import multiprocessing as mp
import platform
import queue
import numpy as np
import pytest
import megengine as mge
import megengine.distributed as dist
from megengine.core.ops.builtin import CollectiveComm, ParamPackConcat, ParamPackSplit
from megengine.device import get_default_device
from megengine.distributed.helper import param_pack_concat, param_pack_split
def _assert_q_empty(q):
try:
res = q.get(timeout=1)
except Exception as e:
assert isinstance(e, queue.Empty)
else:
assert False, "queue is not empty"
def _assert_q_val(q, val):
ret = q.get()
assert ret == val
@pytest.mark.require_ngpu(2)
@pytest.mark.parametrize("backend", ["nccl"])
@pytest.mark.isolated_distributed
def test_init_process_group(backend):
world_size = 2
server = dist.Server()
port = server.py_server_port
def worker(rank):
dist.init_process_group("localhost", port, world_size, rank, rank, backend)
assert dist.is_distributed() == True
assert dist.get_rank() == rank
assert dist.get_world_size() == world_size
assert dist.get_backend() == backend
py_server_addr = dist.get_py_server_addr()
assert py_server_addr[0] == "localhost"
assert py_server_addr[1] == port
mm_server_addr = dist.get_mm_server_addr()
assert mm_server_addr[0] == "localhost"
assert mm_server_addr[1] > 0
assert isinstance(dist.get_client(), dist.Client)
procs = []
for rank in range(world_size):
p = mp.Process(target=worker, args=(rank,))
p.start()
procs.append(p)
for p in procs:
p.join(20)
assert p.exitcode == 0
@pytest.mark.require_ngpu(3)
@pytest.mark.isolated_distributed
def test_new_group():
world_size = 3
ranks = [2, 0]
@dist.launcher
def worker():
rank = dist.get_rank()
if rank in ranks:
group = dist.new_group(ranks)
assert group.size == 2
assert group.key == "2,0"
assert group.rank == ranks.index(rank)
dt = get_default_device()[:-1]
assert group.comp_node == "{}{}:2".format(dt, rank)
worker()
@pytest.mark.require_ngpu(2)
@pytest.mark.isolated_distributed
def test_group_barrier():
world_size = 2
server = dist.Server()
port = server.py_server_port
def worker(rank, q):
dist.init_process_group("localhost", port, world_size, rank, rank)
dist.group_barrier()
if rank == 0:
dist.group_barrier()
q.put(0) else:
_assert_q_empty(q) dist.group_barrier()
_assert_q_val(q, 0)
Q = mp.Queue()
procs = []
for rank in range(world_size):
p = mp.Process(target=worker, args=(rank, Q))
p.start()
procs.append(p)
for p in procs:
p.join(20)
assert p.exitcode == 0
@pytest.mark.require_ngpu(2)
@pytest.mark.isolated_distributed
def test_synchronized():
world_size = 2
server = dist.Server()
port = server.py_server_port
@dist.synchronized
def func(rank, q):
q.put(rank)
def worker(rank, q):
dist.init_process_group("localhost", port, world_size, rank, rank)
dist.group_barrier()
if rank == 0:
func(0, q) q.put(2)
else:
_assert_q_val(q, 0) _assert_q_empty(q) func(1, q)
_assert_q_val(
q, 1
) _assert_q_val(q, 2)
Q = mp.Queue()
procs = []
for rank in range(world_size):
p = mp.Process(target=worker, args=(rank, Q))
p.start()
procs.append(p)
for p in procs:
p.join(20)
assert p.exitcode == 0
@pytest.mark.require_ngpu(2)
@pytest.mark.isolated_distributed
def test_user_set_get():
@dist.launcher
def worker():
dist.get_client().user_set("foo", 1)
ret = dist.get_client().user_get("foo")
assert ret == 1
worker()
def test_oprmm_hashable():
lhs = (CollectiveComm(), ParamPackConcat(), ParamPackSplit())
rhs = (CollectiveComm(), ParamPackConcat(), ParamPackSplit())
assert lhs == rhs
assert hash(lhs) == hash(rhs)
def test_param_pack_split():
a = mge.Tensor(np.ones((10,), np.int32))
b, c = param_pack_split(a, [0, 1, 1, 10], [(1,), (3, 3)])
assert np.allclose(b.numpy(), a.numpy()[1])
assert np.allclose(c.numpy(), a.numpy()[1:].reshape(3, 3))
def test_param_pack_concat():
a = mge.Tensor(np.ones((1,), np.int32))
b = mge.Tensor(np.ones((3, 3), np.int32))
offsets_val = [0, 1, 1, 10]
offsets = mge.Tensor(offsets_val, np.int32)
c = param_pack_concat([a, b], offsets, offsets_val)
assert np.allclose(np.concatenate([a.numpy(), b.numpy().flatten()]), c.numpy())
@pytest.mark.require_ngpu(2)
@pytest.mark.parametrize("early_return", [False, True], ids=["common", "early_return"])
@pytest.mark.parametrize("output_size", [10, 10000], ids=["small_size", "large_size"])
@pytest.mark.isolated_distributed
def test_collect_results(early_return, output_size):
@dist.launcher
def worker():
if early_return:
exit(0)
return [dist.get_rank()] * output_size
results = worker()
world_size = len(results)
assert world_size > 0
expects = (
[None] * world_size
if early_return
else [[dev] * output_size for dev in range(world_size)]
)
assert results == expects
@pytest.mark.require_ngpu(2)
@pytest.mark.isolated_distributed
def test_user_set_pop():
@dist.launcher
def worker():
dist.get_client().user_set("foo", 1)
if dist.get_rank() == 1:
ret = dist.get_client().user_pop("foo")
assert ret == 1
worker()
@pytest.mark.require_ngpu(2)
@pytest.mark.isolated_distributed
def test_get_cuda_compute_capability():
assert mge.device.get_cuda_compute_capability(0) > 0
assert mge.device.get_cuda_compute_capability(1) > 0
@dist.launcher
def worker():
x = mge.tensor([1.0])
assert mge.device.get_cuda_compute_capability(dist.get_rank()) > 0
worker()