Le traduzioni sono generate tramite traduzione automatica. In caso di conflitto tra il contenuto di una traduzione e la versione originale in Inglese, quest'ultima prevarrà.
Percorsi di registro Docker e codice di esempio per Asia Pacifico (Hong Kong) (ap-east-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='ap-east-1',image_scope='inference',version='0.4')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
1.3.0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
1.3.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
1.2.0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
1.2.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
1.1.1 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
1.1.1 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
1.1.0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
1.1.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
1.0.0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
1.0.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
0.8.2 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
0.8.2 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
0.7.0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
0.7.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
0.6.2 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
0.6.2 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
0.6.1 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
0.6.1 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
0.5.2 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
0,5,2 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
0,4,3 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
0,4,3 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
0,4,2 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
0,4,2 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
0,40 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
0,40 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
0,32 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<tag> |
0,32 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<tag> |
0,31 | addestramento |
871362719292.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-1.amazonaws.com/blazingtext:<tag> |
1 | inferenza, addestramento |
Chainer (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='chainer',region='ap-east-1',version='5.0.0',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 |
|---|---|---|---|---|
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-chainer:<tag> |
5.0.0 | inferenza, addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-chainer:<tag> |
4.1.0 | inferenza, addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-chainer:<tag> |
4.0.0 | inferenza, addestramento | CPU, GPU | py2, py3 |
Clarify (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='clarify',region='ap-east-1',version='1.0',image_scope='processing')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
098760798382.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-clarify-processing:<tag> |
1.0 | elaborazione |
DJL DeepSpeed (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='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inferenceIl seguente esempio di AI Python SDK mostra come recuperare un percorso di registro specifico. ----sep----:0.27.0-deepspeed0.12.6-cu121- <tag> |
0,27.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference0.27.0 ----set----:0.26.0-velocità profonda 0.12,6-cu121- <tag> |
0,26.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference0.26.0 ----set----:0.25.0-velocità profonda 0.11.0-cu118- <tag> |
0,25.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference0.25.0 ----set----:0.24.0-deepspeed0.10.0-cu118- <tag> |
0.24.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference0.24.0 ----set----:0.23.0-velocità profonda 0.9.5-cu118- <tag> |
0.23.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference0.23.0 ----set----:0.22.1-velocità profonda 0.9.2-cu118- <tag> |
0.22.1 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference0.22.1 ----set----:0.21.0-velocità profonda 0.8.3-cu117- <tag> |
0.21.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference0.21.0 ----set----:0.20.0-velocità profonda 0.7.5-cu116- <tag> |
0,20.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference0.20.0 ----set----:0.19.0-velocità profonda 0.7.3-cu113- <tag> |
0.19.0 | inferenza |
Data Wrangler (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='data-wrangler',region='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
707077482487.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-data-wrangler-container:<tag> |
3.x | elaborazione |
707077482487.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-data-wrangler-container:<tag> |
2.x | elaborazione |
707077482487.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-data-wrangler-container:<tag> |
1.x | elaborazione |
Debugger (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='debugger',region='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
199566480951.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-debugger-rules:<tag> |
più recente | debugger |
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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-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) |
|---|---|---|
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.49.0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,49,0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,48,0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,48,0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,46,1 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,37,0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,36,0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,28,1 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,28,1 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,26,0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,26,0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4,26,0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,17,0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4,17,0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,17,0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4,17,0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4,12,3 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4,12,3 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4,12,3 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4,12,3 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.11.0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.11.0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4.11.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4.11.0 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
410.2 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
410.2 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
410.2 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
410.2 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
410.2 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
410.2 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
410.2 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
410.2 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
46.1 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.6.1 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.6.1 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.6.1 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<tag> |
4.6.1 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<tag> |
4.6.1 | Inferenza |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.5.0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<tag> |
4.5.0 | addestramento |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<tag> |
4.4.2 | addestramento |
871362719292.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-1.amazonaws.com/image-classification:<tag> |
1 | inferenza, addestramento |
Inferentia 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='inferentia-mxnet',region='ap-east-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-mxnet:<tag> |
1.8 | inferenza | inf | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-mxnet:<tag> |
1.5.1 | inferenza | inf | py3 |
Inferentia PyTorch (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='inferentia-pytorch',region='ap-east-1',version='1.9',py_version='py3')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-pytorch:<tag> |
1.9 | inferenza | inf | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-pytorch:<tag> |
1.8 | inferenza | inf | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-pytorch:<tag> |
1,7 | inferenza | inf | py3 |
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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-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 |
|---|---|---|---|---|
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-training:<tag> |
1.9.0 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference:<tag> |
1.9.0 | inferenza | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-training:<tag> |
1.8.0 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference:<tag> |
1.8.0 | inferenza | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-training:<tag> |
1.7.0 | addestramento | CPU, GPU | py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference:<tag> |
1.7.0 | inferenza | CPU, GPU | py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference-eia:<tag> |
1.7.0 | eia | CPU | py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-training:<tag> |
1.6.0 | addestramento | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference:<tag> |
1.6.0 | inferenza | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference-eia:<tag> |
1.5.1 | eia | CPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.4.1 | addestramento | CPU, GPU | py2 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-training:<tag> |
1.4.1 | addestramento | CPU, GPU | py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet-serving:<tag> |
1.4.1 | inferenza | CPU, GPU | py2 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference:<tag> |
1.4.1 | inferenza | CPU, GPU | py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference-eia:<tag> |
1.4.1 | eia | CPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.4.0 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet-serving:<tag> |
1.4.0 | inferenza | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet-serving-eia:<tag> |
1.4.0 | eia | CPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.3.0 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.3.0 | inferenza | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet-eia:<tag> |
1.3.0 | eia | CPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.2.1 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.2.1 | inferenza | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.1.0 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.1.0 | inferenza | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.0.0 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
1.0.0 | inferenza | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
0.12.1 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<tag> |
0.12.1 | inferenza | CPU, GPU | py2, py3 |
MXNet Allenatore (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='coach-mxnet',region='ap-east-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-mxnetIl seguente esempio di AI Python SDK mostra come recuperare un percorso di registro specifico. ----sep----:coach0.11.0- <tag> |
0.11.0 | addestramento | CPU, GPU | py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-mxnet: allenatore 0.11.0- ----set ----:allenatore 0.11- <tag> |
0,11 | addestramento | CPU, GPU | 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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
001633400207.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-1.amazonaws.com/ntm:<tag> |
1 | inferenza, addestramento |
Classificazione delle immagine Neo (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-neo',region='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
110948597952.dkr.ecr.ap-east-1.amazonaws.com/image-classification-neo:<tag> |
più recente | Inferenza |
Neo 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='neo-mxnet',region='ap-east-1',version='1.8',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 |
|---|---|---|---|---|
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-mxnet:<tag> |
1.8 | inferenza | CPU, GPU | py3 |
Neo PyTorch (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='neo-pytorch',region='ap-east-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
2.0 | Inferenza | CPU, GPU | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.13 | inferenza | CPU, GPU | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.12 | inferenza | CPU, GPU | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.8 | inferenza | CPU, GPU | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1,7 | inferenza | CPU, GPU | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.6 | inferenza | CPU, GPU | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.5 | inferenza | CPU, GPU | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<tag> |
1.4 | inferenza | CPU, GPU | py3 |
Neo Tensorflow (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='neo-tensorflow',region='ap-east-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-tensorflow:<tag> |
2.9.2 | inferenza | CPU, GPU | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-tensorflow:<tag> |
1.15.3 | inferenza | CPU, GPU | py3 |
Neo 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-neo',region='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
110948597952.dkr.ecr.ap-east-1.amazonaws.com/xgboost-neo:<tag> |
più recente | inferenza |
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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-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 |
|---|---|---|---|---|
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
2.7.1 | addestramento | CPU, GPU | py312 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
2.6.0 | inferenza | CPU, GPU | py312 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
2.6.0 | addestramento | CPU, GPU | py312 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
2.5.1 | inferenza | CPU, GPU | py311 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
2.5.1 | addestramento | CPU, GPU | py311 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
2.4.0 | Inferenza | CPU, GPU | py311 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.4.0 | inference_graviton | CPU | py311 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
2.4.0 | addestramento | CPU, GPU | py311 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
2.3.0 | inferenza | CPU, GPU | py311 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.3.0 | inference_graviton | CPU | py311 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
2.3.0 | addestramento | CPU, GPU | py311 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.2.1 | inference_graviton | CPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
2.2.0 | inferenza | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
2.2.0 | addestramento | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
2.1.0 | inferenza | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.1.0 | inference_graviton | CPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
2.1.0 | addestramento | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
2.0.1 | inferenza | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.0.1 | inference_graviton | CPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
2.0.1 | addestramento | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
2.0.0 | inferenza | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<tag> |
2.0.0 | inference_graviton | CPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
2.0.0 | addestramento | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.13.1 | inferenza | CPU, GPU | py39 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.13.1 | addestramento | CPU, GPU | py39 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.12.1 | inferenza | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<tag> |
1.12.1 | inference_graviton | CPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.12.1 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.12.0 | inferenza | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.12.0 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.11.0 | inferenza | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.11.0 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.10.2 | inferenza | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.10.2 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.10.0 | inferenza | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.10.0 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.9.1 | inferenza | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.9.1 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.9.0 | inferenza | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.9.0 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.8.1 | inferenza | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.8.1 | addestramento | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.8.0 | inferenza | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.8.0 | addestramento | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.7.1 | inferenza | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.7.1 | addestramento | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.6.0 | inferenza | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.6.0 | addestramento | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.5.0 | inferenza | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.5.0 | addestramento | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.4.0 | inferenza | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.4.0 | addestramento | CPU, GPU | py2, py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.3.1 | inferenza | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.3.1 | addestramento | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<tag> |
1.2.0 | inferenza | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<tag> |
1.2.0 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<tag> |
1.1.0 | inferenza | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<tag> |
1.1.0 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<tag> |
1.0.0 | inferenza | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<tag> |
1.0.0 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<tag> |
0.4.0 | inferenza | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<tag> |
0,40 | addestramento | CPU, GPU | py2, py3 |
PyTorch Compilatore di formazione (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='pytorch-training-compiler',region='us-west-2', version='py38')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-trcomp-training:<tag> |
1.13.1 | addestramento | GPU | py39 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-trcomp-training:<tag> |
1.12.0 | addestramento | GPU | py38 |
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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-1',version='0.23-1',image_scope='inference')
| Percorso Registro di sistema | Versione | Versione del pacchetto | Tipi di processo (ambito di immagine) |
|---|---|---|---|
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,2-1 | 1.2.1 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,2-1 | 1.2.1 | addestramento |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,0-1 | 1.0.2 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,0-1 | 1.0.2 | addestramento |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
1,0-1 | 1.0.2 | inference_graviton |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,23-1 | 0,23,2 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,23-1 | 0,23,2 | addestramento |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<tag> |
0,20,0 | 0,20,0 | Inferenza |
651117190479.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-1')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
286214385809.dkr.ecr.ap-east-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='ap-east-1',version='3.0',image_scope='processing')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
732049463269.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.3 | elaborazione |
732049463269.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.2 | elaborazione |
732049463269.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.1 | elaborazione |
732049463269.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-spark-processing:<tag> |
3.0 | elaborazione |
732049463269.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-spark-processing:<tag> |
2.4 | elaborazione |
SparkML Serving (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='sparkml-serving',region='ap-east-1',version='2.4')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) |
|---|---|---|
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-sparkml-serving:<tag> |
3.3 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-sparkml-serving:<tag> |
2.4 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-sparkml-serving:<tag> |
2.2 | inferenza |
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='ap-east-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 |
|---|---|---|---|---|
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.19.0 | Inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.19.0 | addestramento | CPU, GPU | py312 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.18.0 | Inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.18.0 | addestramento | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.16.2 | addestramento | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2,16,1 | Inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2,16,1 | inference_graviton | CPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2,14,1 | Inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2,14,1 | inference_graviton | CPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2,14,1 | addestramento | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.13.0 | Inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2.13.0 | inference_graviton | CPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.13.0 | addestramento | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2,12,1 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
2,12.1 | inference_graviton | CPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.12.0 | addestramento | CPU, GPU | py310 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.11.1 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.11.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.11.0 | addestramento | CPU, GPU | py39 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
210.1 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
210.1 | addestramento | CPU, GPU | py39 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.10.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
29.3 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
29.2 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
29.2 | addestramento | CPU, GPU | py39 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-graviton:<tag> |
29.1 | inference_graviton | CPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
28.4 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.8.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.8.0 | addestramento | CPU, GPU | py39 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.7.1 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.7.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
26.3 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
26.3 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
26.2 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.6.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.6.0 | addestramento | CPU, GPU | py38 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.5.1 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.5.1 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.5.0 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.4.3 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.4.3 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.4.1 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.4.1 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.3.2 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.3.2 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.3.1 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.3.1 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-eia:<tag> |
2.3.0 | eia | CPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.3.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.3.0 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.2.2 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.2.2 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.2.1 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.2.1 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.2.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.2.0 | addestramento | CPU, GPU | py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.3 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.1.3 | addestramento | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.2 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.1.2 | addestramento | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.1 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.1.1 | addestramento | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.1.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.1.0 | addestramento | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.4 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.0.4 | addestramento | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.3 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.0.3 | addestramento | CPU, GPU | py3, py36 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.2 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.0.2 | addestramento | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.1 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.0.1 | addestramento | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-eia:<tag> |
2.0.0 | eia | CPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
2.0.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
2.0.0 | addestramento | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
1,15,5 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
1,15,5 | addestramento | CPU, GPU | py3, py36, py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
1.15,4 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
1.15,4 | addestramento | CPU, GPU | py3, py36, py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
1.15.3 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
1.15.3 | addestramento | CPU, GPU | py2, py3, py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
1.15.2 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
1.15.2 | addestramento | CPU, GPU | py2, py3, py37 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-eia:<tag> |
1.15.0 | eia | CPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
1.15.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
1.15.0 | addestramento | CPU, GPU | py2, py3 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-eia:<tag> |
1.14.0 | eia | CPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
1.14.0 | inferenza | CPU, GPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
1.14.0 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<tag> |
1.13.1 | addestramento | CPU, GPU | py2 |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<tag> |
1.13.1 | addestramento | CPU, GPU | py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<tag> |
1.13.0 | eia | CPU | - |
871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<tag> |
1.13.0 | inferenza | CPU, GPU | - |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<tag> |
1.12.0 | eia | CPU | - |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-serving:<tag> |
1.12.0 | inferenza | CPU, GPU | - |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<tag> |
1.12.0 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<tag> |
1.11.0 | eia | CPU | - |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-serving:<tag> |
1.11.0 | inferenza | CPU, GPU | - |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<tag> |
1.11.0 | addestramento | CPU, GPU | py2, py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-eia:<tag> |
1.10.0 | eia | CPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.10.0 | inferenza | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.10.0 | addestramento | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.9.0 | inferenza | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.9.0 | addestramento | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.8.0 | inferenza | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.8.0 | addestramento | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.7.0 | inferenza | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.7.0 | addestramento | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.6.0 | inferenza | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.6.0 | addestramento | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.5.0 | inferenza | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.5.0 | addestramento | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.4.1 | inferenza | CPU, GPU | py2 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<tag> |
1.4.1 | addestramento | CPU, GPU | py2 |
Tensorflow Coach (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='coach-tensorflow',region='ap-east-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflowIl seguente esempio di AI Python SDK mostra come recuperare un percorso di registro specifico. ----sep----:coach0.11.1- <tag> |
0.11.1 | addestramento | CPU, GPU | py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:allenatore0.11.1- ----set----:allenatore 0.11.0- <tag> |
0.11.0 | addestramento | CPU, GPU | py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow: allenatore 0.11.0- ----set ----:allenatore 0.11- <tag> |
0,11 | addestramento | CPU, GPU | py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow0.11 ----sep----:allenatore0.10.1- <tag> |
0.10.1 | addestramento | CPU, GPU | py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow0.10.1 ----sep----:allenatore0.10- <tag> |
0.10 | addestramento | CPU, GPU | py3 |
Tensorflow Inferentia (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='inferentia-tensorflow',region='ap-east-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-tensorflow:<tag> |
2.5.2 | inferenza | inf | py3 |
110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-tensorflow:<tag> |
1.15.0 | inferenza | inf | py3 |
Tensorflow Ray (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='ray-tensorflow',region='ap-east-1',version='0.8.5',instance_type='ml.c5.4xlarge')
| Percorso Registro di sistema | Versione | Tipi di processo (ambito di immagine) | Tipi di processori | Versioni Python |
|---|---|---|---|---|
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflowIl seguente esempio di AI Python SDK mostra come recuperare un percorso di registro specifico. ----sep----:ray0.6.5- <tag> |
0.6.5 | addestramento | CPU, GPU | py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow0.6.5 ----sep----:ray0.6- <tag> |
0.6 | addestramento | CPU, GPU | py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6- ----sep----:ray0.5.3- <tag> |
0.5.3 | addestramento | CPU, GPU | py3 |
057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow0.5.3 ----sep----:ray0.5- <tag> |
0,5 | addestramento | CPU, GPU | py3 |
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='ap-east-1',version='1.5-1')
| Percorso Registro di sistema | Versione | Versione del pacchetto | Tipi di processo (ambito di immagine) |
|---|---|---|---|
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,7-1 | 1,7,4 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,7-1 | 1,7,4 | addestramento |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,5-1 | 1.5.2 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,5-1 | 1.5.2 | addestramento |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,5-1 | 1.5.2 | inference_graviton |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,3-1 | 1.3.3 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,3-1 | 1.3.3 | addestramento |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,3-1 | 1.3.3 | inference_graviton |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,2-2 | 1.2.0 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,2-2 | 1.2.0 | addestramento |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,2-1 | 1.2.0 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,2-1 | 1.2.0 | addestramento |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,0-1 | 1.0.0 | Inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
1,0-1 | 1.0.0 | addestramento |
286214385809.dkr.ecr.ap-east-1.amazonaws.com/xgboost:<tag> |
1 | 0,72 | Inferenza |
286214385809.dkr.ecr.ap-east-1.amazonaws.com/xgboost:<tag> |
1 | 0,72 | addestramento |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-2 | 0.90 | inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-2 | 0.90 | addestramento |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-1 | 0.90 | inferenza |
651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<tag> |
0,90-1 | 0.90 | addestramento |
