2023/05/09 - Amazon SageMaker Service - 5 updated api methods
Changes This release includes support for (1) Provisioned Concurrency for Amazon SageMaker Serverless Inference and (2) UpdateEndpointWeightsAndCapacities API for Serverless endpoints.
{'ProductionVariants': {'ServerlessConfig': {'ProvisionedConcurrency': 'integer'}},
'ShadowProductionVariants': {'ServerlessConfig': {'ProvisionedConcurrency': 'integer'}}}
Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want SageMaker to provision. Then you call the CreateEndpoint API.
In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want SageMaker to provision. This includes the number and type of ML compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
See also: AWS API Documentation
Request Syntax
client.create_endpoint_config(
EndpointConfigName='string',
ProductionVariants=[
{
'VariantName': 'string',
'ModelName': 'string',
'InitialInstanceCount': 123,
'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',
'InitialVariantWeight': ...,
'AcceleratorType': 'ml.eia1.medium'|'ml.eia1.large'|'ml.eia1.xlarge'|'ml.eia2.medium'|'ml.eia2.large'|'ml.eia2.xlarge',
'CoreDumpConfig': {
'DestinationS3Uri': 'string',
'KmsKeyId': 'string'
},
'ServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
},
'VolumeSizeInGB': 123,
'ModelDataDownloadTimeoutInSeconds': 123,
'ContainerStartupHealthCheckTimeoutInSeconds': 123,
'EnableSSMAccess': True|False
},
],
DataCaptureConfig={
'EnableCapture': True|False,
'InitialSamplingPercentage': 123,
'DestinationS3Uri': 'string',
'KmsKeyId': 'string',
'CaptureOptions': [
{
'CaptureMode': 'Input'|'Output'
},
],
'CaptureContentTypeHeader': {
'CsvContentTypes': [
'string',
],
'JsonContentTypes': [
'string',
]
}
},
Tags=[
{
'Key': 'string',
'Value': 'string'
},
],
KmsKeyId='string',
AsyncInferenceConfig={
'ClientConfig': {
'MaxConcurrentInvocationsPerInstance': 123
},
'OutputConfig': {
'KmsKeyId': 'string',
'S3OutputPath': 'string',
'NotificationConfig': {
'SuccessTopic': 'string',
'ErrorTopic': 'string',
'IncludeInferenceResponseIn': [
'SUCCESS_NOTIFICATION_TOPIC'|'ERROR_NOTIFICATION_TOPIC',
]
},
'S3FailurePath': 'string'
}
},
ExplainerConfig={
'ClarifyExplainerConfig': {
'EnableExplanations': 'string',
'InferenceConfig': {
'FeaturesAttribute': 'string',
'ContentTemplate': 'string',
'MaxRecordCount': 123,
'MaxPayloadInMB': 123,
'ProbabilityIndex': 123,
'LabelIndex': 123,
'ProbabilityAttribute': 'string',
'LabelAttribute': 'string',
'LabelHeaders': [
'string',
],
'FeatureHeaders': [
'string',
],
'FeatureTypes': [
'numerical'|'categorical'|'text',
]
},
'ShapConfig': {
'ShapBaselineConfig': {
'MimeType': 'string',
'ShapBaseline': 'string',
'ShapBaselineUri': 'string'
},
'NumberOfSamples': 123,
'UseLogit': True|False,
'Seed': 123,
'TextConfig': {
'Language': 'af'|'sq'|'ar'|'hy'|'eu'|'bn'|'bg'|'ca'|'zh'|'hr'|'cs'|'da'|'nl'|'en'|'et'|'fi'|'fr'|'de'|'el'|'gu'|'he'|'hi'|'hu'|'is'|'id'|'ga'|'it'|'kn'|'ky'|'lv'|'lt'|'lb'|'mk'|'ml'|'mr'|'ne'|'nb'|'fa'|'pl'|'pt'|'ro'|'ru'|'sa'|'sr'|'tn'|'si'|'sk'|'sl'|'es'|'sv'|'tl'|'ta'|'tt'|'te'|'tr'|'uk'|'ur'|'yo'|'lij'|'xx',
'Granularity': 'token'|'sentence'|'paragraph'
}
}
}
},
ShadowProductionVariants=[
{
'VariantName': 'string',
'ModelName': 'string',
'InitialInstanceCount': 123,
'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',
'InitialVariantWeight': ...,
'AcceleratorType': 'ml.eia1.medium'|'ml.eia1.large'|'ml.eia1.xlarge'|'ml.eia2.medium'|'ml.eia2.large'|'ml.eia2.xlarge',
'CoreDumpConfig': {
'DestinationS3Uri': 'string',
'KmsKeyId': 'string'
},
'ServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
},
'VolumeSizeInGB': 123,
'ModelDataDownloadTimeoutInSeconds': 123,
'ContainerStartupHealthCheckTimeoutInSeconds': 123,
'EnableSSMAccess': True|False
},
]
)
string
[REQUIRED]
The name of the endpoint configuration. You specify this name in a CreateEndpoint request.
list
[REQUIRED]
An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
(dict) --
Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
VariantName (string) -- [REQUIRED]
The name of the production variant.
ModelName (string) -- [REQUIRED]
The name of the model that you want to host. This is the name that you specified when creating the model.
InitialInstanceCount (integer) --
Number of instances to launch initially.
InstanceType (string) --
The ML compute instance type.
InitialVariantWeight (float) --
Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.
AcceleratorType (string) --
The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
CoreDumpConfig (dict) --
Specifies configuration for a core dump from the model container when the process crashes.
DestinationS3Uri (string) -- [REQUIRED]
The Amazon S3 bucket to send the core dump to.
KmsKeyId (string) --
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID "1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias "alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
ServerlessConfig (dict) --
The serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.
MemorySizeInMB (integer) -- [REQUIRED]
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) -- [REQUIRED]
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
VolumeSizeInGB (integer) --
The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
ModelDataDownloadTimeoutInSeconds (integer) --
The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
ContainerStartupHealthCheckTimeoutInSeconds (integer) --
The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
EnableSSMAccess (boolean) --
You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling UpdateEndpoint.
dict
Configuration to control how SageMaker captures inference data.
EnableCapture (boolean) --
Whether data capture should be enabled or disabled (defaults to enabled).
InitialSamplingPercentage (integer) -- [REQUIRED]
The percentage of requests SageMaker will capture. A lower value is recommended for Endpoints with high traffic.
DestinationS3Uri (string) -- [REQUIRED]
The Amazon S3 location used to capture the data.
KmsKeyId (string) --
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
CaptureOptions (list) -- [REQUIRED]
Specifies data Model Monitor will capture. You can configure whether to collect only input, only output, or both
(dict) --
Specifies data Model Monitor will capture.
CaptureMode (string) -- [REQUIRED]
Specify the boundary of data to capture.
CaptureContentTypeHeader (dict) --
Configuration specifying how to treat different headers. If no headers are specified SageMaker will by default base64 encode when capturing the data.
CsvContentTypes (list) --
The list of all content type headers that SageMaker will treat as CSV and capture accordingly.
(string) --
JsonContentTypes (list) --
The list of all content type headers that SageMaker will treat as JSON and capture accordingly.
(string) --
list
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
(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
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMS
dict
Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.
ClientConfig (dict) --
Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
MaxConcurrentInvocationsPerInstance (integer) --
The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
OutputConfig (dict) -- [REQUIRED]
Specifies the configuration for asynchronous inference invocation outputs.
KmsKeyId (string) --
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
S3OutputPath (string) --
The Amazon S3 location to upload inference responses to.
NotificationConfig (dict) --
Specifies the configuration for notifications of inference results for asynchronous inference.
SuccessTopic (string) --
Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
ErrorTopic (string) --
Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
IncludeInferenceResponseIn (list) --
The Amazon SNS topics where you want the inference response to be included.
(string) --
S3FailurePath (string) --
The Amazon S3 location to upload failure inference responses to.
dict
A member of CreateEndpointConfig that enables explainers.
ClarifyExplainerConfig (dict) --
A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer.
EnableExplanations (string) --
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See `EnableExplanations <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-enable>`__for additional information.
InferenceConfig (dict) --
The inference configuration parameter for the model container.
FeaturesAttribute (string) --
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression 'myfeatures', it extracts a list of features [1,2,3] from request data '{"myfeatures":[1,2,3]}'.
ContentTemplate (string) --
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string '{"myfeatures":$features}' will format a list of features [1,2,3] into the record string '{"myfeatures":[1,2,3]}'. Required only when the model container input is in JSON Lines format.
MaxRecordCount (integer) --
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime.
MaxPayloadInMB (integer) --
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB.
ProbabilityIndex (integer) --
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: '1,0.6', set ProbabilityIndex to 1 to select the probability value 0.6.
Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set ProbabilityIndex to 1 to select the probability values [0.1,0.6,0.3].
LabelIndex (integer) --
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.
Example for a multiclass model: If the model container output consists of label headers followed by probabilities: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set LabelIndex to 0 to select the label headers ['cat','dog','fish'].
ProbabilityAttribute (string) --
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.
Example: If the model container output of a single request is '{"predicted_label":1,"probability":0.6}', then set ProbabilityAttribute to 'probability'.
LabelAttribute (string) --
A JMESPath expression used to locate the list of label headers in the model container output.
Example: If the model container output of a batch request is '{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}', then set LabelAttribute to 'labels' to extract the list of label headers ["cat","dog","fish"]
LabelHeaders (list) --
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter.
(string) --
FeatureHeaders (list) --
The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the Response section under Invoke the endpoint in the Developer Guide for more information.
(string) --
FeatureTypes (list) --
A list of data types of the features (optional). Applicable only to NLP explainability. If provided, FeatureTypes must have at least one 'text' string (for example, ['text']). If FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information.
(string) --
ShapConfig (dict) -- [REQUIRED]
The configuration for SHAP analysis.
ShapBaselineConfig (dict) -- [REQUIRED]
The configuration for the SHAP baseline of the Kernal SHAP algorithm.
MimeType (string) --
The MIME type of the baseline data. Choose from 'text/csv' or 'application/jsonlines'. Defaults to 'text/csv'.
ShapBaseline (string) --
The inline SHAP baseline data in string format. ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity of the TextConfig parameter. The size limit for ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data.
ShapBaselineUri (string) --
The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
NumberOfSamples (integer) --
The number of samples to be used for analysis by the Kernal SHAP algorithm.
UseLogit (boolean) --
A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
Seed (integer) --
The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
TextConfig (dict) --
A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.
Language (string) -- [REQUIRED]
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language.
Granularity (string) -- [REQUIRED]
The unit of granularity for the analysis of text features. For example, if the unit is 'token', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.
list
An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants. If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants.
(dict) --
Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
VariantName (string) -- [REQUIRED]
The name of the production variant.
ModelName (string) -- [REQUIRED]
The name of the model that you want to host. This is the name that you specified when creating the model.
InitialInstanceCount (integer) --
Number of instances to launch initially.
InstanceType (string) --
The ML compute instance type.
InitialVariantWeight (float) --
Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.
AcceleratorType (string) --
The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
CoreDumpConfig (dict) --
Specifies configuration for a core dump from the model container when the process crashes.
DestinationS3Uri (string) -- [REQUIRED]
The Amazon S3 bucket to send the core dump to.
KmsKeyId (string) --
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID "1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias "alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
ServerlessConfig (dict) --
The serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.
MemorySizeInMB (integer) -- [REQUIRED]
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) -- [REQUIRED]
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
VolumeSizeInGB (integer) --
The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
ModelDataDownloadTimeoutInSeconds (integer) --
The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
ContainerStartupHealthCheckTimeoutInSeconds (integer) --
The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
EnableSSMAccess (boolean) --
You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling UpdateEndpoint.
dict
Response Syntax
{
'EndpointConfigArn': 'string'
}
Response Structure
(dict) --
EndpointConfigArn (string) --
The Amazon Resource Name (ARN) of the endpoint configuration.
{'PendingDeploymentSummary': {'ProductionVariants': {'CurrentServerlessConfig': {'ProvisionedConcurrency': 'integer'},
'DesiredServerlessConfig': {'ProvisionedConcurrency': 'integer'}},
'ShadowProductionVariants': {'CurrentServerlessConfig': {'ProvisionedConcurrency': 'integer'},
'DesiredServerlessConfig': {'ProvisionedConcurrency': 'integer'}}},
'ProductionVariants': {'CurrentServerlessConfig': {'ProvisionedConcurrency': 'integer'},
'DesiredServerlessConfig': {'ProvisionedConcurrency': 'integer'}},
'ShadowProductionVariants': {'CurrentServerlessConfig': {'ProvisionedConcurrency': 'integer'},
'DesiredServerlessConfig': {'ProvisionedConcurrency': 'integer'}}}
Returns the description of an endpoint.
See also: AWS API Documentation
Request Syntax
client.describe_endpoint(
EndpointName='string'
)
string
[REQUIRED]
The name of the endpoint.
dict
Response Syntax
{
'EndpointName': 'string',
'EndpointArn': 'string',
'EndpointConfigName': 'string',
'ProductionVariants': [
{
'VariantName': 'string',
'DeployedImages': [
{
'SpecifiedImage': 'string',
'ResolvedImage': 'string',
'ResolutionTime': datetime(2015, 1, 1)
},
],
'CurrentWeight': ...,
'DesiredWeight': ...,
'CurrentInstanceCount': 123,
'DesiredInstanceCount': 123,
'VariantStatus': [
{
'Status': 'Creating'|'Updating'|'Deleting'|'ActivatingTraffic'|'Baking',
'StatusMessage': 'string',
'StartTime': datetime(2015, 1, 1)
},
],
'CurrentServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
},
'DesiredServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
}
},
],
'DataCaptureConfig': {
'EnableCapture': True|False,
'CaptureStatus': 'Started'|'Stopped',
'CurrentSamplingPercentage': 123,
'DestinationS3Uri': 'string',
'KmsKeyId': 'string'
},
'EndpointStatus': 'OutOfService'|'Creating'|'Updating'|'SystemUpdating'|'RollingBack'|'InService'|'Deleting'|'Failed',
'FailureReason': 'string',
'CreationTime': datetime(2015, 1, 1),
'LastModifiedTime': datetime(2015, 1, 1),
'LastDeploymentConfig': {
'BlueGreenUpdatePolicy': {
'TrafficRoutingConfiguration': {
'Type': 'ALL_AT_ONCE'|'CANARY'|'LINEAR',
'WaitIntervalInSeconds': 123,
'CanarySize': {
'Type': 'INSTANCE_COUNT'|'CAPACITY_PERCENT',
'Value': 123
},
'LinearStepSize': {
'Type': 'INSTANCE_COUNT'|'CAPACITY_PERCENT',
'Value': 123
}
},
'TerminationWaitInSeconds': 123,
'MaximumExecutionTimeoutInSeconds': 123
},
'AutoRollbackConfiguration': {
'Alarms': [
{
'AlarmName': 'string'
},
]
}
},
'AsyncInferenceConfig': {
'ClientConfig': {
'MaxConcurrentInvocationsPerInstance': 123
},
'OutputConfig': {
'KmsKeyId': 'string',
'S3OutputPath': 'string',
'NotificationConfig': {
'SuccessTopic': 'string',
'ErrorTopic': 'string',
'IncludeInferenceResponseIn': [
'SUCCESS_NOTIFICATION_TOPIC'|'ERROR_NOTIFICATION_TOPIC',
]
},
'S3FailurePath': 'string'
}
},
'PendingDeploymentSummary': {
'EndpointConfigName': 'string',
'ProductionVariants': [
{
'VariantName': 'string',
'DeployedImages': [
{
'SpecifiedImage': 'string',
'ResolvedImage': 'string',
'ResolutionTime': datetime(2015, 1, 1)
},
],
'CurrentWeight': ...,
'DesiredWeight': ...,
'CurrentInstanceCount': 123,
'DesiredInstanceCount': 123,
'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',
'AcceleratorType': 'ml.eia1.medium'|'ml.eia1.large'|'ml.eia1.xlarge'|'ml.eia2.medium'|'ml.eia2.large'|'ml.eia2.xlarge',
'VariantStatus': [
{
'Status': 'Creating'|'Updating'|'Deleting'|'ActivatingTraffic'|'Baking',
'StatusMessage': 'string',
'StartTime': datetime(2015, 1, 1)
},
],
'CurrentServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
},
'DesiredServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
}
},
],
'StartTime': datetime(2015, 1, 1),
'ShadowProductionVariants': [
{
'VariantName': 'string',
'DeployedImages': [
{
'SpecifiedImage': 'string',
'ResolvedImage': 'string',
'ResolutionTime': datetime(2015, 1, 1)
},
],
'CurrentWeight': ...,
'DesiredWeight': ...,
'CurrentInstanceCount': 123,
'DesiredInstanceCount': 123,
'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',
'AcceleratorType': 'ml.eia1.medium'|'ml.eia1.large'|'ml.eia1.xlarge'|'ml.eia2.medium'|'ml.eia2.large'|'ml.eia2.xlarge',
'VariantStatus': [
{
'Status': 'Creating'|'Updating'|'Deleting'|'ActivatingTraffic'|'Baking',
'StatusMessage': 'string',
'StartTime': datetime(2015, 1, 1)
},
],
'CurrentServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
},
'DesiredServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
}
},
]
},
'ExplainerConfig': {
'ClarifyExplainerConfig': {
'EnableExplanations': 'string',
'InferenceConfig': {
'FeaturesAttribute': 'string',
'ContentTemplate': 'string',
'MaxRecordCount': 123,
'MaxPayloadInMB': 123,
'ProbabilityIndex': 123,
'LabelIndex': 123,
'ProbabilityAttribute': 'string',
'LabelAttribute': 'string',
'LabelHeaders': [
'string',
],
'FeatureHeaders': [
'string',
],
'FeatureTypes': [
'numerical'|'categorical'|'text',
]
},
'ShapConfig': {
'ShapBaselineConfig': {
'MimeType': 'string',
'ShapBaseline': 'string',
'ShapBaselineUri': 'string'
},
'NumberOfSamples': 123,
'UseLogit': True|False,
'Seed': 123,
'TextConfig': {
'Language': 'af'|'sq'|'ar'|'hy'|'eu'|'bn'|'bg'|'ca'|'zh'|'hr'|'cs'|'da'|'nl'|'en'|'et'|'fi'|'fr'|'de'|'el'|'gu'|'he'|'hi'|'hu'|'is'|'id'|'ga'|'it'|'kn'|'ky'|'lv'|'lt'|'lb'|'mk'|'ml'|'mr'|'ne'|'nb'|'fa'|'pl'|'pt'|'ro'|'ru'|'sa'|'sr'|'tn'|'si'|'sk'|'sl'|'es'|'sv'|'tl'|'ta'|'tt'|'te'|'tr'|'uk'|'ur'|'yo'|'lij'|'xx',
'Granularity': 'token'|'sentence'|'paragraph'
}
}
}
},
'ShadowProductionVariants': [
{
'VariantName': 'string',
'DeployedImages': [
{
'SpecifiedImage': 'string',
'ResolvedImage': 'string',
'ResolutionTime': datetime(2015, 1, 1)
},
],
'CurrentWeight': ...,
'DesiredWeight': ...,
'CurrentInstanceCount': 123,
'DesiredInstanceCount': 123,
'VariantStatus': [
{
'Status': 'Creating'|'Updating'|'Deleting'|'ActivatingTraffic'|'Baking',
'StatusMessage': 'string',
'StartTime': datetime(2015, 1, 1)
},
],
'CurrentServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
},
'DesiredServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
}
},
]
}
Response Structure
(dict) --
EndpointName (string) --
Name of the endpoint.
EndpointArn (string) --
The Amazon Resource Name (ARN) of the endpoint.
EndpointConfigName (string) --
The name of the endpoint configuration associated with this endpoint.
ProductionVariants (list) --
An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.
(dict) --
Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities API and the endpoint status is Updating, you get different desired and current values.
VariantName (string) --
The name of the variant.
DeployedImages (list) --
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
(dict) --
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
SpecifiedImage (string) --
The image path you specified when you created the model.
ResolvedImage (string) --
The specific digest path of the image hosted in this ProductionVariant.
ResolutionTime (datetime) --
The date and time when the image path for the model resolved to the ResolvedImage
CurrentWeight (float) --
The weight associated with the variant.
DesiredWeight (float) --
The requested weight, as specified in the UpdateEndpointWeightsAndCapacities request.
CurrentInstanceCount (integer) --
The number of instances associated with the variant.
DesiredInstanceCount (integer) --
The number of instances requested in the UpdateEndpointWeightsAndCapacities request.
VariantStatus (list) --
The endpoint variant status which describes the current deployment stage status or operational status.
(dict) --
Describes the status of the production variant.
Status (string) --
The endpoint variant status which describes the current deployment stage status or operational status.
Creating: Creating inference resources for the production variant.
Deleting: Terminating inference resources for the production variant.
Updating: Updating capacity for the production variant.
ActivatingTraffic: Turning on traffic for the production variant.
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
StatusMessage (string) --
A message that describes the status of the production variant.
StartTime (datetime) --
The start time of the current status change.
CurrentServerlessConfig (dict) --
The serverless configuration for the endpoint.
MemorySizeInMB (integer) --
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) --
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
DesiredServerlessConfig (dict) --
The serverless configuration requested for the endpoint update.
MemorySizeInMB (integer) --
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) --
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
DataCaptureConfig (dict) --
The currently active data capture configuration used by your Endpoint.
EnableCapture (boolean) --
Whether data capture is enabled or disabled.
CaptureStatus (string) --
Whether data capture is currently functional.
CurrentSamplingPercentage (integer) --
The percentage of requests being captured by your Endpoint.
DestinationS3Uri (string) --
The Amazon S3 location being used to capture the data.
KmsKeyId (string) --
The KMS key being used to encrypt the data in Amazon S3.
EndpointStatus (string) --
The status of the endpoint.
OutOfService: Endpoint is not available to take incoming requests.
Creating: CreateEndpoint is executing.
Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService: Endpoint is available to process incoming requests.
Deleting: DeleteEndpoint is executing.
Failed: Endpoint could not be created, updated, or re-scaled. Use the FailureReason value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
FailureReason (string) --
If the status of the endpoint is Failed, the reason why it failed.
CreationTime (datetime) --
A timestamp that shows when the endpoint was created.
LastModifiedTime (datetime) --
A timestamp that shows when the endpoint was last modified.
LastDeploymentConfig (dict) --
The most recent deployment configuration for the endpoint.
BlueGreenUpdatePolicy (dict) --
Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
TrafficRoutingConfiguration (dict) --
Defines the traffic routing strategy to shift traffic from the old fleet to the new fleet during an endpoint deployment.
Type (string) --
Traffic routing strategy type.
ALL_AT_ONCE: Endpoint traffic shifts to the new fleet in a single step.
CANARY: Endpoint traffic shifts to the new fleet in two steps. The first step is the canary, which is a small portion of the traffic. The second step is the remainder of the traffic.
LINEAR: Endpoint traffic shifts to the new fleet in n steps of a configurable size.
WaitIntervalInSeconds (integer) --
The waiting time (in seconds) between incremental steps to turn on traffic on the new endpoint fleet.
CanarySize (dict) --
Batch size for the first step to turn on traffic on the new endpoint fleet. Value must be less than or equal to 50% of the variant's total instance count.
Type (string) --
Specifies the endpoint capacity type.
INSTANCE_COUNT: The endpoint activates based on the number of instances.
CAPACITY_PERCENT: The endpoint activates based on the specified percentage of capacity.
Value (integer) --
Defines the capacity size, either as a number of instances or a capacity percentage.
LinearStepSize (dict) --
Batch size for each step to turn on traffic on the new endpoint fleet. Value must be 10-50% of the variant's total instance count.
Type (string) --
Specifies the endpoint capacity type.
INSTANCE_COUNT: The endpoint activates based on the number of instances.
CAPACITY_PERCENT: The endpoint activates based on the specified percentage of capacity.
Value (integer) --
Defines the capacity size, either as a number of instances or a capacity percentage.
TerminationWaitInSeconds (integer) --
Additional waiting time in seconds after the completion of an endpoint deployment before terminating the old endpoint fleet. Default is 0.
MaximumExecutionTimeoutInSeconds (integer) --
Maximum execution timeout for the deployment. Note that the timeout value should be larger than the total waiting time specified in TerminationWaitInSeconds and WaitIntervalInSeconds.
AutoRollbackConfiguration (dict) --
Automatic rollback configuration for handling endpoint deployment failures and recovery.
Alarms (list) --
List of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment.
(dict) --
An Amazon CloudWatch alarm configured to monitor metrics on an endpoint.
AlarmName (string) --
The name of a CloudWatch alarm in your account.
AsyncInferenceConfig (dict) --
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
ClientConfig (dict) --
Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
MaxConcurrentInvocationsPerInstance (integer) --
The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
OutputConfig (dict) --
Specifies the configuration for asynchronous inference invocation outputs.
KmsKeyId (string) --
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
S3OutputPath (string) --
The Amazon S3 location to upload inference responses to.
NotificationConfig (dict) --
Specifies the configuration for notifications of inference results for asynchronous inference.
SuccessTopic (string) --
Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
ErrorTopic (string) --
Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
IncludeInferenceResponseIn (list) --
The Amazon SNS topics where you want the inference response to be included.
(string) --
S3FailurePath (string) --
The Amazon S3 location to upload failure inference responses to.
PendingDeploymentSummary (dict) --
Returns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.
EndpointConfigName (string) --
The name of the endpoint configuration used in the deployment.
ProductionVariants (list) --
An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.
(dict) --
The production variant summary for a deployment when an endpoint is creating or updating with the CreateEndpoint or UpdateEndpoint operations. Describes the ``VariantStatus ``, weight and capacity for a production variant associated with an endpoint.
VariantName (string) --
The name of the variant.
DeployedImages (list) --
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
(dict) --
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
SpecifiedImage (string) --
The image path you specified when you created the model.
ResolvedImage (string) --
The specific digest path of the image hosted in this ProductionVariant.
ResolutionTime (datetime) --
The date and time when the image path for the model resolved to the ResolvedImage
CurrentWeight (float) --
The weight associated with the variant.
DesiredWeight (float) --
The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
CurrentInstanceCount (integer) --
The number of instances associated with the variant.
DesiredInstanceCount (integer) --
The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
InstanceType (string) --
The type of instances associated with the variant.
AcceleratorType (string) --
The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
VariantStatus (list) --
The endpoint variant status which describes the current deployment stage status or operational status.
(dict) --
Describes the status of the production variant.
Status (string) --
The endpoint variant status which describes the current deployment stage status or operational status.
Creating: Creating inference resources for the production variant.
Deleting: Terminating inference resources for the production variant.
Updating: Updating capacity for the production variant.
ActivatingTraffic: Turning on traffic for the production variant.
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
StatusMessage (string) --
A message that describes the status of the production variant.
StartTime (datetime) --
The start time of the current status change.
CurrentServerlessConfig (dict) --
The serverless configuration for the endpoint.
MemorySizeInMB (integer) --
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) --
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
DesiredServerlessConfig (dict) --
The serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint.
MemorySizeInMB (integer) --
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) --
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
StartTime (datetime) --
The start time of the deployment.
ShadowProductionVariants (list) --
An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants for the in-progress deployment.
(dict) --
The production variant summary for a deployment when an endpoint is creating or updating with the CreateEndpoint or UpdateEndpoint operations. Describes the ``VariantStatus ``, weight and capacity for a production variant associated with an endpoint.
VariantName (string) --
The name of the variant.
DeployedImages (list) --
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
(dict) --
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
SpecifiedImage (string) --
The image path you specified when you created the model.
ResolvedImage (string) --
The specific digest path of the image hosted in this ProductionVariant.
ResolutionTime (datetime) --
The date and time when the image path for the model resolved to the ResolvedImage
CurrentWeight (float) --
The weight associated with the variant.
DesiredWeight (float) --
The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
CurrentInstanceCount (integer) --
The number of instances associated with the variant.
DesiredInstanceCount (integer) --
The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
InstanceType (string) --
The type of instances associated with the variant.
AcceleratorType (string) --
The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
VariantStatus (list) --
The endpoint variant status which describes the current deployment stage status or operational status.
(dict) --
Describes the status of the production variant.
Status (string) --
The endpoint variant status which describes the current deployment stage status or operational status.
Creating: Creating inference resources for the production variant.
Deleting: Terminating inference resources for the production variant.
Updating: Updating capacity for the production variant.
ActivatingTraffic: Turning on traffic for the production variant.
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
StatusMessage (string) --
A message that describes the status of the production variant.
StartTime (datetime) --
The start time of the current status change.
CurrentServerlessConfig (dict) --
The serverless configuration for the endpoint.
MemorySizeInMB (integer) --
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) --
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
DesiredServerlessConfig (dict) --
The serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint.
MemorySizeInMB (integer) --
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) --
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
ExplainerConfig (dict) --
The configuration parameters for an explainer.
ClarifyExplainerConfig (dict) --
A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer.
EnableExplanations (string) --
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See `EnableExplanations <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-enable>`__for additional information.
InferenceConfig (dict) --
The inference configuration parameter for the model container.
FeaturesAttribute (string) --
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression 'myfeatures', it extracts a list of features [1,2,3] from request data '{"myfeatures":[1,2,3]}'.
ContentTemplate (string) --
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string '{"myfeatures":$features}' will format a list of features [1,2,3] into the record string '{"myfeatures":[1,2,3]}'. Required only when the model container input is in JSON Lines format.
MaxRecordCount (integer) --
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime.
MaxPayloadInMB (integer) --
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB.
ProbabilityIndex (integer) --
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: '1,0.6', set ProbabilityIndex to 1 to select the probability value 0.6.
Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set ProbabilityIndex to 1 to select the probability values [0.1,0.6,0.3].
LabelIndex (integer) --
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.
Example for a multiclass model: If the model container output consists of label headers followed by probabilities: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set LabelIndex to 0 to select the label headers ['cat','dog','fish'].
ProbabilityAttribute (string) --
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.
Example: If the model container output of a single request is '{"predicted_label":1,"probability":0.6}', then set ProbabilityAttribute to 'probability'.
LabelAttribute (string) --
A JMESPath expression used to locate the list of label headers in the model container output.
Example: If the model container output of a batch request is '{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}', then set LabelAttribute to 'labels' to extract the list of label headers ["cat","dog","fish"]
LabelHeaders (list) --
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter.
(string) --
FeatureHeaders (list) --
The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the Response section under Invoke the endpoint in the Developer Guide for more information.
(string) --
FeatureTypes (list) --
A list of data types of the features (optional). Applicable only to NLP explainability. If provided, FeatureTypes must have at least one 'text' string (for example, ['text']). If FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information.
(string) --
ShapConfig (dict) --
The configuration for SHAP analysis.
ShapBaselineConfig (dict) --
The configuration for the SHAP baseline of the Kernal SHAP algorithm.
MimeType (string) --
The MIME type of the baseline data. Choose from 'text/csv' or 'application/jsonlines'. Defaults to 'text/csv'.
ShapBaseline (string) --
The inline SHAP baseline data in string format. ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity of the TextConfig parameter. The size limit for ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data.
ShapBaselineUri (string) --
The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
NumberOfSamples (integer) --
The number of samples to be used for analysis by the Kernal SHAP algorithm.
UseLogit (boolean) --
A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
Seed (integer) --
The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
TextConfig (dict) --
A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.
Language (string) --
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language.
Granularity (string) --
The unit of granularity for the analysis of text features. For example, if the unit is 'token', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.
ShadowProductionVariants (list) --
An array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.
(dict) --
Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities API and the endpoint status is Updating, you get different desired and current values.
VariantName (string) --
The name of the variant.
DeployedImages (list) --
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
(dict) --
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
SpecifiedImage (string) --
The image path you specified when you created the model.
ResolvedImage (string) --
The specific digest path of the image hosted in this ProductionVariant.
ResolutionTime (datetime) --
The date and time when the image path for the model resolved to the ResolvedImage
CurrentWeight (float) --
The weight associated with the variant.
DesiredWeight (float) --
The requested weight, as specified in the UpdateEndpointWeightsAndCapacities request.
CurrentInstanceCount (integer) --
The number of instances associated with the variant.
DesiredInstanceCount (integer) --
The number of instances requested in the UpdateEndpointWeightsAndCapacities request.
VariantStatus (list) --
The endpoint variant status which describes the current deployment stage status or operational status.
(dict) --
Describes the status of the production variant.
Status (string) --
The endpoint variant status which describes the current deployment stage status or operational status.
Creating: Creating inference resources for the production variant.
Deleting: Terminating inference resources for the production variant.
Updating: Updating capacity for the production variant.
ActivatingTraffic: Turning on traffic for the production variant.
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
StatusMessage (string) --
A message that describes the status of the production variant.
StartTime (datetime) --
The start time of the current status change.
CurrentServerlessConfig (dict) --
The serverless configuration for the endpoint.
MemorySizeInMB (integer) --
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) --
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
DesiredServerlessConfig (dict) --
The serverless configuration requested for the endpoint update.
MemorySizeInMB (integer) --
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) --
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
{'ProductionVariants': {'ServerlessConfig': {'ProvisionedConcurrency': 'integer'}},
'ShadowProductionVariants': {'ServerlessConfig': {'ProvisionedConcurrency': 'integer'}}}
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
See also: AWS API Documentation
Request Syntax
client.describe_endpoint_config(
EndpointConfigName='string'
)
string
[REQUIRED]
The name of the endpoint configuration.
dict
Response Syntax
{
'EndpointConfigName': 'string',
'EndpointConfigArn': 'string',
'ProductionVariants': [
{
'VariantName': 'string',
'ModelName': 'string',
'InitialInstanceCount': 123,
'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',
'InitialVariantWeight': ...,
'AcceleratorType': 'ml.eia1.medium'|'ml.eia1.large'|'ml.eia1.xlarge'|'ml.eia2.medium'|'ml.eia2.large'|'ml.eia2.xlarge',
'CoreDumpConfig': {
'DestinationS3Uri': 'string',
'KmsKeyId': 'string'
},
'ServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
},
'VolumeSizeInGB': 123,
'ModelDataDownloadTimeoutInSeconds': 123,
'ContainerStartupHealthCheckTimeoutInSeconds': 123,
'EnableSSMAccess': True|False
},
],
'DataCaptureConfig': {
'EnableCapture': True|False,
'InitialSamplingPercentage': 123,
'DestinationS3Uri': 'string',
'KmsKeyId': 'string',
'CaptureOptions': [
{
'CaptureMode': 'Input'|'Output'
},
],
'CaptureContentTypeHeader': {
'CsvContentTypes': [
'string',
],
'JsonContentTypes': [
'string',
]
}
},
'KmsKeyId': 'string',
'CreationTime': datetime(2015, 1, 1),
'AsyncInferenceConfig': {
'ClientConfig': {
'MaxConcurrentInvocationsPerInstance': 123
},
'OutputConfig': {
'KmsKeyId': 'string',
'S3OutputPath': 'string',
'NotificationConfig': {
'SuccessTopic': 'string',
'ErrorTopic': 'string',
'IncludeInferenceResponseIn': [
'SUCCESS_NOTIFICATION_TOPIC'|'ERROR_NOTIFICATION_TOPIC',
]
},
'S3FailurePath': 'string'
}
},
'ExplainerConfig': {
'ClarifyExplainerConfig': {
'EnableExplanations': 'string',
'InferenceConfig': {
'FeaturesAttribute': 'string',
'ContentTemplate': 'string',
'MaxRecordCount': 123,
'MaxPayloadInMB': 123,
'ProbabilityIndex': 123,
'LabelIndex': 123,
'ProbabilityAttribute': 'string',
'LabelAttribute': 'string',
'LabelHeaders': [
'string',
],
'FeatureHeaders': [
'string',
],
'FeatureTypes': [
'numerical'|'categorical'|'text',
]
},
'ShapConfig': {
'ShapBaselineConfig': {
'MimeType': 'string',
'ShapBaseline': 'string',
'ShapBaselineUri': 'string'
},
'NumberOfSamples': 123,
'UseLogit': True|False,
'Seed': 123,
'TextConfig': {
'Language': 'af'|'sq'|'ar'|'hy'|'eu'|'bn'|'bg'|'ca'|'zh'|'hr'|'cs'|'da'|'nl'|'en'|'et'|'fi'|'fr'|'de'|'el'|'gu'|'he'|'hi'|'hu'|'is'|'id'|'ga'|'it'|'kn'|'ky'|'lv'|'lt'|'lb'|'mk'|'ml'|'mr'|'ne'|'nb'|'fa'|'pl'|'pt'|'ro'|'ru'|'sa'|'sr'|'tn'|'si'|'sk'|'sl'|'es'|'sv'|'tl'|'ta'|'tt'|'te'|'tr'|'uk'|'ur'|'yo'|'lij'|'xx',
'Granularity': 'token'|'sentence'|'paragraph'
}
}
}
},
'ShadowProductionVariants': [
{
'VariantName': 'string',
'ModelName': 'string',
'InitialInstanceCount': 123,
'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',
'InitialVariantWeight': ...,
'AcceleratorType': 'ml.eia1.medium'|'ml.eia1.large'|'ml.eia1.xlarge'|'ml.eia2.medium'|'ml.eia2.large'|'ml.eia2.xlarge',
'CoreDumpConfig': {
'DestinationS3Uri': 'string',
'KmsKeyId': 'string'
},
'ServerlessConfig': {
'MemorySizeInMB': 123,
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
},
'VolumeSizeInGB': 123,
'ModelDataDownloadTimeoutInSeconds': 123,
'ContainerStartupHealthCheckTimeoutInSeconds': 123,
'EnableSSMAccess': True|False
},
]
}
Response Structure
(dict) --
EndpointConfigName (string) --
Name of the SageMaker endpoint configuration.
EndpointConfigArn (string) --
The Amazon Resource Name (ARN) of the endpoint configuration.
ProductionVariants (list) --
An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
(dict) --
Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
VariantName (string) --
The name of the production variant.
ModelName (string) --
The name of the model that you want to host. This is the name that you specified when creating the model.
InitialInstanceCount (integer) --
Number of instances to launch initially.
InstanceType (string) --
The ML compute instance type.
InitialVariantWeight (float) --
Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.
AcceleratorType (string) --
The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
CoreDumpConfig (dict) --
Specifies configuration for a core dump from the model container when the process crashes.
DestinationS3Uri (string) --
The Amazon S3 bucket to send the core dump to.
KmsKeyId (string) --
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID "1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias "alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
ServerlessConfig (dict) --
The serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.
MemorySizeInMB (integer) --
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) --
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
VolumeSizeInGB (integer) --
The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
ModelDataDownloadTimeoutInSeconds (integer) --
The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
ContainerStartupHealthCheckTimeoutInSeconds (integer) --
The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
EnableSSMAccess (boolean) --
You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling UpdateEndpoint.
DataCaptureConfig (dict) --
Configuration to control how SageMaker captures inference data.
EnableCapture (boolean) --
Whether data capture should be enabled or disabled (defaults to enabled).
InitialSamplingPercentage (integer) --
The percentage of requests SageMaker will capture. A lower value is recommended for Endpoints with high traffic.
DestinationS3Uri (string) --
The Amazon S3 location used to capture the data.
KmsKeyId (string) --
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
CaptureOptions (list) --
Specifies data Model Monitor will capture. You can configure whether to collect only input, only output, or both
(dict) --
Specifies data Model Monitor will capture.
CaptureMode (string) --
Specify the boundary of data to capture.
CaptureContentTypeHeader (dict) --
Configuration specifying how to treat different headers. If no headers are specified SageMaker will by default base64 encode when capturing the data.
CsvContentTypes (list) --
The list of all content type headers that SageMaker will treat as CSV and capture accordingly.
(string) --
JsonContentTypes (list) --
The list of all content type headers that SageMaker will treat as JSON and capture accordingly.
(string) --
KmsKeyId (string) --
Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
CreationTime (datetime) --
A timestamp that shows when the endpoint configuration was created.
AsyncInferenceConfig (dict) --
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
ClientConfig (dict) --
Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
MaxConcurrentInvocationsPerInstance (integer) --
The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
OutputConfig (dict) --
Specifies the configuration for asynchronous inference invocation outputs.
KmsKeyId (string) --
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
S3OutputPath (string) --
The Amazon S3 location to upload inference responses to.
NotificationConfig (dict) --
Specifies the configuration for notifications of inference results for asynchronous inference.
SuccessTopic (string) --
Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
ErrorTopic (string) --
Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
IncludeInferenceResponseIn (list) --
The Amazon SNS topics where you want the inference response to be included.
(string) --
S3FailurePath (string) --
The Amazon S3 location to upload failure inference responses to.
ExplainerConfig (dict) --
The configuration parameters for an explainer.
ClarifyExplainerConfig (dict) --
A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer.
EnableExplanations (string) --
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See `EnableExplanations <https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-enable>`__for additional information.
InferenceConfig (dict) --
The inference configuration parameter for the model container.
FeaturesAttribute (string) --
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression 'myfeatures', it extracts a list of features [1,2,3] from request data '{"myfeatures":[1,2,3]}'.
ContentTemplate (string) --
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string '{"myfeatures":$features}' will format a list of features [1,2,3] into the record string '{"myfeatures":[1,2,3]}'. Required only when the model container input is in JSON Lines format.
MaxRecordCount (integer) --
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime.
MaxPayloadInMB (integer) --
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB.
ProbabilityIndex (integer) --
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: '1,0.6', set ProbabilityIndex to 1 to select the probability value 0.6.
Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set ProbabilityIndex to 1 to select the probability values [0.1,0.6,0.3].
LabelIndex (integer) --
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.
Example for a multiclass model: If the model container output consists of label headers followed by probabilities: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set LabelIndex to 0 to select the label headers ['cat','dog','fish'].
ProbabilityAttribute (string) --
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.
Example: If the model container output of a single request is '{"predicted_label":1,"probability":0.6}', then set ProbabilityAttribute to 'probability'.
LabelAttribute (string) --
A JMESPath expression used to locate the list of label headers in the model container output.
Example: If the model container output of a batch request is '{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}', then set LabelAttribute to 'labels' to extract the list of label headers ["cat","dog","fish"]
LabelHeaders (list) --
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter.
(string) --
FeatureHeaders (list) --
The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the Response section under Invoke the endpoint in the Developer Guide for more information.
(string) --
FeatureTypes (list) --
A list of data types of the features (optional). Applicable only to NLP explainability. If provided, FeatureTypes must have at least one 'text' string (for example, ['text']). If FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information.
(string) --
ShapConfig (dict) --
The configuration for SHAP analysis.
ShapBaselineConfig (dict) --
The configuration for the SHAP baseline of the Kernal SHAP algorithm.
MimeType (string) --
The MIME type of the baseline data. Choose from 'text/csv' or 'application/jsonlines'. Defaults to 'text/csv'.
ShapBaseline (string) --
The inline SHAP baseline data in string format. ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity of the TextConfig parameter. The size limit for ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data.
ShapBaselineUri (string) --
The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
NumberOfSamples (integer) --
The number of samples to be used for analysis by the Kernal SHAP algorithm.
UseLogit (boolean) --
A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
Seed (integer) --
The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
TextConfig (dict) --
A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.
Language (string) --
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language.
Granularity (string) --
The unit of granularity for the analysis of text features. For example, if the unit is 'token', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.
ShadowProductionVariants (list) --
An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.
(dict) --
Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
VariantName (string) --
The name of the production variant.
ModelName (string) --
The name of the model that you want to host. This is the name that you specified when creating the model.
InitialInstanceCount (integer) --
Number of instances to launch initially.
InstanceType (string) --
The ML compute instance type.
InitialVariantWeight (float) --
Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.
AcceleratorType (string) --
The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
CoreDumpConfig (dict) --
Specifies configuration for a core dump from the model container when the process crashes.
DestinationS3Uri (string) --
The Amazon S3 bucket to send the core dump to.
KmsKeyId (string) --
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID "1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias "alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
ServerlessConfig (dict) --
The serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.
MemorySizeInMB (integer) --
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
MaxConcurrency (integer) --
The maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
VolumeSizeInGB (integer) --
The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
ModelDataDownloadTimeoutInSeconds (integer) --
The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
ContainerStartupHealthCheckTimeoutInSeconds (integer) --
The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
EnableSSMAccess (boolean) --
You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling UpdateEndpoint.
{'Results': {'Endpoint': {'ProductionVariants': {'CurrentServerlessConfig': {'ProvisionedConcurrency': 'integer'},
'DesiredServerlessConfig': {'ProvisionedConcurrency': 'integer'}},
'ShadowProductionVariants': {'CurrentServerlessConfig': {'ProvisionedConcurrency': 'integer'},
'DesiredServerlessConfig': {'ProvisionedConcurrency': 'integer'}}}}}
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.
{'DesiredWeightsAndCapacities': {'ServerlessUpdateConfig': {'MaxConcurrency': 'integer',
'ProvisionedConcurrency': 'integer'}}}
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint. When it receives the request, SageMaker sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.
See also: AWS API Documentation
Request Syntax
client.update_endpoint_weights_and_capacities(
EndpointName='string',
DesiredWeightsAndCapacities=[
{
'VariantName': 'string',
'DesiredWeight': ...,
'DesiredInstanceCount': 123,
'ServerlessUpdateConfig': {
'MaxConcurrency': 123,
'ProvisionedConcurrency': 123
}
},
]
)
string
[REQUIRED]
The name of an existing SageMaker endpoint.
list
[REQUIRED]
An object that provides new capacity and weight values for a variant.
(dict) --
Specifies weight and capacity values for a production variant.
VariantName (string) -- [REQUIRED]
The name of the variant to update.
DesiredWeight (float) --
The variant's weight.
DesiredInstanceCount (integer) --
The variant's capacity.
ServerlessUpdateConfig (dict) --
Specifies the serverless update concurrency configuration for an endpoint variant.
MaxConcurrency (integer) --
The updated maximum number of concurrent invocations your serverless endpoint can process.
ProvisionedConcurrency (integer) --
The updated amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
dict
Response Syntax
{
'EndpointArn': 'string'
}
Response Structure
(dict) --
EndpointArn (string) --
The Amazon Resource Name (ARN) of the updated endpoint.