LocalSagemakerClient: A SageMakerClient that implements the API calls locally.

In DyfanJones/sagemaker-r-local: Sagemaker core classes, methods and functions

A SageMakerClient that implements the API calls locally.

Description

Used for doing local training and hosting local endpoints. It still needs access to a boto client to interact with S3 but it won't perform any SageMaker call. Implements the methods with the same signature as the boto SageMakerClient.

Methods

Public methods

• LocalSagemakerClient$new()

• LocalSagemakerClient$create_processing_job()

• LocalSagemakerClient$describe_processing_job()

• LocalSagemakerClient$create_training_job()

• LocalSagemakerClient$describe_training_job()

• LocalSagemakerClient$create_transform_job()

• LocalSagemakerClient$describe_transform_job()

• LocalSagemakerClient$create_model()

• LocalSagemakerClient$describe_model()

• LocalSagemakerClient$describe_endpoint_config()

• LocalSagemakerClient$create_endpoint_config()

• LocalSagemakerClient$describe_endpoint()

• LocalSagemakerClient$create_endpoint()

• LocalSagemakerClient$update_endpoint()

• LocalSagemakerClient$delete_endpoint()

• LocalSagemakerClient$delete_endpoint_config()

• LocalSagemakerClient$delete_model()

• LocalSagemakerClient$clone()

---

Method new()

Initialize a LocalSageMakerClient.

Usage

LocalSagemakerClient$new(sagemaker_session = NULL)

Arguments

sagemaker_session

(sagemaker.session.Session): a session to use to read configurations from, and use its boto client.

---

Method create_processing_job()

Creates a processing job in Local Mode

Usage

LocalSagemakerClient$create_processing_job(
  ProcessingJobName,
  AppSpecification,
  ProcessingResources,
  Environment = NULL,
  ProcessingInputs = NULL,
  ProcessingOutputConfig = NULL,
  ...
)

Arguments

ProcessingJobName

(str): local processing job name.

AppSpecification

(dict): Identifies the container and application to run.

ProcessingResources

(dict): Identifies the resources to use for local processing.

Environment

(dict, optional): Describes the environment variables to pass to the container. (Default value = None)

ProcessingInputs

(dict, optional): Describes the processing input data. (Default value = None)

ProcessingOutputConfig

(dict, optional): Describes the processing output configuration. (Default value = None)

...

: Keyword arguments

---

Method describe_processing_job()

Describes a local processing job.

Usage

LocalSagemakerClient$describe_processing_job(ProcessingJobName)

Arguments

ProcessingJobName

(str): Processing job name to describe.

Returns

(dict) DescribeProcessingJob Response.

---

Method create_training_job()

Create a training job in Local Mode.

Usage

LocalSagemakerClient$create_training_job(
  TrainingJobName,
  AlgorithmSpecification,
  OutputDataConfig,
  ResourceConfig,
  InputDataConfig = NULL,
  ...
)

Arguments

TrainingJobName

(str): local training job name.

AlgorithmSpecification

(dict): Identifies the training algorithm to use.

OutputDataConfig

(dict): Identifies the location where you want to save the results of model training.

ResourceConfig

(dict): Identifies the resources to use for local model training.

InputDataConfig

(dict, optional): Describes the training dataset and the location where it is stored. (Default value = None)

...

: Variables added to hyperparameters

HyperParameters

(dict) [optional]: Specifies these algorithm-specific parameters to influence the quality of the final model.

---

Method describe_training_job()

Describe a local training job.

Usage

LocalSagemakerClient$describe_training_job(TrainingJobName)

Arguments

TrainingJobName

(str): Training job name to describe.

Returns

(dict) DescribeTrainingJob Response.

---

Method create_transform_job()

Create the transform job.

Usage

LocalSagemakerClient$create_transform_job(
  TransformJobName,
  ModelName,
  TransformInput,
  TransformOutput,
  TransformResources,
  ...
)

Arguments

TransformJobName

(str):

ModelName

(str):

TransformInput

(str):

TransformOutput

(str):

TransformResources

(str):

...

(obj):

---

Method describe_transform_job()

Describe the transform job.

Usage

LocalSagemakerClient$describe_transform_job(TransformJobName)

Arguments

TransformJobName

(str):

---

Method create_model()

Create a Local Model Object.

Usage

LocalSagemakerClient$create_model(ModelName, PrimaryContainer, ...)

Arguments

ModelName

(str): the Model Name

PrimaryContainer

(dict): a SageMaker primary container definition

...

(obj):

---

Method describe_model()

Describe the model.

Usage

LocalSagemakerClient$describe_model(ModelName)

Arguments

ModelName

(str):

---

Method describe_endpoint_config()

Describe the endpoint configuration.

Usage

LocalSagemakerClient$describe_endpoint_config(EndpointConfigName)

Arguments

EndpointConfigName

(str):

---

Method create_endpoint_config()

Create the endpoint configuration.

Usage

LocalSagemakerClient$create_endpoint_config(
  EndpointConfigName,
  ProductionVariants,
  Tags = NULL
)

Arguments

EndpointConfigName

(str):

ProductionVariants

(str):

Tags

: (Default value = NULL)

---

Method describe_endpoint()

Describe the endpoint.

Usage

LocalSagemakerClient$describe_endpoint(EndpointName)

Arguments

EndpointName

(str):

---

Method create_endpoint()

Create the endpoint.

Usage

LocalSagemakerClient$create_endpoint(
  EndpointName,
  EndpointConfigName,
  Tags = NULL
)

Arguments

EndpointName

(str):

EndpointConfigName

(str):

Tags

: (Default value = None)

---

Method update_endpoint()

Update the endpoint.

Usage

LocalSagemakerClient$update_endpoint(EndpointName, EndpointConfigName)

Arguments

EndpointName

(str):

EndpointConfigName

(str):

---

Method delete_endpoint()

Delete the endpoint.

Usage

LocalSagemakerClient$delete_endpoint(EndpointName)

Arguments

EndpointName

(str):

---

Method delete_endpoint_config()

Delete the endpoint configuration.

Usage

LocalSagemakerClient$delete_endpoint_config(EndpointConfigName)

Arguments

EndpointConfigName

(str):

---

Method delete_model()

Delete the model.

Usage

LocalSagemakerClient$delete_model(ModelName)

Arguments

ModelName

(str):

---

Method clone()

The objects of this class are cloneable with this method.

Usage

LocalSagemakerClient$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

DyfanJones/sagemaker-r-local documentation built on June 14, 2022, 10:32 p.m.