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| from contextlib import contextmanager | |
| from typing import Any, Dict, List, Optional | |
| import torch | |
| from ..trackers import TrackerType, initialize_trackers | |
| class BaseParallelBackend: | |
| r""" | |
| Base class that contains properties and methods that should be implemented by different parallel backends. | |
| """ | |
| def apply_ddp(self, *args, **kwargs) -> torch.nn.Module: | |
| raise NotImplementedError("Method `apply_ddp` must be implemented by subclass.") | |
| def prepare_dataset(self, *args, **kwargs) -> Any: | |
| raise NotImplementedError("Method `prepare_dataset` must be implemented by subclass.") | |
| def prepare_dataloader(self, *args, **kwargs) -> Any: | |
| raise NotImplementedError("Method `prepare_dataloader` must be implemented by subclass.") | |
| def prepare_optimizer(self, *args, **kwargs) -> Any: | |
| raise NotImplementedError("Method `prepare_optimizer` must be implemented by subclass.") | |
| def get_mesh(self, name: Optional[str] = None) -> torch.distributed.DeviceMesh: | |
| raise NotImplementedError("Method `get_mesh` must be implemented by subclass.") | |
| def initialize_trackers( | |
| self, trackers: List[str], experiment_name: str, config: Dict[str, Any], log_dir: str | |
| ) -> TrackerType: | |
| self.tracker = None | |
| if self.is_main_process: | |
| self.tracker = initialize_trackers(trackers, experiment_name, config, log_dir) | |
| def log(self, metrics: Dict[str, Any], step: int) -> None: | |
| if self.is_main_process: | |
| self.tracker.log(metrics, step) | |
| def wait_for_everyone(self): | |
| raise NotImplementedError("Method `wait_for_everyone` must be implemented by subclass.") | |
| def main_process_first(self): | |
| raise NotImplementedError("Method `main_process_first` must be implemented by subclass.") | |
| def destroy(self): | |
| raise NotImplementedError("Method `destroy` must be implemented by subclass.") | |
| def world_size(self): | |
| raise NotImplementedError("Method `world_size` must be implemented by subclass.") | |
| def rank(self): | |
| raise NotImplementedError("Method `rank` must be implemented by subclass.") | |
| def local_rank(self): | |
| raise NotImplementedError("Method `local_rank` must be implemented by subclass.") | |
| def is_main_process(self): | |
| raise NotImplementedError("Method `is_main_process` must be implemented by subclass.") | |
| def is_local_main_process(self): | |
| raise NotImplementedError("Method `is_local_main_process` must be implemented by subclass.") | |
| def device(self): | |
| raise NotImplementedError("Method `device` must be implemented by subclass.") | |
| def pipeline_parallel_enabled(self): | |
| raise NotImplementedError("Property `pipeline_parallel_enabled` must be implemented by subclass.") | |
| def data_parallel_enabled(self): | |
| raise NotImplementedError("Property `data_parallel_enabled` must be implemented by subclass.") | |
| def data_replication_enabled(self): | |
| raise NotImplementedError("Property `data_replication_enabled` must be implemented by subclass.") | |
| def data_sharding_enabled(self): | |
| raise NotImplementedError("Property `data_sharding_enabled` must be implemented by subclass.") | |
| def context_parallel_enabled(self): | |
| raise NotImplementedError("Property `context_parallel_enabled` must be implemented by subclass.") | |
| def tensor_parallel_enabled(self): | |
| raise NotImplementedError("Property `tensor_parallel_enabled` must be implemented by subclass.") | |