Die vorliegende Übersetzung wurde maschinell erstellt. Im Falle eines Konflikts oder eines Widerspruchs zwischen dieser übersetzten Fassung und der englischen Fassung (einschließlich infolge von Verzögerungen bei der Übersetzung) ist die englische Fassung maßgeblich.

# Docker-Registry-Pfade und Beispielcode für Europa (Spanien) (eu-south-2)
<a name="ecr-eu-south-2"></a>

In den folgenden Themen sind Parameter für jeden der Algorithmen und Deep-Learning-Container aufgeführt, die Amazon SageMaker AI in diesem Bereich bereitstellt AWS-Region.

**Topics**
+ [AutoGluon (Algorithmus)](#autogluon-eu-south-2)
+ [BlazingText (Algorithmus)](#blazingtext-eu-south-2)
+ [DeepAR-Prognosen (Algorithmus)](#forecasting-deepar-eu-south-2)
+ [Factorization Machines (Algorithmus)](#factorization-machines-eu-south-2)
+ [Hugging Face (Algorithmus)](#huggingface-eu-south-2)
+ [IP Insights (Algorithmus)](#ipinsights-eu-south-2)
+ [Bildklassifizierung (Algorithmus)](#image-classification-eu-south-2)
+ [K-Means (Algorithmus)](#kmeans-eu-south-2)
+ [KNN (Algorithmus)](#knn-eu-south-2)
+ [Linear Learner (Algorithmus)](#linear-learner-eu-south-2)
+ [MXNet (DLC)](#mxnet-eu-south-2)
+ [Model Monitor (Algorithmus)](#model-monitor-eu-south-2)
+ [NTM (Algorithmus)](#ntm-eu-south-2)
+ [Objekterkennung (Algorithmus)](#object-detection-eu-south-2)
+ [Object2Vec (Algorithmus)](#object2vec-eu-south-2)
+ [PCA (Algorithmus)](#pca-eu-south-2)
+ [PyTorch (DLC)](#pytorch-eu-south-2)
+ [PyTorch Neuron (DLC)](#pytorch-neuron-eu-south-2)
+ [PyTorch Training Compiler (DLC)](#pytorch-training-compiler-eu-south-2)
+ [Random Cut Forest (Algorithmus)](#randomcutforest-eu-south-2)
+ [Scikit-learn (Algorithmus)](#sklearn-eu-south-2)
+ [Semantic Segmentation (Algorithmus)](#semantic-segmentation-eu-south-2)
+ [Seq2Seq (Algorithmus)](#seq2seq-eu-south-2)
+ [Spark (Algorithmus)](#spark-eu-south-2)
+ [Tensorflow (DLC)](#tensorflow-eu-south-2)
+ [XGBoost (Algorithmus)](#xgboost-eu-south-2)

## AutoGluon (Algorithmus)
<a name="autogluon-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='eu-south-2',image_scope='inference',version='0.4')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:{{<tag>}} | 0.5.2 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:{{<tag>}} | 0.5.2 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:{{<tag>}} | 0.4.3 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:{{<tag>}} | 0.4.3 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:{{<tag>}} | 0.4.2 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:{{<tag>}} | 0.4.2 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:{{<tag>}} | 0,4,0 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:{{<tag>}} | 0,4,0 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:{{<tag>}} | 0.3.2 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:{{<tag>}} | 0.3.2 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:{{<tag>}} | 0.3.1 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:{{<tag>}} | 0.3.1 | Inferenz | 

## BlazingText (Algorithmus)
<a name="blazingtext-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/blazingtext:{{<tag>}} | 1 | Inferenz, Training | 

## DeepAR-Prognosen (Algorithmus)
<a name="forecasting-deepar-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/forecasting-deepar:{{<tag>}} | 1 | Inferenz, Training | 

## Factorization Machines (Algorithmus)
<a name="factorization-machines-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/factorization-machines:{{<tag>}} | 1 | Inferenz, Training | 

## Hugging Face (Algorithmus)
<a name="huggingface-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='eu-south-2',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4.49.0 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4,48,0 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4,37,0 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4,28,1 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4,26,0 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:{{<tag>}} | 4,26,0 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:{{<tag>}} | 4.17,0 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:{{<tag>}} | 4.17,0 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4.17,0 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:{{<tag>}} | 4.17,0 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:{{<tag>}} | 4.12.3 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:{{<tag>}} | 4.12.3 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4.12.3 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:{{<tag>}} | 4.12.3 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:{{<tag>}} | 4.11.0 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:{{<tag>}} | 4.11.0 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4.11.0 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:{{<tag>}} | 4.11.0 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:{{<tag>}} | 4.10.2 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:{{<tag>}} | 4.10.2 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:{{<tag>}} | 4.10.2 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:{{<tag>}} | 4.10.2 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4.10.2 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4.10.2 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:{{<tag>}} | 4.10.2 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:{{<tag>}} | 4.10.2 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:{{<tag>}} | 4.6.1 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:{{<tag>}} | 4.6.1 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:{{<tag>}} | 4.6.1 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:{{<tag>}} | 4.6.1 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:{{<tag>}} | 4.6.1 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:{{<tag>}} | 4.6.1 | Inferenz | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:{{<tag>}} | 4.5.0 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:{{<tag>}} | 4.5.0 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:{{<tag>}} | 4.4.2 | Training | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:{{<tag>}} | 4.4.2 | Training | 

## IP Insights (Algorithmus)
<a name="ipinsights-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/ipinsights:{{<tag>}} | 1 | Inferenz, Training | 

## Bildklassifizierung (Algorithmus)
<a name="image-classification-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/image-classification:{{<tag>}} | 1 | Inferenz, Training | 

## K-Means (Algorithmus)
<a name="kmeans-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/kmeans:{{<tag>}} | 1 | Inferenz, Training | 

## KNN (Algorithmus)
<a name="knn-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/knn:{{<tag>}} | 1 | Inferenz, Training | 

## Linear Learner (Algorithmus)
<a name="linear-learner-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/linear-learner:{{<tag>}} | 1 | Inferenz, Training | 

## MXNet (DLC)
<a name="mxnet-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='eu-south-2',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| Registry-Pfad | Version | Auftragstypen (Bildbereich) | Typen von Prozessoren | Python Versionen | 
| --- | --- | --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-training:{{<tag>}} | 1.9.0 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference:{{<tag>}} | 1.9.0 | Inferenz | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-training:{{<tag>}} | 1.8.0 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference:{{<tag>}} | 1.8.0 | Inferenz | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-training:{{<tag>}} | 1.7.0 | Training | CPU, GPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference:{{<tag>}} | 1.7.0 | Inferenz | CPU, GPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference-eia:{{<tag>}} | 1.7.0 | eia | CPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-training:{{<tag>}} | 1.6.0 | Training | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference:{{<tag>}} | 1.6.0 | Inferenz | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference-eia:{{<tag>}} | 1.5.1 | eia | CPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-training:{{<tag>}} | 1.4.1 | Training | CPU, GPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference:{{<tag>}} | 1.4.1 | Inferenz | CPU, GPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference-eia:{{<tag>}} | 1.4.1 | eia | CPU | py2, py3 | 

## Model Monitor (Algorithmus)
<a name="model-monitor-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 437450045455.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-model-monitor-analyzer:{{<tag>}} |  | Überwachung | 

## NTM (Algorithmus)
<a name="ntm-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/ntm:{{<tag>}} | 1 | Inferenz, Training | 

## Objekterkennung (Algorithmus)
<a name="object-detection-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/object-detection:{{<tag>}} | 1 | Inferenz, Training | 

## Object2Vec (Algorithmus)
<a name="object2vec-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/object2vec:{{<tag>}} | 1 | Inferenz, Training | 

## PCA (Algorithmus)
<a name="pca-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/pca:{{<tag>}} | 1 | Inferenz, Training | 

## PyTorch (DLC)
<a name="pytorch-eu-south-2"></a>

Informationen zu den unterstützten und nicht unterstützten PyTorch Versionen finden Sie in der [Framework-Support-Richtlinientabelle](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html) im *AWS Deep Learning Containers Developer Guide*.

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='eu-south-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| Registry-Pfad | Version | Auftragstypen (Bildbereich) | Typen von Prozessoren | Python Versionen | 
| --- | --- | --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 2.7.1 | Training | CPU, GPU | py312 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 2.6.0 | Inferenz | CPU, GPU | py312 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 2.6.0 | Training | CPU, GPU | py312 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 2.5.1 | Inferenz | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 2.5.1 | Training | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 2.4.0 | Inferenz | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:{{<tag>}} | 2.4.0 | inference\_graviton | CPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 2.4.0 | Training | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 2.3.0 | Inferenz | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:{{<tag>}} | 2.3.0 | inference\_graviton | CPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 2.3.0 | Training | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:{{<tag>}} | 2.2.1 | inference\_graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 2.2.0 | Inferenz | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 2.2.0 | Training | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 2.1.0 | Inferenz | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:{{<tag>}} | 2.1.0 | inference\_graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 2.1.0 | Training | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 2.0.1 | Inferenz | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:{{<tag>}} | 2.0.1 | inference\_graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 2.0.1 | Training | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 2.0.0 | Inferenz | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:{{<tag>}} | 2.0.0 | inference\_graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 2.0.0 | Training | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.13.1 | Inferenz | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.13.1 | Training | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.12.1 | Inferenz | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:{{<tag>}} | 1.12.1 | inference\_graviton | CPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.12.1 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.12.0 | Inferenz | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.12.0 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.11.0 | Inferenz | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.11.0 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.10.2 | Inferenz | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.10.2 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.10.0 | Inferenz | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.10.0 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.9.1 | Inferenz | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.9.1 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.9.0 | Inferenz | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.9.0 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.8.1 | Inferenz | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.8.1 | Training | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.8.0 | Inferenz | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.8.0 | Training | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.7.1 | Inferenz | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.7.1 | Training | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.6.0 | Inferenz | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.6.0 | Training | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-eia:{{<tag>}} | 1.5.1 | eia | CPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.5.0 | Inferenz | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.5.0 | Training | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.4.0 | Inferenz | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.4.0 | Training | CPU, GPU | py2, py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-eia:{{<tag>}} | 1.3.1 | eia | CPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.3.1 | Inferenz | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.3.1 | Training | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:{{<tag>}} | 1.2.0 | Inferenz | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:{{<tag>}} | 1.2.0 | Training | CPU, GPU | py2, py3 | 

## PyTorch Neuron (DLC)
<a name="pytorch-neuron-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| Registry-Pfad | Version | Auftragstypen (Bildbereich) | Typen von Prozessoren | Python Versionen | 
| --- | --- | --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training-neuron:{{<tag>}} | 1.11.0 | Training | DREHEN | py38 | 

## PyTorch Training Compiler (DLC)
<a name="pytorch-training-compiler-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| Registry-Pfad | Version | Auftragstypen (Bildbereich) | Typen von Prozessoren | Python Versionen | 
| --- | --- | --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-trcomp-training:{{<tag>}} | 1.12.0 | Training | GPU | py38 | 

## Random Cut Forest (Algorithmus)
<a name="randomcutforest-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/randomcutforest:{{<tag>}} | 1 | Inferenz, Training | 

## Scikit-learn (Algorithmus)
<a name="sklearn-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='eu-south-2',version='0.23-1',image_scope='inference')
```


| Registry-Pfad | Version | Version Package | Auftragstypen (Bildbereich) | 
| --- | --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:{{<tag>}} | 1.2-1 | 1.2.1 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:{{<tag>}} | 1,2-1 | 1.2.1 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:{{<tag>}} | 1,0-1 | 1.0.2 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:{{<tag>}} | 1,0-1 | 1.0.2 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:{{<tag>}} | 1,0-1 | 1.0.2 | inference\_graviton | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:{{<tag>}} | 0,23-1 | 0,23,2 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:{{<tag>}} | 0,23-1 | 0,23,2 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:{{<tag>}} | 0,20,0 | 0,20,0 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:{{<tag>}} | 0,20,0 | 0,20,0 | Training | 

## Semantic Segmentation (Algorithmus)
<a name="semantic-segmentation-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/semantic-segmentation:{{<tag>}} | 1 | Inferenz, Training | 

## Seq2Seq (Algorithmus)
<a name="seq2seq-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='eu-south-2')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/seq2seq:{{<tag>}} | 1 | Inferenz, Training | 

## Spark (Algorithmus)
<a name="spark-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='eu-south-2',version='3.0',image_scope='processing')
```


| Registry-Pfad | Version | Jobtypen (Bildbereich) | 
| --- | --- | --- | 
| 833944533722.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-spark-processing:{{<tag>}} | 3.3 | Verarbeitung | 
| 833944533722.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-spark-processing:{{<tag>}} | 3.2 | Verarbeitung | 
| 833944533722.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-spark-processing:{{<tag>}} | 3.1 | Verarbeitung | 
| 833944533722.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-spark-processing:{{<tag>}} | 3.0 | Verarbeitung | 
| 833944533722.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-spark-processing:{{<tag>}} | 2.4 | Verarbeitung | 

## Tensorflow (DLC)
<a name="tensorflow-eu-south-2"></a>

Informationen zu den unterstützten und nicht unterstützten TensorFlow Versionen finden Sie in der [Framework-Support-Richtlinientabelle](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html) im *AWS Deep Learning Containers Developer Guide*.

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='eu-south-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| Registry-Pfad | Version | Auftragstypen (Bildbereich) | Typen von Prozessoren | Python Versionen | 
| --- | --- | --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.19.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.19.0 | Training | CPU, GPU | py312 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.18.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.18.0 | Training | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.16.2 | Training | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.16.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-graviton:{{<tag>}} | 2.16.1 | inference\_graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.14.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-graviton:{{<tag>}} | 2.14.1 | inference\_graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.14.1 | Training | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.13.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-graviton:{{<tag>}} | 2.13.0 | inference\_graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.13.0 | Training | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.12.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-graviton:{{<tag>}} | 2.12.1 | inference\_graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.12.0 | Training | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.11.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.11.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.11.0 | Training | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.10.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.10.1 | Training | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.10.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.9.3 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.9.2 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.9.2 | Training | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-graviton:{{<tag>}} | 2.9.1 | inference\_graviton | CPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.8.4 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.8.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.8.0 | Training | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.7.1 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.7.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.6.3 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.6.3 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.6.2 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.6.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.6.0 | Training | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.5.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.5.1 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.5.0 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.4.3 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.4.3 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.4.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.4.1 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.3.2 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.3.2 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.3.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.3.1 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-eia:{{<tag>}} | 2.3.0 | eia | CPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.3.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.3.0 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.2.2 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.2.2 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.2.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.2.1 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.2.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.2.0 | Training | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.1.3 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.1.3 | Training | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.1.2 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.1.2 | Training | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.1.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.1.1 | Training | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.1.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.1.0 | Training | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.0.4 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.0.4 | Training | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.0.3 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.0.3 | Training | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.0.2 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.0.2 | Training | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.0.1 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.0.1 | Training | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-eia:{{<tag>}} | 2.0.0 | eia | CPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 2.0.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 2.0.0 | Training | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 1.15,5 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 1,1,5 | Training | CPU, GPU | py3, py36, py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 1.15,4 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 1.15,4 | Training | CPU, GPU | py3, py36, py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 1.15,3 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 1.15,3 | Training | CPU, GPU | py2, py3, py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 1.15.2 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 1.15.2 | Training | CPU, GPU | py2, py3, py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-eia:{{<tag>}} | 1.15.0 | eia | CPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 1.15.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 1.15.0 | Training | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-eia:{{<tag>}} | 1.14.0 | eia | CPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 1.14.0 | Inferenz | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 1.14.0 | Training | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:{{<tag>}} | 1.13.1 | Training | CPU, GPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:{{<tag>}} | 1.13.0 | Inferenz | CPU, GPU | - | 

## XGBoost (Algorithmus)
<a name="xgboost-eu-south-2"></a>

Das folgende SageMaker AI-Python-SDK-Beispiel zeigt, wie ein bestimmter Registrierungspfad abgerufen wird.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='eu-south-2',version='1.5-1')
```


| Registry-Pfad | Version | Version Package | Auftragstypen (Bildbereich) | 
| --- | --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1.7-1 | 1,7.4 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,7-1 | 1,7.4 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,5-1 | 1.5.2 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,5-1 | 1.5.2 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,5-1 | 1.5.2 | inference\_graviton | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,3-1 | 1.3.3 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,3-1 | 1.3.3 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,3-1 | 1.3.3 | inference\_graviton | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,2-2 | 1.2.0 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,2-2 | 1.2.0 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,2-1 | 1.2.0 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,2-1 | 1.2.0 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,0-1 | 1.0.0 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 1,0-1 | 1.0.0 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/xgboost:{{<tag>}} | 1 | 0,72 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/xgboost:{{<tag>}} | 1 | 0,72 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 0,90-2 | 0.90 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 0,90-2 | 0.90 | Training | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 0,90-1 | 0.90 | Inferenz | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:{{<tag>}} | 0,90-1 | 0.90 | Training |