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Percorsi di registro Docker e codice di esempio per il Medio Oriente (Emirati Arabi Uniti) (me-central-1)
I seguenti argomenti elencano i parametri per ciascuno degli algoritmi e contenitori di deep learning forniti da Amazon SageMaker AI in questo Regione AWS contesto.
Argomenti
AutoGluon (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='autogluon',region='me-central-1',image_scope='inference',version='0.4')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<tag> |
0.5.2 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<tag> |
0,5,2 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<tag> |
0,4,3 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<tag> |
0,4,3 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<tag> |
0,4,2 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<tag> |
0,4,2 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<tag> |
0,40 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<tag> |
0,40 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<tag> |
0,32 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<tag> |
0,32 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<tag> |
0,31 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<tag> |
0,31 | Inferenza |
BlazingText (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='blazingtext',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/blazingtext:<tag> |
1 | inferenza, addestramento |
Previsioni DeepAR (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='forecasting-deepar',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/forecasting-deepar:<tag> |
1 | inferenza, addestramento |
Macchine di fattorizzazione (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='factorization-machines',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/factorization-machines:<tag> |
1 | inferenza, addestramento |
Hugging Face (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='huggingface',region='me-central-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.49.0 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,49,0 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,48,0 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,48,0 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,46,1 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,37,0 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,36,0 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,28,1 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,28,1 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,26,0 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,26,0 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4,26,0 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,17,0 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4,17,0 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,17,0 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4,17,0 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,12,3 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4,12,3 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,12,3 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4,12,3 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.11.0 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.11.0 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4.11.0 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4.11.0 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
410.2 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
410.2 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
410.2 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
410.2 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
410.2 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
410.2 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
410.2 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
410.2 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
46.1 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.6.1 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.6.1 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.6.1 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4.6.1 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4.6.1 | Inferenza |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.5.0 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.5.0 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.4.2 | addestramento |
914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.4.2 | addestramento |
IP Insights (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='ipinsights',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/ipinsights:<tag> |
1 | inferenza, addestramento |
Classificazione delle immagini (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='image-classification',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/image-classification:<tag> |
1 | inferenza, addestramento |
K-Means (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='kmeans',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/kmeans:<tag> |
1 | inferenza, addestramento |
KNN (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='knn',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/knn:<tag> |
1 | inferenza, addestramento |
Linear Learner (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='linear-learner',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/linear-learner:<tag> |
1 | inferenza, addestramento |
MXNet (DLC)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='mxnet',region='me-central-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-training:<tag> |
1.9.0 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference:<tag> |
1.9.0 | inferenza | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-training:<tag> |
1.8.0 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference:<tag> |
1.8.0 | inferenza | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-training:<tag> |
1.7.0 | addestramento | CPU, GPU | py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference:<tag> |
1.7.0 | inferenza | CPU, GPU | py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference-eia:<tag> |
1.7.0 | eia | CPU | py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-training:<tag> |
1.6.0 | addestramento | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference:<tag> |
1.6.0 | inferenza | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference-eia:<tag> |
1.5.1 | eia | CPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-training:<tag> |
1.4.1 | addestramento | CPU, GPU | py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference:<tag> |
1.4.1 | inferenza | CPU, GPU | py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference-eia:<tag> |
1.4.1 | eia | CPU | py2, py3 |
Monitoraggio modelli (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='model-monitor',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
588750061953.dkr.ecr.me-central-1.amazonaws.com/sagemaker-model-monitor-analyzer:<tag> |
monitoraggio |
NTM (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='ntm',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/ntm:<tag> |
1 | inferenza, addestramento |
Rilevamento degli oggetti (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='object-detection',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/object-detection:<tag> |
1 | inferenza, addestramento |
Object2Vec (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='object2vec',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/object2vec:<tag> |
1 | inferenza, addestramento |
PCA (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='pca',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/pca:<tag> |
1 | inferenza, addestramento |
PyTorch (DLC)
Per informazioni sulle PyTorch versioni supportate e non supportate, consulta la tabella dei criteri di supporto del Framework nella AWS Deep Learning Containers Developer Guide.
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='pytorch',region='me-central-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
2.7.1 | addestramento | CPU, GPU | py312 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
2.6.0 | inferenza | CPU, GPU | py312 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
2.6.0 | addestramento | CPU, GPU | py312 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
2.5.1 | inferenza | CPU, GPU | py311 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
2.5.1 | addestramento | CPU, GPU | py311 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
2.4.0 | Inferenza | CPU, GPU | py311 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.4.0 | inference_graviton | CPU | py311 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
2.4.0 | addestramento | CPU, GPU | py311 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
2.3.0 | inferenza | CPU, GPU | py311 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.3.0 | inference_graviton | CPU | py311 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
2.3.0 | addestramento | CPU, GPU | py311 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.2.1 | inference_graviton | CPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
2.2.0 | inferenza | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
2.2.0 | addestramento | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
2.1.0 | inferenza | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.1.0 | inference_graviton | CPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
2.1.0 | addestramento | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
2.0.1 | inferenza | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.0.1 | inference_graviton | CPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
2.0.1 | addestramento | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
2.0.0 | inferenza | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.0.0 | inference_graviton | CPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
2.0.0 | addestramento | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.13.1 | inferenza | CPU, GPU | py39 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.13.1 | addestramento | CPU, GPU | py39 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.12.1 | inferenza | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<tag> |
1.12.1 | inference_graviton | CPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.12.1 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.12.0 | inferenza | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.12.0 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.11.0 | inferenza | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.11.0 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.10.2 | inferenza | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.10.2 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.10.0 | inferenza | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.10.0 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.9.1 | inferenza | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.9.1 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.9.0 | inferenza | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.9.0 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.8.1 | inferenza | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.8.1 | addestramento | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.8.0 | inferenza | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.8.0 | addestramento | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.7.1 | inferenza | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.7.1 | addestramento | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.6.0 | inferenza | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.6.0 | addestramento | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.5.0 | inferenza | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.5.0 | addestramento | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.4.0 | inferenza | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.4.0 | addestramento | CPU, GPU | py2, py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.3.1 | inferenza | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.3.1 | addestramento | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<tag> |
1.2.0 | inferenza | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<tag> |
1.2.0 | addestramento | CPU, GPU | py2, py3 |
Random Cut Forest (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='randomcutforest',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/randomcutforest:<tag> |
1 | inferenza, addestramento |
Scikit-learn (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='sklearn',region='me-central-1',version='0.23-1',image_scope='inference')
| Percorso Registro di sistema | Versione | Versione del pacchetto | Tipi di processo (ambito di immagine) |
|---|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,2-1 | 1.2.1 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,2-1 | 1.2.1 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,0-1 | 1.0.2 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,0-1 | 1.0.2 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,0-1 | 1.0.2 | inference_graviton |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,23-1 | 0,23,2 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,23-1 | 0,23,2 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,20,0 | 0,20,0 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,20,0 | 0,20,0 | addestramento |
Segmentazione semantica (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='semantic-segmentation',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/semantic-segmentation:<tag> |
1 | inferenza, addestramento |
Seq2Seq (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='seq2seq',region='me-central-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/seq2seq:<tag> |
1 | inferenza, addestramento |
Spark (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='spark',region='me-central-1',version='3.0',image_scope='processing')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
395420993607.dkr.ecr.me-central-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.3 | elaborazione |
395420993607.dkr.ecr.me-central-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.2 | elaborazione |
395420993607.dkr.ecr.me-central-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.1 | elaborazione |
395420993607.dkr.ecr.me-central-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.0 | elaborazione |
395420993607.dkr.ecr.me-central-1.amazonaws.com/sagemaker-spark-processing:<tag> |
2.4 | elaborazione |
Tensorflow (DLC)
Per informazioni sulle TensorFlow versioni supportate e non supportate, consulta la tabella dei criteri di supporto del Framework nella AWS Deep Learning Containers Developer Guide.
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='tensorflow',region='me-central-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.19.0 | Inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.19.0 | addestramento | CPU, GPU | py312 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.18.0 | Inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.18.0 | addestramento | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.16.2 | addestramento | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2,16,1 | Inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2,16,1 | inference_graviton | CPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2,14,1 | Inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2,14,1 | inference_graviton | CPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2,14,1 | addestramento | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.13.0 | Inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2.13.0 | inference_graviton | CPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.13.0 | addestramento | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2,12,1 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2,12.1 | inference_graviton | CPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.12.0 | addestramento | CPU, GPU | py310 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.11.1 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.11.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.11.0 | addestramento | CPU, GPU | py39 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
210.1 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
210.1 | addestramento | CPU, GPU | py39 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.10.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
29.3 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
29.2 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
29.2 | addestramento | CPU, GPU | py39 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
29.1 | inference_graviton | CPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
28.4 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.8.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.8.0 | addestramento | CPU, GPU | py39 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.7.1 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.7.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
26.3 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
26.3 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
26.2 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.6.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.6.0 | addestramento | CPU, GPU | py38 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.5.1 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.5.1 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.5.0 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.4.3 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.4.3 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.4.1 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.4.1 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.3.2 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.3.2 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.3.1 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.3.1 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-eia:<tag> |
2.3.0 | eia | CPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.3.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.3.0 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.2.2 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.2.2 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.2.1 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.2.1 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.2.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.2.0 | addestramento | CPU, GPU | py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.3 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.1.3 | addestramento | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.2 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.1.2 | addestramento | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.1 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.1.1 | addestramento | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.1.0 | addestramento | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.4 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.0.4 | addestramento | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.3 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.0.3 | addestramento | CPU, GPU | py3, py36 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.2 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.0.2 | addestramento | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.1 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.0.1 | addestramento | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-eia:<tag> |
2.0.0 | eia | CPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
2.0.0 | addestramento | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
1,15,5 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
1,15,5 | addestramento | CPU, GPU | py3, py36, py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
1.15,4 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
1.15,4 | addestramento | CPU, GPU | py3, py36, py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
1.15.3 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
1.15.3 | addestramento | CPU, GPU | py2, py3, py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
1.15.2 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
1.15.2 | addestramento | CPU, GPU | py2, py3, py37 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-eia:<tag> |
1.15.0 | eia | CPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
1.15.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
1.15.0 | addestramento | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-eia:<tag> |
1.14.0 | eia | CPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
1.14.0 | inferenza | CPU, GPU | - |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
1.14.0 | addestramento | CPU, GPU | py2, py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<tag> |
1.13.1 | addestramento | CPU, GPU | py3 |
914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<tag> |
1.13.0 | inferenza | CPU, GPU | - |
XGBoost (algoritmo)
Il seguente esempio di SageMaker AI Python SDK mostra come recuperare un percorso di registro specifico.
from sagemaker import image_uris image_uris.retrieve(framework='xgboost',region='me-central-1',version='1.5-1')
| Percorso Registro di sistema | Versione | Versione del pacchetto | Tipi di processo (ambito di immagine) |
|---|---|---|---|
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,7-1 | 1,7,4 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,7-1 | 1,7,4 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,5-1 | 1.5.2 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,5-1 | 1.5.2 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,5-1 | 1.5.2 | inference_graviton |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,3-1 | 1.3.3 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,3-1 | 1.3.3 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,3-1 | 1.3.3 | inference_graviton |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,2-2 | 1.2.0 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,2-2 | 1.2.0 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,2-1 | 1.2.0 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,2-1 | 1.2.0 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,0-1 | 1.0.0 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,0-1 | 1.0.0 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/xgboost:<tag> |
1 | 0,72 | Inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/xgboost:<tag> |
1 | 0,72 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-2 | 0.90 | inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-2 | 0.90 | addestramento |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-1 | 0.90 | inferenza |
272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-1 | 0.90 | addestramento |
