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Runs multiple additive regression ensemble predictors on input instances and

computes the update to cached logits. It is designed to be used during training. It traverses the trees starting from cached tree id and cached node id and calculates the updates to be pushed to the cache.

tree_ensemble_handle A Tensor of type resource.
cached_tree_ids A Tensor of type int32. Rank 1 Tensor containing cached tree ids which is the starting tree of prediction.
cached_node_ids A Tensor of type int32. Rank 1 Tensor containing cached node id which is the starting node of prediction.
bucketized_features A list of at least 1 Tensor objects with type int32. A list of rank 1 Tensors containing bucket id for each feature.
logits_dimension An int. scalar, dimension of the logits, to be used for partial logits shape.
name A name for the operation (optional).

A tuple of Tensor objects (partial_logits, tree_ids, node_ids).
partial_logits A Tensor of type float32.
tree_ids A Tensor of type int32.
node_ids A Tensor of type int32.