syne_tune.remote.estimators module

syne_tune.remote.estimators.instance_sagemaker_estimator(**kwargs)[source]

Returns SageMaker estimator to be used for simulator back-end experiments and for remote launching of SageMaker back-end experiments.

syne_tune.remote.estimators.basic_cpu_instance_sagemaker_estimator(**kwargs)[source]

Returns SageMaker estimator to be used for simulator back-end experiments and for remote launching of SageMaker back-end experiments.

syne_tune.remote.estimators.pytorch_estimator(**estimator_kwargs)[source]

Get the PyTorch sagemaker estimator with the most up-to-date framework version. List of available containers: https://github.com/aws/deep-learning-containers/blob/master/available_images.md

Parameters:: estimator_kwargs – Estimator parameters as discussed in https://sagemaker.readthedocs.io/en/stable/frameworks/pytorch/sagemaker.pytorch.html
Return type:: PyTorch
Returns:: PyTorch estimator

syne_tune.remote.estimators.huggingface_estimator(**estimator_kwargs)[source]

Get the Huggingface sagemaker estimator with the most up-to-date framework version. List of available containers: https://github.com/aws/deep-learning-containers/blob/master/available_images.md

Parameters:: estimator_kwargs – Estimator parameters as discussed in https://sagemaker.readthedocs.io/en/stable/frameworks/huggingface/sagemaker.huggingface.html
Return type:: HuggingFace
Returns:: PyTorch estimator

syne_tune.remote.estimators.sklearn_estimator(**estimator_kwargs)[source]

Get the Scikit-learn sagemaker estimator with the most up-to-date framework version. List of available containers: https://github.com/aws/deep-learning-containers/blob/master/available_images.md

Parameters:: estimator_kwargs – Estimator parameters as discussed in https://sagemaker.readthedocs.io/en/stable/frameworks/sklearn/sagemaker.sklearn.html
Return type:: SKLearn
Returns:: PyTorch estimator

syne_tune.remote.estimators.mxnet_estimator(**estimator_kwargs)[source]

Get the MXNet sagemaker estimator with the most up-to-date framework version. List of available containers: https://github.com/aws/deep-learning-containers/blob/master/available_images.md

Parameters:: estimator_kwargs – Estimator parameters as discussed in https://sagemaker.readthedocs.io/en/stable/frameworks/mxnet/sagemaker.mxnet.html
Return type:: MXNet
Returns:: PyTorch estimator