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Chemins de registre Docker et exemple de code pour Afrique (Le Cap) (af-south-1)
Les rubriques suivantes répertorient les paramètres de chacun des algorithmes et conteneurs de deep learning fournis par Amazon SageMaker AI dans ce document Région AWS.
Rubriques
AutoGluon (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='autogluon',region='af-south-1',image_scope='inference',version='0.4')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
1.3.0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
1.3.0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
1.2.0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
1.2.0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
1.1.1 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
1.1.1 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
1.1.0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
1.1.0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
1.0.0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
1.0.0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
0.8.2 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
0.8.2 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
0.7.0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
0.7.0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
0.6.2 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
0.6.2 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
0.6.1 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
0.6.1 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
0,5.2 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
0,5.2 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
0,4.3 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
0,4.3 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
0,4.2 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
0,4.2 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
0,4,0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
0,4,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
0,3.2 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
0,3.2 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<tag> |
0,3.1 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<tag> |
0,3.1 | inférence |
BlazingText (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='blazingtext',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/blazingtext:<tag> |
1 | inférence, entraînement |
Chainer (conteneur DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='chainer',region='af-south-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-chainer:<tag> |
5.0.0 | inférence, entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-chainer:<tag> |
4.1.0 | inférence, entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-chainer:<tag> |
4.0.0 | inférence, entraînement | CPU, GPU | py2, py3 |
Clarify (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='clarify',region='af-south-1',version='1.0',image_scope='processing')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
811711786498.dkr.ecr.af-south-1.amazonaws.com/sagemaker-clarify-processing:<tag> |
1.0 | traitement |
DJL DeepSpeed (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer 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) |
|---|---|---|
626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference: 0.27.0-deep speed 0.12.6-cu 121- <tag> |
0,27,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference: 0.26.0-deep speed 0.12.6-cu 121- <tag> |
0,26,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference: 0.25.0-deep speed 0.11.0-cu118- <tag> |
0,25,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference: 0.24.0-deepspeed0.10.0-cu118- <tag> |
0,24,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference: 0,23,0 - vitesse profonde 0,9,5 - cu118- <tag> |
0,23,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference: 0.22.1-deepspeed0.9.2-cu118- <tag> |
0,22,1 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference: 0.21.0-deepspeed0.8.3-cu117- <tag> |
0,21,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference: 0,20,0 - vitesse profonde 0,7,5 - cu116- <tag> |
0,20,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference: 0.19.0-deepspeed0.7.3-cu113- <tag> |
0,19,0 | inférence |
Data Wrangler (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='data-wrangler',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
143210264188.dkr.ecr.af-south-1.amazonaws.com/sagemaker-data-wrangler-container:<tag> |
3.x | traitement |
143210264188.dkr.ecr.af-south-1.amazonaws.com/sagemaker-data-wrangler-container:<tag> |
2.x | traitement |
143210264188.dkr.ecr.af-south-1.amazonaws.com/sagemaker-data-wrangler-container:<tag> |
1.x | traitement |
Debugger (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='debugger',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
314341159256.dkr.ecr.af-south-1.amazonaws.com/sagemaker-debugger-rules:<tag> |
dernière | debugger |
DeepAR Forecasting (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='forecasting-deepar',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/forecasting-deepar:<tag> |
1 | inférence, entraînement |
Factorization Machines (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='factorization-machines',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/factorization-machines:<tag> |
1 | inférence, entraînement |
Hugging Face (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='huggingface',region='af-south-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,49,0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,49,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,48,0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,48,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,46.1 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,37,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,36,0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.28.1 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4.28.1 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,26,0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,26,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4,26,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,17,0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4,17,0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,17,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4,17,0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.12.3 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.12.3 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4.12.3 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4.12.3 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.11.0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.11.0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4.11.0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4.11.0 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.10.2 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.10.2 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.10.2 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.10.2 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4.10.2 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4.10.2 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4.10.2 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4.10.2 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.6.1 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.6.1 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.6.1 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.6.1 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4.6.1 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4.6.1 | inférence |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.5.0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.5.0 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.4.2 | entraînement |
626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.4.2 | entraînement |
IP Insights (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='ipinsights',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/ipinsights:<tag> |
1 | inférence, entraînement |
Image classification (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='image-classification',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/image-classification:<tag> |
1 | inférence, entraînement |
Inferentia MXNet (DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='inferentia-mxnet',region='af-south-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-mxnet:<tag> |
1.8 | inférence | inf | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-mxnet:<tag> |
1.5.1 | inférence | inf | py3 |
Inferentia PyTorch (DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='inferentia-pytorch',region='af-south-1',version='1.9',py_version='py3')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-pytorch:<tag> |
1.9 | inférence | inf | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-pytorch:<tag> |
1.8 | inférence | inf | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-pytorch:<tag> |
1,7 | inférence | inf | py3 |
K-Means (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='kmeans',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/kmeans:<tag> |
1 | inférence, entraînement |
KNN (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='knn',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/knn:<tag> |
1 | inférence, entraînement |
Linear Learner (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='linear-learner',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/linear-learner:<tag> |
1 | inférence, entraînement |
MXNet (DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='mxnet',region='af-south-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-training:<tag> |
1.9.0 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference:<tag> |
1.9.0 | inférence | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-training:<tag> |
1.8.0 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference:<tag> |
1.8.0 | inférence | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-training:<tag> |
1.7.0 | entraînement | CPU, GPU | py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference:<tag> |
1.7.0 | inférence | CPU, GPU | py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference-eia:<tag> |
1.7.0 | eia | CPU | py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-training:<tag> |
1.6.0 | entraînement | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference:<tag> |
1.6.0 | inférence | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference-eia:<tag> |
1.5.1 | eia | CPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.4.1 | entraînement | CPU, GPU | py2 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-training:<tag> |
1.4.1 | entraînement | CPU, GPU | py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet-serving:<tag> |
1.4.1 | inférence | CPU, GPU | py2 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference:<tag> |
1.4.1 | inférence | CPU, GPU | py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference-eia:<tag> |
1.4.1 | eia | CPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.4.0 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet-serving:<tag> |
1.4.0 | inférence | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet-serving-eia:<tag> |
1.4.0 | eia | CPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.3.0 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.3.0 | inférence | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet-eia:<tag> |
1.3.0 | eia | CPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.2.1 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.2.1 | inférence | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.1.0 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.1.0 | inférence | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.0.0 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.0.0 | inférence | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
0.12.1 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<tag> |
0.12.1 | inférence | CPU, GPU | py2, py3 |
MXNet Entraîneur (DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='coach-mxnet',region='af-south-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-mxnet: coach 0.11.0- <tag> |
0.11.0 | entraînement | CPU, GPU | py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-mxnet: coach 0.11- <tag> |
0,11 | entraînement | CPU, GPU | py3 |
Model Monitor (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='model-monitor',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
875698925577.dkr.ecr.af-south-1.amazonaws.com/sagemaker-model-monitor-analyzer:<tag> |
surveillance |
NTM (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='ntm',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/ntm:<tag> |
1 | inférence, entraînement |
Neo Image Classification (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='image-classification-neo',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
774647643957.dkr.ecr.af-south-1.amazonaws.com/image-classification-neo:<tag> |
dernières | inférence |
Néo MXNet (DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='neo-mxnet',region='af-south-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-mxnet:<tag> |
1.8 | inférence | CPU, GPU | py3 |
Néo PyTorch (DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='neo-pytorch',region='af-south-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
2.0 | inférence | CPU, GPU | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.13 | inférence | CPU, GPU | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.12 | inférence | CPU, GPU | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.8 | inférence | CPU, GPU | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1,7 | inférence | CPU, GPU | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.6 | inférence | CPU, GPU | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.5 | inférence | CPU, GPU | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.4 | inférence | CPU, GPU | py3 |
Neo Tensorflow (conteneur DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='neo-tensorflow',region='af-south-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-tensorflow:<tag> |
2.9.2 | inférence | CPU, GPU | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-tensorflow:<tag> |
1.15.3 | inférence | CPU, GPU | py3 |
Neo XGBoost (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='xgboost-neo',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
774647643957.dkr.ecr.af-south-1.amazonaws.com/xgboost-neo:<tag> |
dernières | inférence |
Object Detection (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='object-detection',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/object-detection:<tag> |
1 | inférence, entraînement |
Object2Vec (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='object2vec',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/object2vec:<tag> |
1 | inférence, entraînement |
PCA (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='pca',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/pca:<tag> |
1 | inférence, entraînement |
PyTorch (DLC)
Pour plus d'informations sur les PyTorch versions prises en charge et non prises en charge, consultez le tableau des politiques de support du Framework dans le guide du développeur de AWS Deep Learning Containers.
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='pytorch',region='af-south-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
2.7.1 | entraînement | CPU, GPU | py312 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
2.6.0 | inférence | CPU, GPU | py312 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
2.6.0 | entraînement | CPU, GPU | py312 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
2.5.1 | inférence | CPU, GPU | py311 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
2.5.1 | entraînement | CPU, GPU | py311 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
2.4.0 | inférence | CPU, GPU | py311 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.4.0 | inference_graviton | CPU | py311 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
2.4.0 | entraînement | CPU, GPU | py311 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
2.3.0 | inférence | CPU, GPU | py311 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.3.0 | inference_graviton | CPU | py311 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
2.3.0 | entraînement | CPU, GPU | py311 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.2.1 | inference_graviton | CPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
2.2.0 | inférence | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
2.2.0 | entraînement | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
2.1.0 | inférence | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.1.0 | inference_graviton | CPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
2.1.0 | entraînement | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
2.0.1 | inférence | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.0.1 | inference_graviton | CPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
2.0.1 | entraînement | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
2.0.0 | inférence | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.0.0 | inference_graviton | CPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
2.0.0 | entraînement | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.13.1 | inférence | CPU, GPU | py39 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.13.1 | entraînement | CPU, GPU | py39 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.12.1 | inférence | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<tag> |
1.12.1 | inference_graviton | CPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.12.1 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.12.0 | inférence | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.12.0 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.11.0 | inférence | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.11.0 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.10.2 | inférence | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.10.2 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.10.0 | inférence | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.10.0 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.9.1 | inférence | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.9.1 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.9.0 | inférence | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.9.0 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.8.1 | inférence | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.8.1 | entraînement | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.8.0 | inférence | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.8.0 | entraînement | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.7.1 | inférence | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.7.1 | entraînement | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.6.0 | inférence | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.6.0 | entraînement | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.5.0 | inférence | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.5.0 | entraînement | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.4.0 | inférence | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.4.0 | entraînement | CPU, GPU | py2, py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.3.1 | inférence | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.3.1 | entraînement | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<tag> |
1.2.0 | inférence | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<tag> |
1.2.0 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<tag> |
1.1.0 | inférence | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<tag> |
1.1.0 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<tag> |
1.0.0 | inférence | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<tag> |
1.0.0 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<tag> |
0,4,0 | inférence | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<tag> |
0,4,0 | entraînement | CPU, GPU | py2, py3 |
PyTorch Compilateur d'entraînement (DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer 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 tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-trcomp-training:<tag> |
1.13.1 | entraînement | GPU | py39 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-trcomp-training:<tag> |
1.12.0 | entraînement | GPU | py38 |
Random Cut Forest (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='randomcutforest',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/randomcutforest:<tag> |
1 | inférence, entraînement |
Scikit-learn (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='sklearn',region='af-south-1',version='0.23-1',image_scope='inference')
| Chemin de registre | Version | Version du package | Types de tâches (portée de l'image) |
|---|---|---|---|
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,2-1 | 1.2.1 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,2-1 | 1.2.1 | entraînement |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,0-1 | 1.0.2 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,0-1 | 1.0.2 | entraînement |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,0-1 | 1.0.2 | inference_graviton |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,23-1 | 0,23,2 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,23-1 | 0,23,2 | entraînement |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,20,0 | 0,20,0 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,20,0 | 0,20,0 | entraînement |
Semantic Segmentation (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='semantic-segmentation',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/semantic-segmentation:<tag> |
1 | inférence, entraînement |
Seq2Seq (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='seq2seq',region='af-south-1')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
455444449433.dkr.ecr.af-south-1.amazonaws.com/seq2seq:<tag> |
1 | inférence, entraînement |
Spark (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='spark',region='af-south-1',version='3.0',image_scope='processing')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
309385258863.dkr.ecr.af-south-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.3 | traitement |
309385258863.dkr.ecr.af-south-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.2 | traitement |
309385258863.dkr.ecr.af-south-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.1 | traitement |
309385258863.dkr.ecr.af-south-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.0 | traitement |
309385258863.dkr.ecr.af-south-1.amazonaws.com/sagemaker-spark-processing:<tag> |
2,4 | traitement |
SparkML Serving (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='sparkml-serving',region='af-south-1',version='2.4')
| Chemin de registre | Version | Types de tâches (portée de l'image) |
|---|---|---|
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-sparkml-serving:<tag> |
3.3 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-sparkml-serving:<tag> |
2,4 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-sparkml-serving:<tag> |
2.2 | inférence |
Tensorflow (conteneur DLC)
Pour plus d'informations sur les TensorFlow versions prises en charge et non prises en charge, consultez le tableau des politiques de support du Framework dans le guide du développeur de AWS Deep Learning Containers.
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='tensorflow',region='af-south-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.19.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.19.0 | entraînement | CPU, GPU | py312 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.18.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.18.0 | entraînement | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.16,2 | entraînement | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.16.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2.16.1 | inference_graviton | CPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.14.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2.14.1 | inference_graviton | CPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.14.1 | entraînement | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.13.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2.13.0 | inference_graviton | CPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.13.0 | entraînement | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.12.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2.12.1 | inference_graviton | CPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.12.0 | entraînement | CPU, GPU | py310 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.11.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.11.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.11.0 | entraînement | CPU, GPU | py39 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.10.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.10.1 | entraînement | CPU, GPU | py39 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.10.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.9.3 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.9.2 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.9.2 | entraînement | CPU, GPU | py39 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2.9.1 | inference_graviton | CPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.8.4 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.8.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.8.0 | entraînement | CPU, GPU | py39 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.7.1 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.7.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.6.3 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.6.3 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.6.2 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.6.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.6.0 | entraînement | CPU, GPU | py38 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.5.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.5.1 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.5.0 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.4.3 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.4.3 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.4.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.4.1 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.3.2 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.3.2 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.3.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.3.1 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-eia:<tag> |
2.3.0 | eia | CPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.3.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.3.0 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.2.2 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.2.2 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.2.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.2.1 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.2.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.2.0 | entraînement | CPU, GPU | py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.3 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.1.3 | entraînement | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.2 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.1.2 | entraînement | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.1.1 | entraînement | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.1.0 | entraînement | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.4 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.0.4 | entraînement | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.3 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.0.3 | entraînement | CPU, GPU | py3, py36 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.2 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.0.2 | entraînement | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.1 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.0.1 | entraînement | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-eia:<tag> |
2.0.0 | eia | CPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
2.0.0 | entraînement | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
1,1,5 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
1,1,5 | entraînement | CPU, GPU | py3, py36, py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
1.15.4 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
1.15.4 | entraînement | CPU, GPU | py3, py36, py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
1.15.3 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
1.15.3 | entraînement | CPU, GPU | py2, py3, py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
1.15.2 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
1.15.2 | entraînement | CPU, GPU | py2, py3, py37 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-eia:<tag> |
1.15.0 | eia | CPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
1.15.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
1.15.0 | entraînement | CPU, GPU | py2, py3 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-eia:<tag> |
1.14.0 | eia | CPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
1.14.0 | inférence | CPU, GPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
1.14.0 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<tag> |
1.13.1 | entraînement | CPU, GPU | py2 |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<tag> |
1.13.1 | entraînement | CPU, GPU | py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<tag> |
1.13.0 | eia | CPU | - |
626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<tag> |
1.13.0 | inférence | CPU, GPU | - |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<tag> |
1.12.0 | eia | CPU | - |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-serving:<tag> |
1.12.0 | inférence | CPU, GPU | - |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<tag> |
1.12.0 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<tag> |
1.11.0 | eia | CPU | - |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-serving:<tag> |
1.11.0 | inférence | CPU, GPU | - |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<tag> |
1.11.0 | entraînement | CPU, GPU | py2, py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-eia:<tag> |
1.10.0 | eia | CPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.10.0 | inférence | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.10.0 | entraînement | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.9.0 | inférence | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.9.0 | entraînement | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.8.0 | inférence | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.8.0 | entraînement | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.7.0 | inférence | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.7.0 | entraînement | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.6.0 | inférence | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.6.0 | entraînement | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.5.0 | inférence | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.5.0 | entraînement | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.4.1 | inférence | CPU, GPU | py2 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.4.1 | entraînement | CPU, GPU | py2 |
Tensorflow Coach (conteneur DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='coach-tensorflow',region='af-south-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow: coach 0.11.1- <tag> |
0.11.1 | entraînement | CPU, GPU | py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow: coach 0.11.0- <tag> |
0.11.0 | entraînement | CPU, GPU | py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow: coach 0.11- <tag> |
0,11 | entraînement | CPU, GPU | py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow: coach 0.10.1- <tag> |
0,1,1 | entraînement | CPU, GPU | py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow: coach 0.10- <tag> |
0.10 | entraînement | CPU, GPU | py3 |
Tensorflow Inferentia (conteneur DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='inferentia-tensorflow',region='af-south-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-tensorflow:<tag> |
2.5.2 | inférence | inf | py3 |
774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-tensorflow:<tag> |
1.15.0 | inférence | inf | py3 |
Tensorflow Ray (conteneur DLC)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='ray-tensorflow',region='af-south-1',version='0.8.5',instance_type='ml.c5.4xlarge')
| Chemin de registre | Version | Types de tâche (portée de l'image) | Types de processeur | Versions de Python |
|---|---|---|---|---|
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5- <tag> |
0,6,5 | entraînement | CPU, GPU | py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6- <tag> |
0.6 | entraînement | CPU, GPU | py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3- <tag> |
0,5.3 | entraînement | CPU, GPU | py3 |
313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5- <tag> |
0.5 | entraînement | CPU, GPU | py3 |
XGBoost (algorithme)
L'exemple de SDK SageMaker AI Python suivant montre comment récupérer un chemin de registre spécifique.
from sagemaker import image_uris image_uris.retrieve(framework='xgboost',region='af-south-1',version='1.5-1')
| Chemin de registre | Version | Version du package | Types de tâches (portée de l'image) |
|---|---|---|---|
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,7-1 | 1.7.4 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,7-1 | 1.7.4 | entraînement |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,5-1 | 1.5.2 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,5-1 | 1.5.2 | entraînement |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,5-1 | 1.5.2 | inference_graviton |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1.3-1 | 1.3.3 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1.3-1 | 1.3.3 | entraînement |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1.3-1 | 1.3.3 | inference_graviton |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1.2-2 | 1.2.0 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1.2-2 | 1.2.0 | entraînement |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,2-1 | 1.2.0 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,2-1 | 1.2.0 | entraînement |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,0-1 | 1.0.0 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,0-1 | 1.0.0 | entraînement |
455444449433.dkr.ecr.af-south-1.amazonaws.com/xgboost:<tag> |
1 | 0,72 | inférence |
455444449433.dkr.ecr.af-south-1.amazonaws.com/xgboost:<tag> |
1 | 0,72 | entraînement |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-2 | 0.90 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-2 | 0.90 | entraînement |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-1 | 0.90 | inférence |
510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-1 | 0.90 | entraînement |
