[pull] master from ray-project:master #2322
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Previously we only shard the "train" Ray Dataset by default. If users want to shard other datasets, they need to explicitly specify it with a `DataConfig`. e.g. `DataConfig(datasets_to_split=["train", "eval"])`.
We now change the default behavior to shard all datasets by default for the following considerations:
- Efficiency: We want people to leverage Ray Data as best as possible. The best way to optimize training time is to leverage the fact that Ray Data can effectively shard all the datasets across workers. Training frameworks (e.g. Lightning) provide ways to aggregate results across workers, and we should be recommending users to shard their validation datasets.
- Consistency: It is conceptually easier for users to understand a single default behavior applied to all Datasets and to be provided options to configure them.
- Explicitness: The behavior for the magic “train” key is not very explicit, and users will not understand this until they really read through the documentation. Relying on untyped keywords is non-ideal.
### API
- Shard all datasets(default):
```python
TorchTrainer(
datasets={"a": ds_1, "b": ds_2, "c": ds_3},
# data_config=DataConfig(datasets_to_split="all")
)
```
- Shard a subset of datasets
```python
TorchTrainer(
datasets={"a": ds_1, "b": ds_2, "c": ds_3},
data_config=DataConfig(datasets_to_split=["a", "b"])
)
```
Signed-off-by: woshiyyya <[email protected]>
Signed-off-by: Yunxuan Xiao <[email protected]>
Co-authored-by: matthewdeng <[email protected]>
Co-authored-by: Eric Liang <[email protected]>
Co-authored-by: Cheng Su <[email protected]>
We have a mixture of raw strings and Ray `TagKey`s being used throughout the code. Unifying them under a single interface. Also unified the report parsing code used in tests.
…8682) We clean up this outdated example which uses AccelerateTrainer API. Signed-off-by: woshiyyya <[email protected]>
In addition to removing unnecessary code duplication, these changes fix the links to the stack trace and flame graph pages when behind a reverse proxy. Previously the links used in NodeRow.tsx included a leading / that is not included in other links and does not work when hosting the Ray dashboard behind a reverse proxy.
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