itwinai.distributed
- class itwinai.distributed.DistributedStrategy[source]
Bases:
ABCAbstract class to define the distributed backend methods.
- class itwinai.distributed.ClusterEnvironment(*, global_rank: int = 0, local_rank: int = 0, global_world_size: int = 1, local_world_size: int = 1)[source]
Bases:
BaseModelStores information about distributed environment.
- global_rank: int
Global rank of current worker, in a distributed environment.
global_rank==0identifies the main worker. Defaults to 0.
- local_rank: int
Local rank of current worker, in a distributed environment. Defaults to 0.
- global_world_size: int
Total number of workers in a distributed environment. Defaults to 1.
- local_world_size: int
Number of workers on the same node in a distributed environment. Defaults to 1.
- model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}
A dictionary of computed field names and their corresponding ComputedFieldInfo objects.
- model_config: ClassVar[ConfigDict] = {}
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- model_fields: ClassVar[dict[str, FieldInfo]] = {'global_rank': FieldInfo(annotation=int, required=False, default=0), 'global_world_size': FieldInfo(annotation=int, required=False, default=1), 'local_rank': FieldInfo(annotation=int, required=False, default=0), 'local_world_size': FieldInfo(annotation=int, required=False, default=1)}
Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].
This replaces Model.__fields__ from Pydantic V1.
- itwinai.distributed.detect_distributed_environment() ClusterEnvironment[source]
Detects distributed environment, extracting information like global ans local ranks, and world size.
- itwinai.distributed.builtin_print()
Save original builtin print before patching it in distributed environments