get_local_world_size

TrainContext.get_local_world_size() → int

Get the local world size of this node (i.e. number of workers on this node).

Examples

>>> import ray
>>> from ray import train
>>> from ray.train import ScalingConfig
>>> from ray.train.torch import TorchTrainer
>>> def train_loop_per_worker():
...     print(train.get_context().get_local_world_size())
>>> train_dataset = ray.data.from_items(
...     [{"x": x, "y": x + 1} for x in range(32)])
>>> trainer = TorchTrainer(train_loop_per_worker,
...     scaling_config=ScalingConfig(num_workers=1),
...     datasets={"train": train_dataset})
>>> print("[ignore]"); trainer.fit()
[ignore]...

Returns:

The number of workers running on this node.

Return type:

int

PublicAPI (beta): This API is in beta and may change before becoming stable.