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KubeflowEnvironment

class pytorch_lightning.plugins.environments.KubeflowEnvironment[source]

Bases: pytorch_lightning.plugins.environments.cluster_environment.ClusterEnvironment

Environment for distributed training using the PyTorchJob operator from Kubeflow

static detect()[source]

Returns True if the current process was launched using Kubeflow PyTorchJob.

Return type:

bool

global_rank()[source]

The rank (index) of the currently running process across all nodes and devices.

Return type:

int

local_rank()[source]

The rank (index) of the currently running process inside of the current node.

Return type:

int

node_rank()[source]

The rank (index) of the node on which the current process runs.

Return type:

int

world_size()[source]

The number of processes across all devices and nodes.

Return type:

int

property creates_processes_externally: bool

Whether the environment creates the subprocesses or not.

Return type:

bool

property main_address: str

The main address through which all processes connect and communicate.

Return type:

str

property main_port: int

An open and configured port in the main node through which all processes communicate.

Return type:

int