chore: import upstream snapshot with attribution

python/ray/train/v2/api/reported_checkpoint.py

@@ -0,0 +1,43 @@
+from dataclasses import dataclass
+from enum import Enum
+from typing import TYPE_CHECKING, Any, Dict
+
+from ray.util.annotations import PublicAPI
+
+if TYPE_CHECKING:
+    from ray.train import Checkpoint
+
+
+@PublicAPI(stability="alpha")
+class ReportedCheckpointStatus(Enum):
+    """ReportedCheckpoint status enum.
+
+    * COMMITTED: The checkpoint is saved, and no validation was requested.
+    * PENDING_VALIDATION: The checkpoint is saved, and validation is in progress.
+    * VALIDATED: The checkpoint is saved, and validation is complete.
+    * VALIDATION_TIMEOUT: The checkpoint is saved, and validation is timed out according to
+        `ValidationTaskConfig(..., timeout_s=N)`.
+    * VALIDATION_FAILED: The checkpoint is saved, and validation failed.
+    """
+
+    COMMITTED = "COMMITTED"
+    PENDING_VALIDATION = "PENDING_VALIDATION"
+    VALIDATED = "VALIDATED"
+    VALIDATION_TIMEOUT = "VALIDATION_TIMEOUT"
+    VALIDATION_FAILED = "VALIDATION_FAILED"
+
+
+@dataclass
+@PublicAPI(stability="alpha")
+class ReportedCheckpoint:
+    """A user-reported checkpoint and its associated metrics.
+
+    Attributes:
+        checkpoint: The checkpoint reported by the user.
+        metrics: The metrics associated with that checkpoint.
+        status: The status of the checkpoint.
+    """
+
+    checkpoint: "Checkpoint"
+    metrics: Dict[str, Any]
+    status: ReportedCheckpointStatus