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remove deprecated mentioning (Project-MONAI#736)
Signed-off-by: Wenqi Li <[email protected]>
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acceleration/distributed_training/unet_evaluation_workflows.py

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@@ -31,7 +31,7 @@
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- Wrap the model with `DistributedDataParallel` after moving to expected device.
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- Put model file on every node, then load and map to expected GPU device in every process.
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- Wrap Dataset with `DistributedSampler`, disable the `shuffle` in sampler and DataLoader.
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- Add `StatsHandler` and `SegmentationSaver` to the master process which is `dist.get_rank() == 0`.
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- Add `StatsHandler` to the master process which is `dist.get_rank() == 0`.
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- ignite can automatically reduce metrics for distributed evaluation, refer to:
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https://github.com/pytorch/ignite/blob/v0.4.2/ignite/metrics/metric.py#L507
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modules/dynunet_pipeline/evaluator.py

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@@ -42,7 +42,7 @@ class DynUNetEvaluator(SupervisedEvaluator):
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checkpoint into files.
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additional_metrics: more Ignite metrics that also attach to Ignite Engine.
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val_handlers: every handler is a set of Ignite Event-Handlers, must have `attach` function, like:
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CheckpointHandler, StatsHandler, SegmentationSaver, etc.
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CheckpointHandler, StatsHandler, etc.
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amp: whether to enable auto-mixed-precision evaluation, default is False.
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tta_val: whether to do the 8 flips (8 = 2 ** 3, where 3 represents the three dimensions)
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test time augmentation, default is False.

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