""" NOTE(zihao) The unittest on shared memory store is temporally disabled because we have not fixed the bug described in https://github.com/dmlc/dgl/issues/755 yet. The bug causes CI failures occasionally but does not affect other parts of DGL. As a result, we decide to disable this test until we fixed the bug. """ import dgl import sys import random import time import numpy as np from numpy.testing import assert_array_equal from multiprocessing import Process, Manager from scipy import sparse as spsp import backend as F import unittest import dgl.function as fn import traceback from numpy.testing import assert_almost_equal num_nodes = 100 num_edges = int(num_nodes * num_nodes * 0.1) rand_port = random.randint(5000, 8000) print('run graph store with port ' + str(rand_port), file=sys.stderr) def check_array_shared_memory(g, worker_id, arrays): if worker_id == 0: for i, arr in enumerate(arrays): arr[0] = i + 10 g._sync_barrier(60) else: g._sync_barrier(60) for i, arr in enumerate(arrays): assert_almost_equal(F.asnumpy(arr[0]), i + 10) def create_graph_store(graph_name): for _ in range(10): try: g = dgl.contrib.graph_store.create_graph_from_store(graph_name, "shared_mem", port=rand_port) return g except ConnectionError as e: traceback.print_exc() time.sleep(1) return None def check_init_func(worker_id, graph_name, return_dict): time.sleep(3) print("worker starts") np.random.seed(0) csr = (spsp.random(num_nodes, num_nodes, density=0.1, format='csr') != 0).astype(np.int64) # Verify the graph structure loaded from the shared memory. try: g = create_graph_store(graph_name) if g is None: return_dict[worker_id] = -1 return src, dst = g.all_edges() coo = csr.tocoo() assert_array_equal(F.asnumpy(dst), coo.row) assert_array_equal(F.asnumpy(src), coo.col) feat = F.asnumpy(g.nodes[0].data['feat']) assert_array_equal(np.squeeze(feat), np.arange(10, dtype=feat.dtype)) feat = F.asnumpy(g.edges[0].data['feat']) assert_array_equal(np.squeeze(feat), np.arange(10, dtype=feat.dtype)) g.init_ndata('test4', (g.number_of_nodes(), 10), 'float32') g.init_edata('test4', (g.number_of_edges(), 10), 'float32') g._sync_barrier(60) check_array_shared_memory(g, worker_id, [g.nodes[:].data['test4'], g.edges[:].data['test4']]) data = g.nodes[:].data['test4'] g.set_n_repr({'test4': F.ones((1, 10)) * 10}, u=[0]) assert_almost_equal(F.asnumpy(data[0]), np.squeeze(F.asnumpy(g.nodes[0].data['test4']))) data = g.edges[:].data['test4'] g.set_e_repr({'test4': F.ones((1, 10)) * 20}, edges=[0]) assert_almost_equal(F.asnumpy(data[0]), np.squeeze(F.asnumpy(g.edges[0].data['test4']))) g.destroy() return_dict[worker_id] = 0 except Exception as e: return_dict[worker_id] = -1 g.destroy() print(e, file=sys.stderr) traceback.print_exc() def server_func(num_workers, graph_name): print("server starts") np.random.seed(0) csr = (spsp.random(num_nodes, num_nodes, density=0.1, format='csr') != 0).astype(np.int64) g = dgl.contrib.graph_store.create_graph_store_server(csr, graph_name, "shared_mem", num_workers, False, edge_dir="in", port=rand_port) assert num_nodes == g._graph.number_of_nodes() assert num_edges == g._graph.number_of_edges() nfeat = np.arange(0, num_nodes * 10).astype('float32').reshape((num_nodes, 10)) efeat = np.arange(0, num_edges * 10).astype('float32').reshape((num_edges, 10)) g.ndata['feat'] = F.tensor(nfeat) g.edata['feat'] = F.tensor(efeat) g.run() @unittest.skip def test_init(): manager = Manager() return_dict = manager.dict() serv_p = Process(target=server_func, args=(2, 'test_graph1')) work_p1 = Process(target=check_init_func, args=(0, 'test_graph1', return_dict)) work_p2 = Process(target=check_init_func, args=(1, 'test_graph1', return_dict)) serv_p.start() work_p1.start() work_p2.start() serv_p.join() work_p1.join() work_p2.join() for worker_id in return_dict.keys(): assert return_dict[worker_id] == 0, "worker %d fails" % worker_id def check_compute_func(worker_id, graph_name, return_dict): time.sleep(3) print("worker starts") try: g = create_graph_store(graph_name) if g is None: return_dict[worker_id] = -1 return g._sync_barrier(60) in_feats = g.nodes[0].data['feat'].shape[1] # Test update all. g.update_all(fn.copy_src(src='feat', out='m'), fn.sum(msg='m', out='preprocess')) adj = g.adjacency_matrix() tmp = F.spmm(adj, g.nodes[:].data['feat']) assert_almost_equal(F.asnumpy(g.nodes[:].data['preprocess']), F.asnumpy(tmp)) g._sync_barrier(60) check_array_shared_memory(g, worker_id, [g.nodes[:].data['preprocess']]) # Test apply nodes. data = g.nodes[:].data['feat'] g.apply_nodes(func=lambda nodes: {'feat': F.ones((1, in_feats)) * 10}, v=0) assert_almost_equal(F.asnumpy(data[0]), np.squeeze(F.asnumpy(g.nodes[0].data['feat']))) # Test apply edges. data = g.edges[:].data['feat'] g.apply_edges(func=lambda edges: {'feat': F.ones((1, in_feats)) * 10}, edges=0) assert_almost_equal(F.asnumpy(data[0]), np.squeeze(F.asnumpy(g.edges[0].data['feat']))) g.init_ndata('tmp', (g.number_of_nodes(), 10), 'float32') data = g.nodes[:].data['tmp'] # Test pull g.pull(1, fn.copy_src(src='feat', out='m'), fn.sum(msg='m', out='tmp')) assert_almost_equal(F.asnumpy(data[1]), np.squeeze(F.asnumpy(g.nodes[1].data['preprocess']))) # Test send_and_recv in_edges = g.in_edges(v=2) g.send_and_recv(in_edges, fn.copy_src(src='feat', out='m'), fn.sum(msg='m', out='tmp')) assert_almost_equal(F.asnumpy(data[2]), np.squeeze(F.asnumpy(g.nodes[2].data['preprocess']))) g.destroy() return_dict[worker_id] = 0 except Exception as e: return_dict[worker_id] = -1 g.destroy() print(e, file=sys.stderr) traceback.print_exc() @unittest.skip def test_compute(): manager = Manager() return_dict = manager.dict() serv_p = Process(target=server_func, args=(2, 'test_graph3')) work_p1 = Process(target=check_compute_func, args=(0, 'test_graph3', return_dict)) work_p2 = Process(target=check_compute_func, args=(1, 'test_graph3', return_dict)) serv_p.start() work_p1.start() work_p2.start() serv_p.join() work_p1.join() work_p2.join() for worker_id in return_dict.keys(): assert return_dict[worker_id] == 0, "worker %d fails" % worker_id def check_sync_barrier(worker_id, graph_name, return_dict): time.sleep(3) print("worker starts") try: g = create_graph_store(graph_name) if g is None: return_dict[worker_id] = -1 return if worker_id == 1: g.destroy() return_dict[worker_id] = 0 return start = time.time() try: g._sync_barrier(10) except TimeoutError as e: # this is very loose. print("timeout: " + str(abs(time.time() - start)), file=sys.stderr) assert 5 < abs(time.time() - start) < 15 g.destroy() return_dict[worker_id] = 0 except Exception as e: return_dict[worker_id] = -1 g.destroy() print(e, file=sys.stderr) traceback.print_exc() @unittest.skip def test_sync_barrier(): manager = Manager() return_dict = manager.dict() serv_p = Process(target=server_func, args=(2, 'test_graph4')) work_p1 = Process(target=check_sync_barrier, args=(0, 'test_graph4', return_dict)) work_p2 = Process(target=check_sync_barrier, args=(1, 'test_graph4', return_dict)) serv_p.start() work_p1.start() work_p2.start() serv_p.join() work_p1.join() work_p2.join() for worker_id in return_dict.keys(): assert return_dict[worker_id] == 0, "worker %d fails" % worker_id def create_mem(gidx): gidx1 = gidx.copyto_shared_mem("in", "test_graph5") gidx2 = gidx.copyto_shared_mem("out", "test_graph6") time.sleep(30) def check_mem(gidx): time.sleep(10) gidx1 = dgl.graph_index.from_shared_mem_csr_matrix("test_graph5", gidx.number_of_nodes(), gidx.number_of_edges(), "in", False) gidx2 = dgl.graph_index.from_shared_mem_csr_matrix("test_graph6", gidx.number_of_nodes(), gidx.number_of_edges(), "out", False) in_csr = gidx.adjacency_matrix_scipy(False, "csr") out_csr = gidx.adjacency_matrix_scipy(True, "csr") in_csr1 = gidx1.adjacency_matrix_scipy(False, "csr") assert_array_equal(in_csr.indptr, in_csr1.indptr) assert_array_equal(in_csr.indices, in_csr1.indices) out_csr1 = gidx1.adjacency_matrix_scipy(True, "csr") assert_array_equal(out_csr.indptr, out_csr1.indptr) assert_array_equal(out_csr.indices, out_csr1.indices) in_csr2 = gidx2.adjacency_matrix_scipy(False, "csr") assert_array_equal(in_csr.indptr, in_csr2.indptr) assert_array_equal(in_csr.indices, in_csr2.indices) out_csr2 = gidx2.adjacency_matrix_scipy(True, "csr") assert_array_equal(out_csr.indptr, out_csr2.indptr) assert_array_equal(out_csr.indices, out_csr2.indices) gidx1 = gidx1.copyto_shared_mem("in", "test_graph5") gidx2 = gidx2.copyto_shared_mem("out", "test_graph6") @unittest.skip def test_copy_shared_mem(): csr = (spsp.random(num_nodes, num_nodes, density=0.1, format='csr') != 0).astype(np.int64) gidx = dgl.graph_index.create_graph_index(csr, False, True) p1 = Process(target=create_mem, args=(gidx,)) p2 = Process(target=check_mem, args=(gidx,)) p1.start() p2.start() p1.join() p2.join() if __name__ == '__main__': test_copy_shared_mem() test_init() test_sync_barrier() test_compute()