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Package to programmatically access a RIME deployment

Project description

RIME SDK

The RIME SDK provides an interface to RIME backend services for starting and viewing the progress of RIME stress test jobs. There are four objects available in the rime_sdk package:

  • RIMEClient
  • RIMEStressTestJob
  • RIMEProject
  • CustomImage

To use these objects, import them from the package like so:

from rime_sdk import RIMEClient, RIMEStressTestJob, RIMEProject, CustomImage

These calls will throw a ValueError if there are connection issues or arguments are malformed.

RIMEClient

The RIMEClient provides an interface to RIME's backend services for creating projects, starting stress test jobs, and querying the backend for current stress test jobs. To initialize the RIMEClient, provide the address of your RIME instance.

rime_client = RIMEClient("my_vpc.rime.com", "api-key")

start_stress_test()

This allows you to start an AI Stress Testing job on the RIME backend.

Arguments:

  • test_run_config: dict Specifies paths to the model and dataset to be used in stress testing.
  • project_id: Optional[str] = None Specify the project to file the stress test result under. If omitted, the stress test result will be stored in the default project.
  • custom_image: Optional[CustomImage] = None Specify a custom Docker image to run the stress test job on. This image could include custom libraries that your model depends on. If no custom image is provided, the backend will use the default image specified by the cluster configuration.

Return Value:

A RIMEStressTestJob object that provides an interface for monitoring the job in the backend.

Example:

# This example will likely not work for you because it requires permissions to a specific S3 bucket.
# This demonstrates how you might specify such a configuration.
config = {
  "run_name": "Titanic", 
  "data_info": { 
    "label_col": "Survived", 
    "ref_path": "s3://rime-datasets/titanic/titanic_example.csv", "eval_path": "s3://rime-datasets/titanic/titanic_example.csv" 
  }, 
  "model_info": {
    "path": "s3://rime-models/titanic_s3_test/titanic_example_model.py"
  }
}
# Run the job using the specified config and the default Docker image in the RIME backend.
# Store the results under project ID "foo"
job = rime_client.start_stress_test_job(test_run_config=config, project_id="foo")

create_project()

Projects allow you to organize stress test runs as you see fit. A natural way to organize stress test runs is to create a project for each specific ML task, such as predicting whether a transaction is fradulent.

Arguments:

  • name: str The name of the project. You can change this later in the UI.
  • description: str A short blurb about the project.

Return Value:

A RIMEProject that describes the created project. Its project_id attribute can be used in start_stress_test() and list_stress_test_jobs().

Example:

project = rime_client.create_project(name='foo', description='bar')

list_stress_test_jobs()

Query the backend for a list of jobs filtered by status and project ID. This is a good way to recover RIMEStressTestJob objects. Note that this only returns jobs from the last two days, because the time-to-live of job objects in the backend is set at two days.

Arguments:

  • status_filters: Optional[List[str]] = None

    Select jobs by a union of statuses. If this is omitted, jobs will not be filtered by status. Acceptable values are in the following array:

    ['UNKNOWN_JOB_STATUS', 'PENDING', 'RUNNING', 'FAILING', 'SUCCEEDED']
    
  • project_id: Optional[str] = None Select jobs by project. If this is omitted, jobs from across different projects will be returned.

Return Value:

A list of RIMEStressTestJob objects. These are not guaranteed to be in any sorted order.

Example:

# Get all running and succeeded jobs for project 'foo'
jobs = rime_client.list_stress_test_jobs(status_filters=['RUNNING', 'SUCCEEDED'], project_id='foo')

RIMEStressTestJob

This object provides an interface for monitoring the status of a stress test job in the RIME backend.

get_status()

Query the RIME backend for the job's status. This includes flags for blocking until the job is complete and printing information to stdout.

Arguments:

  • verbose: bool = False Whether to print additional status information to stdout. If this flag is enabled and the job status is 'SUCCEEDED' or 'FAILING', the logs of the testing engine will be dumped to stdout to help with debuggability. Note that this logs have no strict form and will be subject to significant change in future versions.
  • wait_until_finish: bool = False Whether to block until the job status is 'SUCCEEDED' or 'FAILING'. If verbose is enabled too, the job status will be printed to stdout every poll_rate_sec.
  • poll_rate_sec: float = 5.0 How often to ping the RIME backend services for the status of the job. Units are in seconds.

Return Value:

A dictionary representing the status of the RIMEStressTestJob.

{
	"name": str
	"type": str
	"status": str
	"start_time_secs": int64
	"running_time_secs": double
}

type will be an element in the following array:

['MODEL_STRESS_TEST', 'UNKNOWN_JOB_TYPE']

status will be an element in the following array:

['UNKNOWN_JOB_STATUS', 'PENDING', 'RUNNING', 'FAILING', 'SUCCEEDED']

Example:

# Block until this job is finished and dump monitoring info to stdout.
job_status = job.get_status(verbose=True, wait_until_finish=True)

RIMEProject

This object describes a project in the RIME backend.

Attributes:

  • project_id: str How to refer to the project in the backend. Use this attribute to specify the project for the backend in start_stress_test_job() and list_stress_test_jobs().
  • name: str
  • description: str

CustomImage

This allows users to specify custom Docker images on which their stress test jobs will be run. An example use case is if you need a particular version of a library or an additional dependency to run your model.

Attributes:

  • name: str The name and tag of the Docker image. This should specify exactly which image to pull.
  • pull_secret: CustomImage.PullSecret If you need a particular registry credential to pull the specified Docker image, add the pull secret field to tell the RIME backend cluster which secret to use. This secret will already need to be stored in the cluster.

Example:

custom_image = CustomImage(name="company/testing-engine-with-xgboost:latest", pull_secret=CustomImage.PullSecret(name="my_secret_name"))

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