Odd behavior on neighbor sampling with neighbor type set to "out"

I’m a bit confused about some of the behavior with the neighbor sampling. It seems that when the neighbor_type is set to out eid’s are returned per block but not the actual edges themselves.

import dgl
import numpy as np
from dgl.contrib.sampling import NeighborSampler

def build_karate_club_graph():
    # All 78 edges are stored in two numpy arrays. One for source endpoints
    # while the other for destination endpoints.
    src = np.array([1, 2, 2, 3, 3, 3, 4, 5, 6, 6, 6, 7, 7, 7, 7, 8, 8, 9, 10, 10,
        10, 11, 12, 12, 13, 13, 13, 13, 16, 16, 17, 17, 19, 19, 21, 21,
        25, 25, 27, 27, 27, 28, 29, 29, 30, 30, 31, 31, 31, 31, 32, 32,
        32, 32, 32, 32, 32, 32, 32, 32, 32, 33, 33, 33, 33, 33, 33, 33,
        33, 33, 33, 33, 33, 33, 33, 33, 33, 33])
    dst = np.array([0, 0, 1, 0, 1, 2, 0, 0, 0, 4, 5, 0, 1, 2, 3, 0, 2, 2, 0, 4,
        5, 0, 0, 3, 0, 1, 2, 3, 5, 6, 0, 1, 0, 1, 0, 1, 23, 24, 2, 23,
        24, 2, 23, 26, 1, 8, 0, 24, 25, 28, 2, 8, 14, 15, 18, 20, 22, 23,
        29, 30, 31, 8, 9, 13, 14, 15, 18, 19, 20, 22, 23, 26, 27, 28, 29, 30,
        31, 32])
    # Edges are directional in DGL; Make them bi-directional.
    u = np.concatenate([src, dst])
    v = np.concatenate([dst, src])
    # Construct a DGLGraph
    return dgl.DGLGraph((u, v))


G = build_karate_club_graph()
G.readonly()
for nf in NeighborSampler(
        G,
        batch_size=10,
        expand_factor=10,
        neighbor_type="in",
        num_hops=1,
):
    print(f" In neighbor eids: {nf.block_eid(0)}")
    print(f"In neighbor edges: {nf.block_edges(0)}")

for nf in NeighborSampler(
        G,
        batch_size=10,
        expand_factor=10,
        neighbor_type="out",
        num_hops=1,
):
    print(f"Out neighbor eids: {nf.block_eid(0)}")
    print(f"Out neighbor edges: {nf.block_edges(0)}")

Looks correct for In neighbor edges but returns an empty array for Out neighbor edges Is this correct?

Thanks!