Trial.Tags
TrialComponent.DisplayName
TrialComponent.TrialComponentName
TrialComponent.Tags
TrialComponent.InputArtifacts
TrialComponent.OutputArtifacts
A SearchExpression can include only one Contains operator for all other values of Name. In these cases, if you include multiple Contains operators in the SearchExpression, the result is the following error message: " 'CONTAINS' operator usage limit of 1 exceeded."
Value (string) --
A value used with Name and Operator to determine which resources satisfy the filter's condition. For numerical properties, Value must be an integer or floating-point decimal. For timestamp properties, Value must be an ISO 8601 date-time string of the following format: YYYY-mm-dd'T'HH:MM:SS.
SubExpressions (list) --
A list of search expression objects.
(dict) --
A multi-expression that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results. You must specify at least one subexpression, filter, or nested filter. A SearchExpression can contain up to twenty elements.
A SearchExpression contains the following components:
A list of Filter objects. Each filter defines a simple Boolean expression comprised of a resource property name, Boolean operator, and value.
A list of NestedFilter objects. Each nested filter defines a list of Boolean expressions using a list of resource properties. A nested filter is satisfied if a single object in the list satisfies all Boolean expressions.
A list of SearchExpression objects. A search expression object can be nested in a list of search expression objects.
A Boolean operator: And or Or.
Operator (string) --
A Boolean operator used to evaluate the search expression. If you want every conditional statement in all lists to be satisfied for the entire search expression to be true, specify And. If only a single conditional statement needs to be true for the entire search expression to be true, specify Or. The default value is And.
string
The name of the resource property used to sort the SearchResults. The default is LastModifiedTime.
string
How SearchResults are ordered. Valid values are Ascending or Descending. The default is Descending.
string
If more than MaxResults resources match the specified SearchExpression, the response includes a NextToken. The NextToken can be passed to the next SearchRequest to continue retrieving results.
integer
The maximum number of results to return.
dict
Response Syntax
# This section is too large to render. # Please see the AWS API Documentation linked below.
Response Structure
# This section is too large to render. # Please see the AWS API Documentation linked below.