chore: import upstream snapshot with attribution

python/ray/train/backend.py

@@ -0,0 +1,74 @@
+import logging
+from contextlib import nullcontext
+from typing import Any, Dict, TypeVar
+
+from ray.train._internal.base_worker_group import BaseWorkerGroup
+from ray.train._internal.utils import Singleton
+from ray.util.annotations import DeveloperAPI
+from ray.widgets import make_table_html_repr
+
+EncodedData = TypeVar("EncodedData")
+
+logger = logging.getLogger(__name__)
+
+
+@DeveloperAPI
+class BackendConfig:
+    """Parent class for configurations of training backend."""
+
+    @property
+    def backend_cls(self):
+        return Backend
+
+    @property
+    def train_func_context(self):
+        return nullcontext
+
+    @property
+    def framework(self):
+        return None
+
+    def _repr_html_(self) -> str:
+        return make_table_html_repr(obj=self, title=type(self).__name__)
+
+    def to_dict(self) -> Dict[str, Any]:
+        """
+        Returns serializable dictionary representation of the backend config.
+        Subclasses can override this to expose framework-specific configuration.
+
+        The fields here are used for state export of the backend config.
+        If a field is not serializable, it should be excluded.
+        """
+        return {}
+
+
+@DeveloperAPI
+class Backend(metaclass=Singleton):
+    """Singleton for distributed communication backend.
+
+    Attributes:
+        share_cuda_visible_devices: If True, each worker
+            process will have CUDA_VISIBLE_DEVICES set as the visible device
+            IDs of all workers on the same node for this training instance.
+            If False, each worker will have CUDA_VISIBLE_DEVICES set to the
+            device IDs allocated by Ray for that worker.
+    """
+
+    share_cuda_visible_devices: bool = False
+    has_replica_groups: bool = False
+
+    def on_start(self, worker_group: BaseWorkerGroup, backend_config: BackendConfig):
+        """Logic for starting this backend."""
+        pass
+
+    def on_shutdown(self, worker_group: BaseWorkerGroup, backend_config: BackendConfig):
+        """Logic for shutting down the backend."""
+        pass
+
+    def on_training_start(
+        self, worker_group: BaseWorkerGroup, backend_config: BackendConfig
+    ):
+        """Logic ran right before training is started.
+
+        Session API is available at this point."""
+        pass