LightningTrainerScript

class lightning.app.components.training.LightningTrainerScript(script_path, script_args=None, num_nodes=1, cloud_compute=CloudCompute(name='cpu-small', disk_size=0, idle_timeout=None, shm_size=0, mounts=None, colocation_group_id=None, interruptible=False, _internal_id='default'), sanity_serving=False, script_runner=<class 'lightning.app.components.training.PyTorchLightningScriptRunner'>, **script_runner_kwargs)

Bases: LightningFlow

This component enables performing distributed multi-node multi-device training.

Example:

from lightning.app import LightningApp
from lightning.app.components.training import LightningTrainerScript
from lightning.app.utilities.packaging.cloud_compute import CloudCompute

app = LightningApp(
    LightningTrainerScript(
        "train.py",
        num_nodes=2,
        cloud_compute=CloudCompute("gpu"),
    ),
)

Parameters

• script_path (str) – Path to the script to be executed.

• script_args (Union[list, str, None]) – The arguments to be pass to the script.

• num_nodes (int) – Number of nodes.

• cloud_compute (CloudCompute) – The cloud compute object used in the cloud.

• sanity_serving (bool) – Whether to validate that the model correctly implements the ServableModule API

run(**run_kwargs)

Override with your own logic.