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[tune/sgd] Document func_trainable and add checkpoint context (#9739)

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Co-authored-by: krfricke <krfricke@users.noreply.github.com>
Co-authored-by: Amog Kamsetty <amogkam@users.noreply.github.com>
This commit is contained in:
Richard Liaw
2020-07-30 09:46:37 -07:00
committed by GitHub
co-authored by krfricke Amog Kamsetty
parent e540e425e4
commit 0c3b9ebeef
23 changed files with 619 additions and 452 deletions
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doc/source/tune/examples/ddp_mnist_torch.rst
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:orphan:
ddp_mnist_torch
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.. literalinclude:: /../../python/ray/tune/examples/ddp_mnist_torch.py
doc/source/tune/examples/index.rst
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@@ -41,6 +41,7 @@ PyTorch Examples
- :doc:`/tune/examples/mnist_pytorch`: Converts the PyTorch MNIST example to use Tune with the function-based API. Also shows how to easily convert something relying on argparse to use Tune.
- :doc:`/tune/examples/mnist_pytorch_trainable`: Converts the PyTorch MNIST example to use Tune with Trainable API. Also uses the HyperBandScheduler and checkpoints the model at the end.
- :doc:`/tune/examples/ddp_mnist_torch`: An example showing how to use DistributedDataParallel with Ray Tune. This enables both distributed training and distributed hyperparameter tuning.
XGBoost Example