ray.train.context.TrainContext.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).

Example

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})
trainer.fit()

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