TrainingJobDefinition
import type { TrainingJobDefinition } from "https://aws-api.deno.dev/v0.3/services/sagemaker.ts?docs=full";
Defines the input needed to run a training job using the algorithm.
§Properties
The hyperparameters used for the training job.
the path to the S3 bucket where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.
The resources, including the ML compute instances and ML storage volumes, to use for model training.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.