self = <Client: scheduler='ucx://172.17.0.3:13339'>
async def _handle_report(self):
"""Listen to scheduler"""
with log_errors():
try:
while True:
if self.scheduler_comm is None:
break
try:
> msgs = await self.scheduler_comm.comm.read()
distributed/client.py:1222:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <UCX Client->Scheduler local=None remote=ucx://172.17.0.3:13339>
deserializers = ('cuda', 'dask', 'pickle', 'error')
async def read(self, deserializers=("cuda", "dask", "pickle", "error")):
with log_errors():
if self.closed():
raise CommClosedError("Endpoint is closed -- unable to read message")
if deserializers is None:
deserializers = ("cuda", "dask", "pickle", "error")
try:
# Recv meta data
# Recv close flag and number of frames (_Bool, int64)
msg = host_array(struct.calcsize("?Q"))
await self.ep.recv(msg)
(shutdown, nframes) = struct.unpack("?Q", msg)
if shutdown: # The writer is closing the connection
> raise CommClosedError("Connection closed by writer")
E distributed.comm.core.CommClosedError: Connection closed by writer
distributed/comm/ucx.py:255: CommClosedError
During handling of the above exception, another exception occurred:
cleanup = None
loop = <tornado.platform.asyncio.AsyncIOLoop object at 0x7f872c175550>
monkeypatch = <_pytest.monkeypatch.MonkeyPatch object at 0x7f87b936b2e0>
def test_ucx_config_w_env_var(cleanup, loop, monkeypatch):
size = "1000.00 MB"
monkeypatch.setenv("DASK_RMM__POOL_SIZE", size)
dask.config.refresh()
port = "13339"
sched_addr = f"ucx://{HOST}:{port}"
with popen(
["dask-scheduler", "--no-dashboard", "--protocol", "ucx", "--port", port]
) as sched:
with popen(
[
"dask-worker",
sched_addr,
"--no-dashboard",
"--protocol",
"ucx",
"--no-nanny",
]
) as w:
with Client(sched_addr, loop=loop, timeout=10) as c:
while not c.scheduler_info()["workers"]:
sleep(0.1)
# Check for RMM pool resource type
rmm_resource = c.run_on_scheduler(
rmm.mr.get_current_device_resource_type
)
assert rmm_resource == rmm.mr.PoolMemoryResource
worker_addr = list(c.scheduler_info()["workers"])[0]
worker_rmm_usage = c.run(rmm.mr.get_current_device_resource_type)
rmm_resource = worker_rmm_usage[worker_addr]
> assert rmm_resource == rmm.mr.PoolMemoryResource
distributed/comm/tests/test_ucx_config.py:118:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
distributed/client.py:1187: in __exit__
self.close()
distributed/client.py:1430: in close
sync(self.loop, self._close, fast=True, callback_timeout=timeout)
distributed/utils.py:325: in sync
raise exc.with_traceback(tb)
distributed/utils.py:308: in f
result[0] = yield future
/opt/conda/envs/dask/lib/python3.8/site-packages/tornado/gen.py:762: in run
value = future.result()
/opt/conda/envs/dask/lib/python3.8/asyncio/tasks.py:494: in wait_for
return fut.result()
distributed/client.py:1339: in _close
await asyncio.wait_for(
/opt/conda/envs/dask/lib/python3.8/asyncio/tasks.py:494: in wait_for
return fut.result()
distributed/client.py:1228: in _handle_report
await self._reconnect()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Client: scheduler='ucx://172.17.0.3:13339'>
async def _reconnect(self):
with log_errors():
> assert self.scheduler_comm.comm.closed()
E AssertionError
distributed/client.py:1053: AssertionError
I noticed the UCX test
distributed.comm.tests.test_ucx_config.test_ucx_config_w_env_varto occasionally failE.g. https://gpuci.gpuopenanalytics.com/job/dask/job/distributed/job/prb/job/distributed-prb/234/CUDA_VER=11.2,LINUX_VER=ubuntu18.04,PYTHON_VER=3.8,RAPIDS_VER=21.10/testReport/junit/distributed.comm.tests/test_ucx_config/test_ucx_config_w_env_var/
Traceback
cc @dask/gpu