LightningEnvironment¶
- class lightning.pytorch.plugins.environments.LightningEnvironment[source]¶
Bases:
lightning.fabric.plugins.environments.cluster_environment.ClusterEnvironment
The default environment used by Lightning for a single node or free cluster (not managed).
There are two modes the Lightning environment can operate with:
The user only launches the main process by
python train.py ...
with no additional environment variables set. Lightning will spawn new worker processes for distributed training in the current node.The user launches all processes manually or with utilities like
torch.distributed.launch
. The appropriate environment variables need to be set, and at minimumLOCAL_RANK
.
If the main address and port are not provided, the default environment will choose them automatically. It is recommended to use this default environment for single-node distributed training as it provides a convenient way to launch the training script.
- static detect()[source]¶
Detects the environment settings corresponding to this cluster and returns
True
if they match.- Return type
- global_rank()[source]¶
The rank (index) of the currently running process across all nodes and devices.
- Return type
- local_rank()[source]¶
The rank (index) of the currently running process inside of the current node.
- Return type
- property creates_processes_externally: bool¶
Returns whether the cluster creates the processes or not.
If at least
LOCAL_RANK
is available as environment variable, Lightning assumes the user acts as the process launcher/job scheduler and Lightning will not launch new processes.- Return type