기계 번역으로 제공되는 번역입니다. 제공된 번역과 원본 영어의 내용이 상충하는 경우에는 영어 버전이 우선합니다.
아시아 태평양(자카르타)의 Docker 레지스트리 경로 및 예제 코드 (ap-southeast-3)
다음 주제에서는 Amazon SageMaker AI에서 제공하는이 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터를 나열합니다.
주제
- AutoGluon(알고리즘)
- BlazingText(알고리즘)
- Clarify(알고리즘)
- DJL DeepSpeed(알고리즘)
- DeepAR Forecasting(알고리즘)
- Factorization Machine(알고리즘)
- Hugging Face(알고리즘)
- IP Insights(알고리즘)
- 이미지 분류(알고리즘)
- K-Means(알고리즘)
- KNN(알고리즘)
- Linear Learner(알고리즘)
- MXNet(DLC)
- 모델 모니터(알고리즘)
- NTM(알고리즘)
- Object Detection(알고리즘)
- Object2Vec(알고리즘)
- PCA(알고리즘)
- PyTorch(DLC)
- Random Cut Forest(알고리즘)
- Scikit-learn(알고리즘)
- 의미 체계 분할(알고리즘)
- Seq2Seq(알고리즘)
- Spark(알고리즘)
- SparkML Serving(알고리즘)
- Tensorflow(DLC)
- XGBoost(알고리즘)
AutoGluon(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='autogluon',region='ap-southeast-3',image_scope='inference',version='0.4')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> |
0.7.0 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> |
0.7.0 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> |
0.6.2 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> |
0.6.2 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> |
0.6.1 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> |
0.6.1 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> |
0.5.2 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> |
0.5.2 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> |
0.4.3 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> |
0.4.3 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> |
0.4.2 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> |
0.4.2 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> |
0.4.0 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> |
0.4.0 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> |
0.3.2 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> |
0.3.2 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> |
0.3.1 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> |
0.3.1 | 추론 |
BlazingText(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='blazingtext',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/blazingtext:<태그> |
1 | 추론, 훈련 |
Clarify(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='clarify',region='ap-southeast-3',version='1.0',image_scope='processing')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
705930551576.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-clarify-processing:<태그> |
1.0 | 처리 중 |
DJL DeepSpeed(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.22.1-deepspeed0.8.3-cu118-<태그> |
0.22.1 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> |
0.21.0 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> |
0.20.0 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> |
0.19.0 | 추론 |
DeepAR Forecasting(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='forecasting-deepar',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/forecasting-deepar:<태그> |
1 | 훈련, 추론 |
Factorization Machine(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='factorization-machines',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/factorization-machines:<태그> |
1 | 훈련, 추론 |
Hugging Face(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='huggingface',region='ap-southeast-3',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.26.0 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> |
4.26.0 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> |
4.26.0 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.17.0 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> |
4.17.0 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> |
4.17.0 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> |
4.17.0 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.12.3 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> |
4.12.3 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> |
4.12.3 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> |
4.12.3 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.11.0 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> |
4.11.0 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> |
4.11.0 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> |
4.11.0 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.10.2 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.10.2 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> |
4.10.2 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> |
4.10.2 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> |
4.10.2 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> |
4.10.2 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> |
4.10.2 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> |
4.10.2 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.6.1 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.6.1 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.6.1 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> |
4.6.1 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> |
4.6.1 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> |
4.6.1 | 추론 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.5.0 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> |
4.5.0 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> |
4.4.2 | 학습 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> |
4.4.2 | 학습 |
IP Insights(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='ipinsights',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/ipinsights:<태그> |
1 | 훈련, 추론 |
이미지 분류(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='image-classification',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/image-classification:<태그> |
1 | 훈련, 추론 |
K-Means(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='kmeans',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/kmeans:<태그> |
1 | 훈련, 추론 |
KNN(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='knn',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/knn:<태그> |
1 | 훈련, 추론 |
Linear Learner(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='linear-learner',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/linear-learner:<태그> |
1 | 훈련, 추론 |
MXNet(DLC)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='mxnet',region='ap-southeast-3',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 |
---|---|---|---|---|
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-training:<태그> |
1.9.0 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference:<태그> |
1.9.0 | 추론 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-training:<태그> |
1.8.0 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference:<태그> |
1.8.0 | 추론 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-training:<태그> |
1.7.0 | 학습 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference:<태그> |
1.7.0 | 추론 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference-eia:<태그> |
1.7.0 | eia | CPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-training:<태그> |
1.6.0 | 학습 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference:<태그> |
1.6.0 | 추론 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference-eia:<태그> |
1.5.1 | eia | CPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-training:<태그> |
1.4.1 | 학습 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference:<태그> |
1.4.1 | 추론 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference-eia:<태그> |
1.4.1 | eia | CPU | py2, py3 |
모델 모니터(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='model-monitor',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
669540362728.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |
모니터링 |
NTM(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='ntm',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/ntm:<태그> |
1 | 훈련, 추론 |
Object Detection(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='object-detection',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/object-detection:<태그> |
1 | 훈련, 추론 |
Object2Vec(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='object2vec',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/object2vec:<태그> |
1 | 훈련, 추론 |
PCA(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='pca',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/pca:<태그> |
1 | 훈련, 추론 |
PyTorch(DLC)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='pytorch',region='ap-southeast-3',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 |
---|---|---|---|---|
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
2.0.0 | 추론 | CPU, GPU | py310 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-graviton:<태그> |
2.0.0 | inference_graviton | CPU | py310 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
2.0.0 | 학습 | CPU, GPU | py310 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.13.1 | 추론 | CPU, GPU | py39 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.13.1 | 학습 | CPU, GPU | py39 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.12.1 | 추론 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-graviton:<태그> |
1.12.1 | inference_graviton | CPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.12.1 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.12.0 | 추론 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.12.0 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.11.0 | 추론 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.11.0 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.10.2 | 추론 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.10.2 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.10.0 | 추론 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.10.0 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.9.1 | 추론 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.9.1 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.9.0 | 추론 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.9.0 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.8.1 | 추론 | CPU, GPU | py3, py36 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.8.1 | 학습 | CPU, GPU | py3, py36 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.8.0 | 추론 | CPU, GPU | py3, py36 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.8.0 | 학습 | CPU, GPU | py3, py36 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.7.1 | 추론 | CPU, GPU | py3, py36 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.7.1 | 학습 | CPU, GPU | py3, py36 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.6.0 | 추론 | CPU, GPU | py3, py36 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.6.0 | 학습 | CPU, GPU | py3, py36 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-eia:<태그> |
1.5.1 | eia | CPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.5.0 | 추론 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.5.0 | 학습 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.4.0 | 추론 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.4.0 | 학습 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-eia:<태그> |
1.3.1 | eia | CPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.3.1 | 추론 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.3.1 | 학습 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> |
1.2.0 | 추론 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> |
1.2.0 | 학습 | CPU, GPU | py2, py3 |
Random Cut Forest(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='randomcutforest',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/randomcutforest:<태그> |
1 | 훈련, 추론 |
Scikit-learn(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='sklearn',region='ap-southeast-3',version='0.23-1',image_scope='inference')
레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) |
---|---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> |
1.2-1 | 1.2.1 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> |
1.2-1 | 1.2.1 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> |
1.0-1 | 1.0.2 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> |
1.0-1 | 1.0.2 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> |
1.0-1 | 1.0.2 | inference_graviton |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> |
0.23-1 | 0.23.2 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> |
0.23-1 | 0.23.2 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> |
0.20.0 | 0.20.0 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> |
0.20.0 | 0.20.0 | 학습 |
의미 체계 분할(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='semantic-segmentation',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/semantic-segmentation:<태그> |
1 | 훈련, 추론 |
Seq2Seq(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='seq2seq',region='ap-southeast-3')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/seq2seq:<태그> |
1 | 추론, 훈련 |
Spark(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='spark',region='ap-southeast-3',version='3.0',image_scope='processing')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
732049463269.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-spark-processing:<태그> |
3.2 | 처리 중 |
732049463269.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-spark-processing:<태그> |
3.1 | 처리 중 |
732049463269.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-spark-processing:<태그> |
3.0 | 처리 중 |
732049463269.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-spark-processing:<태그> |
2.4 | 처리 중 |
SparkML Serving(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='sparkml-serving',region='ap-southeast-3',version='2.4')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) |
---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-sparkml-serving:<태그> |
3.3 | 추론 |
Tensorflow(DLC)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='tensorflow',region='ap-southeast-3',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 |
---|---|---|---|---|
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.12.1 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.12.0 | 학습 | CPU, GPU | py310 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.11.1 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.11.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.11.0 | 학습 | CPU, GPU | py39 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.10.1 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.10.1 | 학습 | CPU, GPU | py39 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.10.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.9.3 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.9.2 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.9.2 | 학습 | CPU, GPU | py39 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> |
2.9.1 | inference_graviton | CPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.8.4 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.8.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.8.0 | 학습 | CPU, GPU | py39 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.7.1 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.7.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.6.3 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.6.3 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.6.2 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.6.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.6.0 | 학습 | CPU, GPU | py38 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.5.1 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.5.1 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.5.0 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.4.3 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.4.3 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.4.1 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.4.1 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.3.2 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.3.2 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.3.1 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.3.1 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-eia:<태그> |
2.3.0 | eia | CPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.3.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.3.0 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.2.2 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.2.2 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.2.1 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.2.1 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.2.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.2.0 | 학습 | CPU, GPU | py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.1.3 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.1.3 | 학습 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.1.2 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.1.2 | 학습 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.1.1 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.1.1 | 학습 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.1.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.1.0 | 학습 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.0.4 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.0.4 | 학습 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.0.3 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.0.3 | 학습 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.0.2 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.0.2 | 학습 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.0.1 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.0.1 | 학습 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-eia:<태그> |
2.0.0 | eia | CPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
2.0.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
2.0.0 | 학습 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
1.15.5 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
1.15.5 | 학습 | CPU, GPU | py3, py36, py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
1.15.4 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
1.15.4 | 학습 | CPU, GPU | py3, py36, py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
1.15.3 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
1.15.3 | 학습 | CPU, GPU | py2, py3, py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
1.15.2 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
1.15.2 | 학습 | CPU, GPU | py2, py3, py37 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-eia:<태그> |
1.15.0 | eia | CPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
1.15.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
1.15.0 | 학습 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-eia:<태그> |
1.14.0 | eia | CPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
1.14.0 | 추론 | CPU, GPU | - |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
1.14.0 | 학습 | CPU, GPU | py2, py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> |
1.13.1 | 학습 | CPU, GPU | py3 |
907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> |
1.13.0 | 추론 | CPU, GPU | - |
XGBoost(알고리즘)
레지스트리 경로를 검색하는 SageMaker AI Python SDK 예제입니다.
from sagemaker import image_uris image_uris.retrieve(framework='xgboost',region='ap-southeast-3',version='1.5-1')
레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) |
---|---|---|---|
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.7-1 | 1.7.4 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.7-1 | 1.7.4 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.5-1 | 1.5.2 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.5-1 | 1.5.2 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.5-1 | 1.5.2 | inference_graviton |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.3-1 | 1.3.3 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.3-1 | 1.3.3 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.3-1 | 1.3.3 | inference_graviton |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.2-2 | 1.2.0 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.2-2 | 1.2.0 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.2-1 | 1.2.0 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.2-1 | 1.2.0 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.0-1 | 1.0.0 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
1.0-1 | 1.0.0 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/xgboost:<태그> |
1 | 0.72 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/xgboost:<태그> |
1 | 0.72 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
0.90-2 | 0.90 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
0.90-2 | 0.90 | 학습 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
0.90-1 | 0.90 | 추론 |
951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> |
0.90-1 | 0.90 | 학습 |