def test_1hop(self):
""" Test case for sample 1 hop neighbor with strategy of edge_weight.
All the src_ids have neighbors.
"""
expand_factor = 6
ids = self._seed_node1_ids
nbr_s = self.g.neighbor_sampler(self._edge1_type,
expand_factor=expand_factor,
strategy="edge_weight")
nbrs = nbr_s.get(ids)
edges = nbrs.layer_edges(1)
nodes = nbrs.layer_nodes(1)
utils.check_fixed_edge_dst_ids(edges, dst_range=self._node2_range,
expected_src_ids=ids)
utils.check_edge_type(edges,
src_type=self._node1_type,
dst_type=self._node2_type,
edge_type=self._edge1_type)
utils.check_edge_shape(edges, ids.size * expand_factor)
utils.check_edge_attrs(edges)
utils.check_edge_labels(edges)
utils.check_equal(nodes.ids, edges.dst_ids)
utils.check_node_ids(nodes, self._node2_ids)
utils.check_node_type(nodes, node_type=self._node2_type)
utils.check_node_shape(nodes, ids.size * expand_factor)
utils.check_node_weights(nodes)
utils.check_node_labels(nodes)
def test_1hop_with_neighbor_missing(self):
""" Test case for sample 1 hop neighbor with strategy of edge_weight.
Some of src_ids have no neighbor.
"""
expand_factor = 6
ids = self._seed_node1_ids_with_nbr_missing
nbr_s = self.g.neighbor_sampler(self._edge1_type,
expand_factor=expand_factor,
strategy="edge_weight")
nbrs = nbr_s.get(ids)
edges = nbrs.layer_edges(1)
nodes = nbrs.layer_nodes(1)
utils.check_fixed_edge_dst_ids(edges, dst_range=self._node2_range,
expected_src_ids=ids,
default_dst_id=self._default_dst_id)
utils.check_edge_type(edges,
src_type=self._node1_type,
dst_type=self._node2_type,
edge_type=self._edge1_type)
utils.check_edge_shape(edges, ids.size * expand_factor)
utils.check_not_exist_edge_attrs(
edges, default_int_attr=self._default_int_attr,
default_float_attr=self._default_float_attr,
default_string_attr=self._default_string_attr,)
utils.check_not_exist_edge_labels(edges)
utils.check_equal(nodes.ids, edges.dst_ids)
utils.check_node_ids(nodes, [self._default_dst_id])
utils.check_node_type(nodes, node_type=self._node2_type)
utils.check_node_shape(nodes, ids.size * expand_factor)
utils.check_not_exist_node_weights(nodes)
utils.check_not_exist_node_labels(nodes)
def test_1hop_using_gsl(self):
""" Using gsl api.
"""
gl.set_eager_mode(True)
expand_factor = 6
ids = self._seed_node1_ids
nbrs = self.g.V(self._node1_type, feed=ids) \
.outE(self._edge1_type).sample(expand_factor).by("in_degree") \
.inV().emit()
edges = nbrs[1]
nodes = nbrs[2]
utils.check_fixed_edge_dst_ids(edges,
dst_range=self._node2_range,
expected_src_ids=ids)
utils.check_edge_type(edges,
src_type=self._node1_type,
dst_type=self._node2_type,
edge_type=self._edge1_type)
utils.check_edge_shape(edges, ids.size * expand_factor)
utils.check_edge_attrs(edges)
utils.check_edge_labels(edges)
utils.check_equal(nodes.ids, edges.dst_ids)
utils.check_node_ids(nodes, self._node2_ids)
utils.check_node_type(nodes, node_type=self._node2_type)
utils.check_node_shape(nodes, ids.size * expand_factor)
utils.check_node_weights(nodes)
utils.check_node_labels(nodes)
def test_1hop_using_gsl(self):
""" Test case for sample 1 hop neighbor.
hetegerous graph with edge attrs, without edge weight.
"""
gl.set_eager_mode(True)
expand_factor = 6
ids = self._seed_node1_ids
nbrs = self.g.V(self._node1_type, feed=ids) \
.outE(self._edge1_type).sample(expand_factor).by("edge_weight") \
.inV().emit()
edges = nbrs[1]
nodes = nbrs[2]
utils.check_fixed_edge_dst_ids(edges, dst_range=self._node2_range,
expected_src_ids=ids)
utils.check_edge_type(edges,
src_type=self._node1_type,
dst_type=self._node2_type,
edge_type=self._edge1_type)
utils.check_edge_shape(edges, ids.size * expand_factor)
utils.check_edge_attrs(edges)
utils.check_edge_labels(edges)
utils.check_equal(nodes.ids, edges.dst_ids)
utils.check_node_ids(nodes, self._node2_ids)
utils.check_node_type(nodes, node_type=self._node2_type)
utils.check_node_shape(nodes, ids.size * expand_factor)
utils.check_node_weights(nodes)
utils.check_node_labels(nodes)
def test_1hop(self):
""" Sample one hop of neighbors.
"""
expand_factor = 6
ids = self._seed_node1_ids
nbr_s = self.g.neighbor_sampler(self._edge1_type,
expand_factor=expand_factor,
strategy="random")
nbrs = nbr_s.get(ids)
edges = nbrs.layer_edges(1)
nodes = nbrs.layer_nodes(1)
print(edges.src_nodes.get_out_degrees(self._edge1_type))
utils.check_fixed_edge_dst_ids(edges, dst_range=self._node2_range,
expected_src_ids=ids)
utils.check_edge_type(edges,
src_type=self._node1_type,
dst_type=self._node2_type,
edge_type=self._edge1_type)
utils.check_edge_shape(edges, ids.size * expand_factor)
utils.check_edge_attrs(edges)
utils.check_edge_labels(edges)
utils.check_equal(nodes.ids, edges.dst_ids)
utils.check_node_ids(nodes, self._node2_ids)
utils.check_node_type(nodes, node_type=self._node2_type)
utils.check_node_shape(nodes, ids.size * expand_factor)
utils.check_node_weights(nodes)
utils.check_node_labels(nodes)
def test_1hop_with_neighbor_missing(self):
""" Sample neighbors for nodes which have no out neighbors,
and get the default neighbor id.
"""
expand_factor = 6
ids = self._seed_node1_ids_with_nbr_missing
nbr_s = self.g.neighbor_sampler(self._edge1_type,
expand_factor=expand_factor,
strategy="in_degree")
nbrs = nbr_s.get(ids)
edges = nbrs.layer_edges(1)
nodes = nbrs.layer_nodes(1)
utils.check_fixed_edge_dst_ids(edges, dst_range=self._node2_range,
expected_src_ids=ids,
default_dst_id=self._default_dst_id)
utils.check_edge_type(edges,
src_type=self._node1_type,
dst_type=self._node2_type,
edge_type=self._edge1_type)
utils.check_edge_shape(edges, ids.size * expand_factor)
utils.check_not_exist_edge_attrs(
edges, default_int_attr=self._default_int_attr,
default_float_attr=self._default_float_attr,
default_string_attr=self._default_string_attr,)
utils.check_not_exist_edge_labels(edges)
utils.check_equal(nodes.ids, edges.dst_ids)
utils.check_node_ids(nodes, [self._default_dst_id])
utils.check_node_type(nodes, node_type=self._node2_type)
utils.check_node_shape(nodes, ids.size * expand_factor)
utils.check_not_exist_node_weights(nodes)
utils.check_not_exist_node_labels(nodes)
def test_sampling_with_mask_eager_mode(self):
gl.set_eager_mode(True)
bs = 8
q = self.g.E(self._edge1_type, mask=gl.Mask.VAL).batch(bs).alias('val') \
.each(
lambda e:
(e.outV().alias('src'),
e.inV().alias('dst') \
.outV(self._edge2_type).sample(3).by('topk').alias('nbr'))
).values(lambda x:
(x['src'].ids,
x['val'].labels,
x['dst'].ids, x['dst'].weights, x['dst'].labels,
x['nbr'].ids, x['nbr'].int_attrs))
iteration = 0
for i in range(2):
res = []
while True:
try:
sid, elb, did, dwei, dlb, nid, ni = q.next()
utils.check_id_weights(did, dwei)
utils.check_equal(dlb, did)
iteration += 1
res += list(sid)
except gl.OutOfRangeError:
break
whole = range(self._val_node_range[0], self._val_node_range[1])
expected = []
for elem in whole:
expected += [elem] * len(
utils.fixed_dst_ids(elem, self._node2_range))
utils.check_sorted_equal(res, expected)
def test_negative_sample(self):
q = self.g.V(self._node1_type).batch(2).alias('a') \
.outNeg(self._edge1_type).sample(5).by("random").alias('b') \
.values(lambda x: (x['a'].ids, x['b'].weights))
dataset = gl.Dataset(q)
res = dataset.next()
utils.check_equal(list(res[0].shape), [2])
utils.check_equal(list(res[1].shape), [2, 5])
def test_2hop(self):
""" Sample 2 hops of neighbors.
"""
gl.set_eager_mode(True)
expand_factor = [3, 2]
ids = self._seed_node1_ids
nbr_s = self.g.neighbor_sampler([self._edge1_type, self._edge2_type],
expand_factor=expand_factor,
strategy="in_degree")
nbrs = nbr_s.get(ids)
edges = nbrs.layer_edges(1)
nodes = nbrs.layer_nodes(1)
utils.check_fixed_edge_dst_ids(edges,
dst_range=self._node2_range,
expected_src_ids=ids)
utils.check_edge_type(edges,
src_type=self._node1_type,
dst_type=self._node2_type,
edge_type=self._edge1_type)
utils.check_edge_shape(edges, ids.size * expand_factor[0])
utils.check_edge_attrs(edges)
utils.check_edge_labels(edges)
utils.check_equal(nodes.ids, edges.dst_ids)
utils.check_node_ids(nodes, self._node2_ids)
utils.check_node_type(nodes, node_type=self._node2_type)
utils.check_node_shape(nodes, ids.size * expand_factor[0])
utils.check_node_weights(nodes)
utils.check_node_labels(nodes)
ids = nodes.ids.reshape(-1)
edges = nbrs.layer_edges(2)
nodes = nbrs.layer_nodes(2)
utils.check_fixed_edge_dst_ids(edges,
dst_range=self._node1_range,
expected_src_ids=ids)
utils.check_edge_type(edges,
src_type=self._node2_type,
dst_type=self._node1_type,
edge_type=self._edge2_type)
utils.check_edge_shape(edges, ids.size * expand_factor[1])
utils.check_edge_attrs(edges)
utils.check_edge_weights(edges)
utils.check_equal(nodes.ids, edges.dst_ids)
utils.check_node_ids(nodes, self._node1_ids)
utils.check_node_type(nodes, node_type=self._node1_type)
utils.check_node_shape(nodes, ids.size * expand_factor[1])
def test_sample_with_filter(self):
q = self.g.E(self._edge1_type).batch(4).alias("a") \
.each(lambda e:
(e.inV().alias('dst'),
e.outV().alias('src') \
.outV(self._edge1_type).sample(2).by("random").filter('dst').alias("b")
)
) \
.values()
dataset = gl.Dataset(q)
while True:
try:
res = dataset.next()
utils.check_equal(list(res['b'].shape), [4, 2])
filter_ids = res['dst'].ids
remained_ids = res['b'].ids
for fid, rid in zip(filter_ids, remained_ids):
assert fid not in rid
except gl.OutOfRangeError:
break
def test_iterate_edge_with_1hop(self):
q = self.g.E(self._edge1_type).batch(4).alias("a") \
.outV().alias("b") \
.outV(self._edge1_type).sample(2).by("random").alias("c") \
.values()
dataset = gl.Dataset(q)
while True:
try:
res = dataset.next()
utils.check_equal(list(res['a'].shape), [4])
utils.check_equal(list(res['b'].shape), [4])
utils.check_equal(list(res['b'].int_attrs.shape), [4, 2]) # [batch_size, int_attr_num]
utils.check_equal(list(res['c'].shape), [4, 2])
except gl.OutOfRangeError:
break
def test_sample_edge(self):
q = self.g.V(self._node1_type).batch(8).alias('a') \
.outE(self._edge1_type).sample(3).by("random").alias('b') \
.inV().alias('c') \
.values()
dataset = gl.Dataset(q)
res = dataset.next()
utils.check_equal(list(res['a'].shape), [8])
utils.check_equal(list(res['b'].shape), [8, 3])
utils.check_equal(list(res['c'].shape), [8, 3])
def test_iterate_node_with_2hop(self):
q = self.g.V(self._node1_type).batch(2).alias('a') \
.outV(self._edge1_type).sample(3).by('random').alias('b') \
.outV(self._edge2_type).sample(4).by('random').alias('c') \
.values()
dataset = gl.Dataset(q, 10)
while True:
try:
res = dataset.next()
utils.check_equal(list(res['a'].shape), [2])
utils.check_equal(list(res['b'].shape), [2, 3])
utils.check_equal(list(res['c'].shape), [2 * 3, 4])
except gl.OutOfRangeError:
break
