microsoft/qlib · error · SeedIteratorNotAvailable

Seed iterator for validation is not available.

Error message

Seed iterator for validation is not available.

What it means

SeedIteratorNotAvailable from the default `Vessel.val_seed_iterator` (qlib/rl/trainer/vessel.py:60). Same abstract-method contract as the training variant, but for the validation set: the trainer fetches validation initial states from this hook when running validation during/after training.

Source

Thrown at qlib/rl/trainer/vessel.py:60

    simulator_fn: Callable[[InitialStateType], Simulator[InitialStateType, StateType, ActType]]
    state_interpreter: StateInterpreter[StateType, ObsType]
    action_interpreter: ActionInterpreter[StateType, PolicyActType, ActType]
    policy: BasePolicy
    reward: Reward
    trainer: Trainer

    def assign_trainer(self, trainer: Trainer) -> None:
        self.trainer = weakref.proxy(trainer)  # type: ignore

    def train_seed_iterator(self) -> ContextManager[Iterable[InitialStateType]] | Iterable[InitialStateType]:
        """Override this to create a seed iterator for training.
        If the iterable is a context manager, the whole training will be invoked in the with-block,
        and the iterator will be automatically closed after the training is done."""
        raise SeedIteratorNotAvailable("Seed iterator for training is not available.")

    def val_seed_iterator(self) -> ContextManager[Iterable[InitialStateType]] | Iterable[InitialStateType]:
        """Override this to create a seed iterator for validation."""
        raise SeedIteratorNotAvailable("Seed iterator for validation is not available.")

    def test_seed_iterator(self) -> ContextManager[Iterable[InitialStateType]] | Iterable[InitialStateType]:
        """Override this to create a seed iterator for testing."""
        raise SeedIteratorNotAvailable("Seed iterator for testing is not available.")

    def train(self, vector_env: BaseVectorEnv) -> Dict[str, Any]:
        """Implement this to train one iteration. In RL, one iteration usually refers to one collect."""
        raise NotImplementedError()

    def validate(self, vector_env: FiniteVectorEnv) -> Dict[str, Any]:
        """Implement this to validate the policy once."""
        raise NotImplementedError()

    def test(self, vector_env: FiniteVectorEnv) -> Dict[str, Any]:
        """Implement this to evaluate the policy on test environment once."""
        raise NotImplementedError()

    def log(self, name: str, value: Any) -> None:

View on GitHub (pinned to 79633dd950)

Solutions

1. Override `val_seed_iterator` to return the iterable of validation initial states (typically a held-out date/order split).
2. If you don't want validation, remove validation-triggering callbacks/arguments rather than letting the exception fire.
3. To reuse training data for validation, return the same generator factory (fresh instance, not an exhausted iterator).

Example fix

// before
class MyVessel(Vessel):
    def train_seed_iterator(self): return iter(train_orders)
    # val_seed_iterator missing -> error when EarlyStopping validates
// after
class MyVessel(Vessel):
    def train_seed_iterator(self): return iter(train_orders)
    def val_seed_iterator(self): return iter(val_orders)

from qlib.rl.trainer.vessel import Vessel

def val_seeds_available(vessel: Vessel) -> bool:
    return type(vessel).val_seed_iterator is not Vessel.val_seed_iterator

def vessel_supports_validation(v) -> bool:
    from qlib.rl.trainer.vessel import Vessel
    return type(v).val_seed_iterator is not Vessel.val_seed_iterator

from qlib.rl.trainer.vessel import SeedIteratorNotAvailable
try:
    trainer.validate(vessel)
except SeedIteratorNotAvailable:
    log.warning("no validation seed iterator; skipping validation")

When it happens

Trigger: A vessel without a `val_seed_iterator` override used with `Trainer.fit(...)` while `num_episode`/callbacks request validation, or an explicit `trainer.validate(vessel)` call.

Common situations: Teams implement training seeds first and forget validation; validation intended to reuse the train iterator but the hook was never wired; EarlyStopping callback configured with a monitor, which forces validation and surfaces the missing override.

Related errors

• Seed iterator for training is not available.
• Seed iterator for testing is not available.
• Sample must be a dict with same length as space.
• Unexpected order direction: {direction}
• Unexpected order direction: {direction}

AI-assisted analysis of microsoft/qlib@79633dd950 (2026-08-15). Data as JSON: /api/errors/8ca5bbb740825961. Report an issue: GitHub.