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Chemins de registre Docker et exemple de code pour Asie Pacifique (Sydney) (ap-southeast-2)
Les rubriques suivantes répertorient les paramètres de chacun des algorithmes et conteneurs Deep Learning Containers qui sont fournis par Amazon SageMaker AI dans cette Région AWS.
Rubriques
AutoGluon (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='autogluon',region='ap-southeast-2',image_scope='inference',version='0.4')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
1.3.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
1.3.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
1.2.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
1.2.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
1.1.1 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
1.1.1 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
1.1.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
1.1.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
1.0.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
1.0.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
0.8.2 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
0.8.2 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
0.7.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
0.7.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
0.6.2 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
0.6.2 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
0.6.1 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
0.6.1 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
0.5.2 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
0.5.2 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
0.4.3 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
0.4.3 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
0.4.2 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
0.4.2 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
0.4.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
0.4.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
0.3.2 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
0.3.2 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<balise> |
0.3.1 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<balise> |
0.3.1 | inférence |
BlazingText (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='blazingtext',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/blazingtext:<balise> |
1 | inférence, entraînement |
Chainer (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='chainer',region='ap-southeast-2',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-chainer:<balise> |
5.0.0 | inférence, entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-chainer:<balise> |
4.1.0 | inférence, entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-chainer:<balise> |
4.0.0 | inférence, entraînement | CPU, GPU | py2, py3 |
Clarify (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='clarify',region='ap-southeast-2',version='1.0',image_scope='processing')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
007051062584.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-clarify-processing:<balise> |
1.0 | traitement |
DJL DeepSpeed (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> |
0.27.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> |
0.26.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> |
0.25.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> |
0.24.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> |
0.23.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> |
0.22.1 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<tag> |
0.21.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<tag> |
0.20.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<tag> |
0.19.0 | inférence |
Data Wrangler (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='data-wrangler',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
422173101802.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-data-wrangler-container:<balise> |
3.x | traitement |
422173101802.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-data-wrangler-container:<balise> |
2.x | traitement |
422173101802.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-data-wrangler-container:<balise> |
1.x | traitement |
Debugger (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='debugger',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
184798709955.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-debugger-rules:<balise> |
dernière | debugger |
DeepAR Forecasting (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='forecasting-deepar',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
514117268639.dkr.ecr.ap-southeast-2.amazonaws.com/forecasting-deepar:<balise> |
1 | inférence, entraînement |
Factorization Machines (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='factorization-machines',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/factorization-machines:<balise> |
1 | inférence, entraînement |
Hugging Face (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='huggingface',region='ap-southeast-2',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.49.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.49.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.48.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.48.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.46.1 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.37.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.36.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.28.1 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.28.1 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.26.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.26.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<balise> |
4.26.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.17.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<balise> |
4.17.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.17.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<balise> |
4.17.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.12.3 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<balise> |
4.12.3 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.12.3 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<balise> |
4.12.3 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.11.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<balise> |
4.11.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.11.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<balise> |
4.11.0 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.10.2 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.10.2 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<balise> |
4.10.2 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<balise> |
4.10.2 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.10.2 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.10.2 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<balise> |
4.10.2 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<balise> |
4.10.2 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.6.1 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.6.1 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.6.1 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<balise> |
4.6.1 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<balise> |
4.6.1 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<balise> |
4.6.1 | inférence |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.5.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<balise> |
4.5.0 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<balise> |
4.4.2 | entraînement |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<balise> |
4.4.2 | entraînement |
IP Insights (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='ipinsights',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/ipinsights:<balise> |
1 | inférence, entraînement |
Classification d’images (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='image-classification',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/image-classification:<balise> |
1 | inférence, entraînement |
Inferentia MXNet (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='inferentia-mxnet',region='ap-southeast-2',version='1.5.1',instance_type='ml.inf1.6xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-mxnet:<balise> |
1.8 | inférence | inf | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-mxnet:<balise> |
1.5.1 | inférence | inf | py3 |
Inferentia PyTorch (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='inferentia-pytorch',region='ap-southeast-2',version='1.9',py_version='py3')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-pytorch:<balise> |
1.9 | inférence | inf | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-pytorch:<balise> |
1.8 | inférence | inf | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-pytorch:<balise> |
1,7 | inférence | inf | py3 |
K-Means (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='kmeans',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/kmeans:<balise> |
1 | inférence, entraînement |
KNN (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='knn',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/knn:<balise> |
1 | inférence, entraînement |
LDA (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='lda',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
297031611018.dkr.ecr.ap-southeast-2.amazonaws.com/lda:<balise> |
1 | inférence, entraînement |
Linear Learner (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='linear-learner',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/linear-learner:<balise> |
1 | inférence, entraînement |
MxNet (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='mxnet',region='ap-southeast-2',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-training:<balise> |
1.9.0 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference:<balise> |
1.9.0 | inférence | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-training:<balise> |
1.8.0 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference:<balise> |
1.8.0 | inférence | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-training:<balise> |
1.7.0 | entraînement | CPU, GPU | py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference:<balise> |
1.7.0 | inférence | CPU, GPU | py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference-eia:<balise> |
1.7.0 | eia | CPU | py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-training:<balise> |
1.6.0 | entraînement | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference:<balise> |
1.6.0 | inférence | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference-eia:<balise> |
1.5.1 | eia | CPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
1.4.1 | entraînement | CPU, GPU | py2 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-training:<balise> |
1.4.1 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet-serving:<balise> |
1.4.1 | inférence | CPU, GPU | py2 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference:<balise> |
1.4.1 | inférence | CPU, GPU | py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference-eia:<balise> |
1.4.1 | eia | CPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
1.4.0 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet-serving:<balise> |
1.4.0 | inférence | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet-serving-eia:<balise> |
1.4.0 | eia | CPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
1.3.0 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
1.3.0 | inférence | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet-eia:<balise> |
1.3.0 | eia | CPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
1.2.1 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
1.2.1 | inférence | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
1.1.0 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
1.1.0 | inférence | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
1.0.0 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
1.0.0 | inférence | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
0.12.1 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<balise> |
0.12.1 | inférence | CPU, GPU | py2, py3 |
MxNet Coach (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='coach-mxnet',region='ap-southeast-2',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<balise> |
0.11.0 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<balise> |
0.11 | entraînement | CPU, GPU | py3 |
Model Monitor (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='model-monitor',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
563025443158.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-model-monitor-analyzer:<balise> |
surveillance |
NTM (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='ntm',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/ntm:<balise> |
1 | inférence, entraînement |
Neo Image Classification (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='image-classification-neo',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/image-classification-neo:<balise> |
dernière | inférence |
Neo MxNet (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='neo-mxnet',region='ap-southeast-2',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-mxnet:<balise> |
1.8 | inférence | CPU, GPU | py3 |
Neo PyTorch (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='neo-pytorch',region='ap-southeast-2',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<balise> |
2.0 | inférence | CPU, GPU | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<balise> |
1.13 | inférence | CPU, GPU | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<balise> |
1.12 | inférence | CPU, GPU | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<balise> |
1.8 | inférence | CPU, GPU | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<balise> |
1,7 | inférence | CPU, GPU | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<balise> |
1.6 | inférence | CPU, GPU | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<balise> |
1.5 | inférence | CPU, GPU | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<balise> |
1.4 | inférence | CPU, GPU | py3 |
Neo Tensorflow (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='neo-tensorflow',region='ap-southeast-2',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-tensorflow:<balise> |
2.9.2 | inférence | CPU, GPU | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-tensorflow:<balise> |
1.15.3 | inférence | CPU, GPU | py3 |
Neo XGBoost (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='xgboost-neo',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/xgboost-neo:<balise> |
dernière | inférence |
Object Detection (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='object-detection',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/object-detection:<balise> |
1 | inférence, entraînement |
Object2Vec (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='object2vec',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/object2vec:<balise> |
1 | inférence, entraînement |
PCA (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='pca',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/pca:<balise> |
1 | inférence, entraînement |
PyTorch (conteneur DLC)
Pour plus d’informations sur les versions de PyTorch prises en charge et non prises en charge, consultez le tableau des politiques de support du cadre dans le Guide du développeur AWS Deep Learning Containers.
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='pytorch',region='ap-southeast-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
2.7.1 | entraînement | CPU, GPU | py312 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
2.6.0 | inférence | CPU, GPU | py312 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
2.6.0 | entraînement | CPU, GPU | py312 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
2.5.1 | inférence | CPU, GPU | py311 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
2.5.1 | entraînement | CPU, GPU | py311 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
2.4.0 | inférence | CPU, GPU | py311 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<balise> |
2.4.0 | inference_graviton | CPU | py311 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
2.4.0 | entraînement | CPU, GPU | py311 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
2.3.0 | inférence | CPU, GPU | py311 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<balise> |
2.3.0 | inference_graviton | CPU | py311 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
2.3.0 | entraînement | CPU, GPU | py311 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<balise> |
2.2.1 | inference_graviton | CPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
2.2.0 | inférence | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
2.2.0 | entraînement | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
2.1.0 | inférence | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<balise> |
2.1.0 | inference_graviton | CPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
2.1.0 | entraînement | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
2.0.1 | inférence | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<balise> |
2.0.1 | inference_graviton | CPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
2.0.1 | entraînement | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
2.0.0 | inférence | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<balise> |
2.0.0 | inference_graviton | CPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
2.0.0 | entraînement | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.13.1 | inférence | CPU, GPU | py39 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.13.1 | entraînement | CPU, GPU | py39 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.12.1 | inférence | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<balise> |
1.12.1 | inference_graviton | CPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.12.1 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.12.0 | inférence | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.12.0 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.11.0 | inférence | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.11.0 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.10.2 | inférence | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.10.2 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.10.0 | inférence | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.10.0 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.9.1 | inférence | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.9.1 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.9.0 | inférence | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.9.0 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.8.1 | inférence | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.8.1 | entraînement | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.8.0 | inférence | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.8.0 | entraînement | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.7.1 | inférence | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.7.1 | entraînement | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.6.0 | inférence | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.6.0 | entraînement | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.5.0 | inférence | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.5.0 | entraînement | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.4.0 | inférence | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.4.0 | entraînement | CPU, GPU | py2, py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-eia:<balise> |
1.3.1 | eia | CPU | py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.3.1 | inférence | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.3.1 | entraînement | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<balise> |
1.2.0 | inférence | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<balise> |
1.2.0 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<balise> |
1.1.0 | inférence | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<balise> |
1.1.0 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<balise> |
1.0.0 | inférence | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<balise> |
1.0.0 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<balise> |
0.4.0 | inférence | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<balise> |
0.4.0 | entraînement | CPU, GPU | py2, py3 |
PyTorch Neuron (DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training-neuron:<balise> |
1.11.0 | entraînement | TRN | py38 |
PyTorch Training Compiler (DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-trcomp-training:<balise> |
1.13.1 | entraînement | GPU | py39 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-trcomp-training:<balise> |
1.12.0 | entraînement | GPU | py38 |
Random Cut Forest (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='randomcutforest',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/randomcutforest:<balise> |
1 | inférence, entraînement |
Ray PyTorch (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='ray-pytorch',region='ap-southeast-2',version='0.8.5',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<balise> |
1.6.0 | entraînement | CPU, GPU | py36 |
462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<balise> |
0.8.5 | entraînement | CPU, GPU | py36 |
Scikit-learn (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='sklearn',region='ap-southeast-2',version='0.23-1',image_scope='inference')
| Chemin de registre | Version | Version du package | Types de tâches (portée de l’image) |
|---|---|---|---|
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<balise> |
1.2-1 | 1.2.1 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<balise> |
1.2-1 | 1.2.1 | entraînement |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<balise> |
1.0-1 | 1.0.2 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<balise> |
1.0-1 | 1.0.2 | entraînement |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<balise> |
1.0-1 | 1.0.2 | inference_graviton |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<balise> |
0.23-1 | 0.23.2 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<balise> |
0.23-1 | 0.23.2 | entraînement |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<balise> |
0.20.0 | 0.20.0 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<balise> |
0.20.0 | 0.20.0 | entraînement |
Semantic Segmentation (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='semantic-segmentation',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/semantic-segmentation:<balise> |
1 | inférence, entraînement |
Seq2Seq (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='seq2seq',region='ap-southeast-2')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/seq2seq:<balise> |
1 | inférence, entraînement |
Spark (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='spark',region='ap-southeast-2',version='3.0',image_scope='processing')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
440695851116.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-spark-processing:<balise> |
3.3 | traitement |
440695851116.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-spark-processing:<balise> |
3.2 | traitement |
440695851116.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-spark-processing:<balise> |
3.1 | traitement |
440695851116.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-spark-processing:<balise> |
3.0 | traitement |
440695851116.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-spark-processing:<balise> |
2.4 | traitement |
SparkML Serving (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='sparkml-serving',region='ap-southeast-2',version='2.4')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-sparkml-serving:<balise> |
3.3 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-sparkml-serving:<balise> |
2.4 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-sparkml-serving:<balise> |
2.2 | inférence |
Tensorflow (conteneur DLC)
Pour plus d’informations sur les versions de TensorFlow prises en charge et non prises en charge, consultez le tableau des politiques de support du cadre dans le Guide du développeur AWS Deep Learning Containers.
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='tensorflow',region='ap-southeast-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.19.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.19.0 | entraînement | CPU, GPU | py312 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.18.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.18.0 | entraînement | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.16.2 | entraînement | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.16.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-graviton:<balise> |
2.16.1 | inference_graviton | CPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.14.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-graviton:<balise> |
2.14.1 | inference_graviton | CPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.14.1 | entraînement | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.13.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-graviton:<balise> |
2.13.0 | inference_graviton | CPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.13.0 | entraînement | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.12.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-graviton:<balise> |
2.12.1 | inference_graviton | CPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.12.0 | entraînement | CPU, GPU | py310 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.11.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.11.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.11.0 | entraînement | CPU, GPU | py39 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.10.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.10.1 | entraînement | CPU, GPU | py39 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.10.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.9.3 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.9.2 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.9.2 | entraînement | CPU, GPU | py39 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-graviton:<balise> |
2.9.1 | inference_graviton | CPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.8.4 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.8.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.8.0 | entraînement | CPU, GPU | py39 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.7.1 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.7.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.6.3 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.6.3 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.6.2 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.6.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.6.0 | entraînement | CPU, GPU | py38 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.5.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.5.1 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.5.0 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.4.3 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.4.3 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.4.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.4.1 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.3.2 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.3.2 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.3.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.3.1 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-eia:<balise> |
2.3.0 | eia | CPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.3.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.3.0 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.2.2 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.2.2 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.2.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.2.1 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.2.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.2.0 | entraînement | CPU, GPU | py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.1.3 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.1.3 | entraînement | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.1.2 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.1.2 | entraînement | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.1.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.1.1 | entraînement | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.1.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.1.0 | entraînement | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.0.4 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.0.4 | entraînement | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.0.3 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.0.3 | entraînement | CPU, GPU | py3, py36 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.0.2 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.0.2 | entraînement | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.0.1 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.0.1 | entraînement | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-eia:<balise> |
2.0.0 | eia | CPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
2.0.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
2.0.0 | entraînement | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
1.15.5 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
1.15.5 | entraînement | CPU, GPU | py3, py36, py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
1.15.4 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
1.15.4 | entraînement | CPU, GPU | py3, py36, py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
1.15.3 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
1.15.3 | entraînement | CPU, GPU | py2, py3, py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
1.15.2 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
1.15.2 | entraînement | CPU, GPU | py2, py3, py37 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-eia:<balise> |
1.15.0 | eia | CPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
1.15.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
1.15.0 | entraînement | CPU, GPU | py2, py3 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-eia:<balise> |
1.14.0 | eia | CPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
1.14.0 | inférence | CPU, GPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
1.14.0 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<balise> |
1.13.1 | entraînement | CPU, GPU | py2 |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<balise> |
1.13.1 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<balise> |
1.13.0 | eia | CPU | - |
763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<balise> |
1.13.0 | inférence | CPU, GPU | - |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<balise> |
1.12.0 | eia | CPU | - |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-serving:<balise> |
1.12.0 | inférence | CPU, GPU | - |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<balise> |
1.12.0 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<balise> |
1.11.0 | eia | CPU | - |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-serving:<balise> |
1.11.0 | inférence | CPU, GPU | - |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<balise> |
1.11.0 | entraînement | CPU, GPU | py2, py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-eia:<balise> |
1.10.0 | eia | CPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.10.0 | inférence | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.10.0 | entraînement | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.9.0 | inférence | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.9.0 | entraînement | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.8.0 | inférence | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.8.0 | entraînement | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.7.0 | inférence | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.7.0 | entraînement | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.6.0 | inférence | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.6.0 | entraînement | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.5.0 | inférence | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.5.0 | entraînement | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.4.1 | inférence | CPU, GPU | py2 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<balise> |
1.4.1 | entraînement | CPU, GPU | py2 |
Tensorflow Coach (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='coach-tensorflow',region='ap-southeast-2',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf<balise> |
1.0.0 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<balise> |
0.11.1 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<balise> |
0.11.0 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<balise> |
0.11 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<balise> |
0.10.1 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<balise> |
0.10 | entraînement | CPU, GPU | py3 |
Tensorflow Inferentia (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='inferentia-tensorflow',region='ap-southeast-2',version='1.15.0',instance_type='ml.inf1.6xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-tensorflow:<balise> |
2.5.2 | inférence | inf | py3 |
355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-tensorflow:<balise> |
1.15.0 | inférence | inf | py3 |
Tensorflow Ray (conteneur DLC)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='ray-tensorflow',region='ap-southeast-2',version='0.8.5',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâches (portée de l’image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<balise> |
1.6.0 | entraînement | CPU, GPU | py37 |
462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<balise> |
0.8.5 | entraînement | CPU, GPU | py36 |
462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<balise> |
0.8.2 | entraînement | CPU, GPU | py36 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<balise> |
0.6.5 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<balise> |
0.6 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<balise> |
0.5.3 | entraînement | CPU, GPU | py3 |
520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<balise> |
0.5 | entraînement | CPU, GPU | py3 |
VW (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='vw',region='ap-southeast-2',version='8.7.0',image_scope='training')
| Chemin de registre | Version | Types de tâches (portée de l’image) |
|---|---|---|
462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<balise> |
8.7.0 | entraînement |
XGBoost (algorithme)
L’exemple suivant du kit SageMaker AI Python SDK montre comment extraire un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='xgboost',region='ap-southeast-2',version='1.5-1')
| Chemin de registre | Version | Version du package | Types de tâches (portée de l’image) |
|---|---|---|---|
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.7-1 | 1.7.4 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.7-1 | 1.7.4 | entraînement |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.5-1 | 1.5.2 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.5-1 | 1.5.2 | entraînement |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.5-1 | 1.5.2 | inference_graviton |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.3-1 | 1.3.3 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.3-1 | 1.3.3 | entraînement |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.3-1 | 1.3.3 | inference_graviton |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.2-2 | 1.2.0 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.2-2 | 1.2.0 | entraînement |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.2-1 | 1.2.0 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.2-1 | 1.2.0 | entraînement |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.0-1 | 1.0.0 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
1.0-1 | 1.0.0 | entraînement |
544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/xgboost:<balise> |
1 | 0.72 | inférence |
544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/xgboost:<balise> |
1 | 0.72 | entraînement |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
0.90-2 | 0.90 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
0.90-2 | 0.90 | entraînement |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
0.90-1 | 0.90 | inférence |
783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<balise> |
0.90-1 | 0.90 | entraînement |
