def check_standalone_etype_sampling(tmpdir, reshuffle):
hg = CitationGraphDataset('cora')[0]
num_parts = 1
num_hops = 1
partition_graph(hg,
'test_sampling',
num_parts,
tmpdir,
num_hops=num_hops,
part_method='metis',
reshuffle=reshuffle)
os.environ['DGL_DIST_MODE'] = 'standalone'
dgl.distributed.initialize("rpc_ip_config.txt")
dist_graph = DistGraph("test_sampling",
part_config=tmpdir / 'test_sampling.json')
sampled_graph = sample_etype_neighbors(dist_graph, [0, 10, 99, 66, 1023],
dgl.ETYPE, 3)
src, dst = sampled_graph.edges()
assert sampled_graph.number_of_nodes() == hg.number_of_nodes()
assert np.all(F.asnumpy(hg.has_edges_between(src, dst)))
eids = hg.edge_ids(src, dst)
assert np.array_equal(F.asnumpy(sampled_graph.edata[dgl.EID]),
F.asnumpy(eids))
dgl.distributed.exit_client()
def check_rpc_sampling(tmpdir, num_server):
ip_config = open("rpc_ip_config.txt", "w")
for _ in range(num_server):
ip_config.write('{} 1\n'.format(get_local_usable_addr()))
ip_config.close()
g = CitationGraphDataset("cora")[0]
g.readonly()
print(g.idtype)
num_parts = num_server
num_hops = 1
partition_graph(g, 'test_sampling', num_parts, tmpdir,
num_hops=num_hops, part_method='metis', reshuffle=False)
pserver_list = []
ctx = mp.get_context('spawn')
for i in range(num_server):
p = ctx.Process(target=start_server, args=(i, tmpdir, num_server > 1, 'test_sampling'))
p.start()
time.sleep(1)
pserver_list.append(p)
time.sleep(3)
sampled_graph = start_sample_client(0, tmpdir, num_server > 1)
print("Done sampling")
for p in pserver_list:
p.join()
src, dst = sampled_graph.edges()
assert sampled_graph.number_of_nodes() == g.number_of_nodes()
assert np.all(F.asnumpy(g.has_edges_between(src, dst)))
eids = g.edge_ids(src, dst)
assert np.array_equal(
F.asnumpy(sampled_graph.edata[dgl.EID]), F.asnumpy(eids))
def check_standalone_sampling(tmpdir):
g = CitationGraphDataset("cora")[0]
g.readonly()
num_parts = 1
num_hops = 1
partition_graph(g,
'test_sampling',
num_parts,
tmpdir,
num_hops=num_hops,
part_method='metis',
reshuffle=False)
dist_graph = DistGraph(None,
"test_sampling",
conf_file=tmpdir / 'test_sampling.json')
sampled_graph = sample_neighbors(dist_graph, [0, 10, 99, 66, 1024, 2008],
3)
src, dst = sampled_graph.edges()
assert sampled_graph.number_of_nodes() == g.number_of_nodes()
assert np.all(F.asnumpy(g.has_edges_between(src, dst)))
eids = g.edge_ids(src, dst)
assert np.array_equal(F.asnumpy(sampled_graph.edata[dgl.EID]),
F.asnumpy(eids))
def check_rpc_in_subgraph_shuffle(tmpdir, num_server):
ip_config = open("rpc_ip_config.txt", "w")
for _ in range(num_server):
ip_config.write('{}\n'.format(get_local_usable_addr()))
ip_config.close()
g = CitationGraphDataset("cora")[0]
g.readonly()
num_parts = num_server
partition_graph(g,
'test_in_subgraph',
num_parts,
tmpdir,
num_hops=1,
part_method='metis',
reshuffle=True)
pserver_list = []
ctx = mp.get_context('spawn')
for i in range(num_server):
p = ctx.Process(target=start_server,
args=(i, tmpdir, num_server > 1, 'test_in_subgraph'))
p.start()
time.sleep(1)
pserver_list.append(p)
nodes = [0, 10, 99, 66, 1024, 2008]
time.sleep(3)
sampled_graph = start_in_subgraph_client(0, tmpdir, num_server > 1, nodes)
for p in pserver_list:
p.join()
orig_nid = F.zeros((g.number_of_nodes(), ), dtype=F.int64, ctx=F.cpu())
orig_eid = F.zeros((g.number_of_edges(), ), dtype=F.int64, ctx=F.cpu())
for i in range(num_server):
part, _, _, _, _, _, _ = load_partition(
tmpdir / 'test_in_subgraph.json', i)
orig_nid[part.ndata[dgl.NID]] = part.ndata['orig_id']
orig_eid[part.edata[dgl.EID]] = part.edata['orig_id']
src, dst = sampled_graph.edges()
src = orig_nid[src]
dst = orig_nid[dst]
assert sampled_graph.number_of_nodes() == g.number_of_nodes()
assert np.all(F.asnumpy(g.has_edges_between(src, dst)))
subg1 = dgl.in_subgraph(g, orig_nid[nodes])
src1, dst1 = subg1.edges()
assert np.all(np.sort(F.asnumpy(src)) == np.sort(F.asnumpy(src1)))
assert np.all(np.sort(F.asnumpy(dst)) == np.sort(F.asnumpy(dst1)))
eids = g.edge_ids(src, dst)
eids1 = orig_eid[sampled_graph.edata[dgl.EID]]
assert np.array_equal(F.asnumpy(eids1), F.asnumpy(eids))
def check_rpc_sampling_shuffle(tmpdir):
num_server = 2
ip_config = open("rpc_sampling_ip_config.txt", "w")
for _ in range(num_server):
ip_config.write('{} 1\n'.format(get_local_usable_addr()))
ip_config.close()
g = CitationGraphDataset("cora")[0]
g.readonly()
num_parts = num_server
num_hops = 1
partition_graph(g,
'test_sampling',
num_parts,
tmpdir,
num_hops=num_hops,
part_method='metis',
reshuffle=True)
pserver_list = []
ctx = mp.get_context('spawn')
for i in range(num_server):
p = ctx.Process(target=start_server, args=(i, tmpdir))
p.start()
time.sleep(1)
pserver_list.append(p)
time.sleep(3)
sampled_graph = start_client(0, tmpdir)
print("Done sampling")
for p in pserver_list:
p.join()
orig_nid = F.zeros((g.number_of_nodes(), ), dtype=F.int64)
orig_eid = F.zeros((g.number_of_edges(), ), dtype=F.int64)
for i in range(num_server):
part, _, _, _ = load_partition(tmpdir / 'test_sampling.json', i)
orig_nid[part.ndata[dgl.NID]] = part.ndata['orig_id']
orig_eid[part.edata[dgl.EID]] = part.edata['orig_id']
src, dst = sampled_graph.edges()
src = orig_nid[src]
dst = orig_nid[dst]
assert sampled_graph.number_of_nodes() == g.number_of_nodes()
assert np.all(F.asnumpy(g.has_edges_between(src, dst)))
eids = g.edge_ids(src, dst)
eids1 = orig_eid[sampled_graph.edata[dgl.EID]]
assert np.array_equal(F.asnumpy(eids1), F.asnumpy(eids))
def check_rpc_in_subgraph(tmpdir, num_server):
ip_config = open("rpc_ip_config.txt", "w")
for _ in range(num_server):
ip_config.write('{} 1\n'.format(get_local_usable_addr()))
ip_config.close()
g = CitationGraphDataset("cora")[0]
g.readonly()
num_parts = num_server
partition_graph(g,
'test_in_subgraph',
num_parts,
tmpdir,
num_hops=1,
part_method='metis',
reshuffle=False)
pserver_list = []
ctx = mp.get_context('spawn')
for i in range(num_server):
p = ctx.Process(target=start_server,
args=(i, tmpdir, num_server > 1, 'test_in_subgraph'))
p.start()
time.sleep(1)
pserver_list.append(p)
nodes = [0, 10, 99, 66, 1024, 2008]
time.sleep(3)
sampled_graph = start_in_subgraph_client(0, tmpdir, num_server > 1, nodes)
for p in pserver_list:
p.join()
src, dst = sampled_graph.edges()
g = dgl.as_heterograph(g)
assert sampled_graph.number_of_nodes() == g.number_of_nodes()
subg1 = dgl.in_subgraph(g, nodes)
src1, dst1 = subg1.edges()
assert np.all(np.sort(F.asnumpy(src)) == np.sort(F.asnumpy(src1)))
assert np.all(np.sort(F.asnumpy(dst)) == np.sort(F.asnumpy(dst1)))
eids = g.edge_ids(src, dst)
assert np.array_equal(F.asnumpy(sampled_graph.edata[dgl.EID]),
F.asnumpy(eids))
