pulumi-aws-kotlin/com.pulumi.aws.sagemaker.kotlin/SagemakerFunctions/getPrebuiltEcrImage

getPrebuiltEcrImage

suspend fun getPrebuiltEcrImage(argument: GetPrebuiltEcrImagePlainArgs): GetPrebuiltEcrImageResult

Get information about prebuilt Amazon SageMaker AI Docker images.

NOTE: The AWS provider creates a validly constructed registry_path but does not verify that the registry_path corresponds to an existing image. For example, using a registry_path containing an image_tag that does not correspond to a Docker image in the ECR repository, will result in an error.

Example Usage

Basic usage:

import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";
const test = aws.sagemaker.getPrebuiltEcrImage({
    repositoryName: "sagemaker-scikit-learn",
    imageTag: "2.2-1.0.11.0",
});
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import pulumi
import pulumi_aws as aws
test = aws.sagemaker.get_prebuilt_ecr_image(repository_name="sagemaker-scikit-learn",
    image_tag="2.2-1.0.11.0")
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using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;
return await Deployment.RunAsync(() =>
{
    var test = Aws.Sagemaker.GetPrebuiltEcrImage.Invoke(new()
    {
        RepositoryName = "sagemaker-scikit-learn",
        ImageTag = "2.2-1.0.11.0",
    });
});
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package main
import (
	"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/sagemaker"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := sagemaker.GetPrebuiltEcrImage(ctx, &sagemaker.GetPrebuiltEcrImageArgs{
			RepositoryName: "sagemaker-scikit-learn",
			ImageTag:       pulumi.StringRef("2.2-1.0.11.0"),
		}, nil)
		if err != nil {
			return err
		}
		return nil
	})
}
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package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.sagemaker.SagemakerFunctions;
import com.pulumi.aws.sagemaker.inputs.GetPrebuiltEcrImageArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }
    public static void stack(Context ctx) {
        final var test = SagemakerFunctions.getPrebuiltEcrImage(GetPrebuiltEcrImageArgs.builder()
            .repositoryName("sagemaker-scikit-learn")
            .imageTag("2.2-1.0.11.0")
            .build());
    }
}
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variables:
  test:
    fn::invoke:
      function: aws:sagemaker:getPrebuiltEcrImage
      arguments:
        repositoryName: sagemaker-scikit-learn
        imageTag: 2.2-1.0.11.0
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Return

A collection of values returned by getPrebuiltEcrImage.

Parameters

argument

A collection of arguments for invoking getPrebuiltEcrImage.

suspend fun getPrebuiltEcrImage(dnsSuffix: String? = null, imageTag: String? = null, region: String? = null, repositoryName: String): GetPrebuiltEcrImageResult

Return

A collection of values returned by getPrebuiltEcrImage.

Parameters

dnsSuffix

DNS suffix to use in the registry path. If not specified, the AWS provider sets it to the DNS suffix for the current region.

imageTag

Image tag for the Docker image. If not specified, the AWS provider sets the value to 1, which for many repositories indicates the latest version. Some repositories, such as XGBoost, do not support 1 or latest and specific version must be used.

region

Region to use in the registry path. If not specified, the AWS provider sets it to the current region.

repositoryName

Name of the repository, which is generally the algorithm or library. Values include autogluon-inference, autogluon-training, blazingtext, djl-inference, factorization-machines, forecasting-deepar, huggingface-pytorch-inference, huggingface-pytorch-inference-neuron, huggingface-pytorch-inference-neuronx, huggingface-pytorch-tgi-inference, huggingface-pytorch-training, huggingface-pytorch-training-neuronx, huggingface-pytorch-trcomp-training, huggingface-tensorflow-inference, huggingface-tensorflow-training, huggingface-tensorflow-trcomp-training, image-classification, image-classification-neo, ipinsights, kmeans, knn, lda, linear-learner, mxnet-inference, mxnet-inference-eia, mxnet-training, ntm, object-detection, object2vec, pca, pytorch-inference, pytorch-inference-eia, pytorch-inference-graviton, pytorch-inference-neuronx, pytorch-training, pytorch-training-neuronx, pytorch-trcomp-training, randomcutforest, sagemaker-base-python, sagemaker-chainer, sagemaker-clarify-processing, sagemaker-data-wrangler-container, sagemaker-debugger-rules, sagemaker-geospatial-v1-0, sagemaker-inference-mxnet, sagemaker-inference-pytorch, sagemaker-inference-tensorflow, sagemaker-model-monitor-analyzer, sagemaker-mxnet, sagemaker-mxnet-eia, sagemaker-mxnet-serving, sagemaker-mxnet-serving-eia, sagemaker-neo-mxnet, sagemaker-neo-pytorch, sagemaker-neo-tensorflow, sagemaker-pytorch, sagemaker-rl-coach-container, sagemaker-rl-mxnet, sagemaker-rl-ray-container, sagemaker-rl-tensorflow, sagemaker-rl-vw-container, sagemaker-scikit-learn, sagemaker-spark-processing, sagemaker-sparkml-serving, sagemaker-tensorflow, sagemaker-tensorflow-eia, sagemaker-tensorflow-scriptmode, sagemaker-tensorflow-serving, sagemaker-tensorflow-serving-eia, sagemaker-tritonserver, sagemaker-xgboost, semantic-segmentation, seq2seq, stabilityai-pytorch-inference, tei, tei-cpu, tensorflow-inference, tensorflow-inference-eia, tensorflow-inference-graviton, tensorflow-training, and xgboost-neo.

See also

.

suspend fun getPrebuiltEcrImage(argument: suspend GetPrebuiltEcrImagePlainArgsBuilder.() -> Unit): GetPrebuiltEcrImageResult

Return

A collection of values returned by getPrebuiltEcrImage.

Parameters

argument

Builder for com.pulumi.aws.sagemaker.kotlin.inputs.GetPrebuiltEcrImagePlainArgs.

See also

.