Errors when saving ranking policies
What is recommended way to save ranking policies?
For each agent policy in the ranking tutorial, im getting errors like below when trying to save with PolicySaver
saver = policy_saver.PolicySaver(
policy = agent.policy,
batch_size=None
)
penalize_cosine_distance_ranking_policy error:
ValueError: Could not determine an appropriate value for field `logits` in object `tfp.distributions.CosinePenalizedPlackettLuce("PlackettLuce", batch_shape=[?],
event_shape=[3], dtype=int32)`. Looked for
1. an attr called `logits`,
2. an attr called `_logits`,
3. an entry in `obj.parameters` with key "logits".
no_penalty_ranking_policy error:
ValueError: Could not determine an appropriate value for field `features` in object `tfp.distributions.NoPenaltyPlackettLuce("PlackettLuce", batch_shape=[?], event_shape=[50], dtype=int32)`.
Looked for
1. an attr called `features`,
2. an attr called `_features`,
3. an entry in `obj.parameters` with key "features".
descending_score_ranking_policy error:
TypeError: To be compatible with tf.function, Python functions must return zero or more Tensors or ExtensionTypes or None values; in compilation of <function PolicySaver.__init__.<locals>.polymorphic_distribution_fn at 0x7ced7451f010>, found return value of type DescendingScoreSampler, which is not a Tensor or ExtensionType.
Hi @tottenjordan I'm having a similar issue, did you ever get an answer, or find a solution?