cfd2a9f872
- Move test files. - Run spark and dask separately to prevent conflicts. - Gather common code into the testing module.
99 lines
3.1 KiB
Python
99 lines
3.1 KiB
Python
import re
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import sys
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import numpy as np
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import pytest
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import xgboost as xgb
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from xgboost import RabitTracker
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from xgboost import testing as tm
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from xgboost import collective
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if sys.platform.startswith("win"):
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pytest.skip("Skipping dask tests on Windows", allow_module_level=True)
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def test_rabit_tracker():
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tracker = RabitTracker(host_ip="127.0.0.1", n_workers=1)
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tracker.start(1)
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with xgb.collective.CommunicatorContext(**tracker.worker_envs()):
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ret = xgb.collective.broadcast("test1234", 0)
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assert str(ret) == "test1234"
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def run_rabit_ops(client, n_workers):
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from xgboost.dask import CommunicatorContext, _get_dask_config, _get_rabit_args
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workers = tm.get_client_workers(client)
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rabit_args = client.sync(_get_rabit_args, len(workers), _get_dask_config(), client)
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assert not collective.is_distributed()
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n_workers_from_dask = len(workers)
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assert n_workers == n_workers_from_dask
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def local_test(worker_id):
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with CommunicatorContext(**rabit_args):
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a = 1
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assert collective.is_distributed()
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a = np.array([a])
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reduced = collective.allreduce(a, collective.Op.SUM)
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assert reduced[0] == n_workers
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worker_id = np.array([worker_id])
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reduced = collective.allreduce(worker_id, collective.Op.MAX)
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assert reduced == n_workers - 1
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return 1
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futures = client.map(local_test, range(len(workers)), workers=workers)
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results = client.gather(futures)
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assert sum(results) == n_workers
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@pytest.mark.skipif(**tm.no_dask())
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def test_rabit_ops():
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from distributed import Client, LocalCluster
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n_workers = 3
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with LocalCluster(n_workers=n_workers) as cluster:
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with Client(cluster) as client:
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run_rabit_ops(client, n_workers)
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@pytest.mark.skipif(**tm.no_ipv6())
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@pytest.mark.skipif(**tm.no_dask())
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def test_rabit_ops_ipv6():
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import dask
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from distributed import Client, LocalCluster
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n_workers = 3
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with dask.config.set({"xgboost.scheduler_address": "[::1]"}):
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with LocalCluster(n_workers=n_workers, host="[::1]") as cluster:
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with Client(cluster) as client:
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run_rabit_ops(client, n_workers)
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def test_rank_assignment() -> None:
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from distributed import Client, LocalCluster
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def local_test(worker_id):
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with xgb.dask.CommunicatorContext(**args) as ctx:
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task_id = ctx["DMLC_TASK_ID"]
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matched = re.search(".*-([0-9]).*", task_id)
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rank = xgb.collective.get_rank()
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# As long as the number of workers is lesser than 10, rank and worker id
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# should be the same
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assert rank == int(matched.group(1))
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with LocalCluster(n_workers=8) as cluster:
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with Client(cluster) as client:
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workers = tm.get_client_workers(client)
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args = client.sync(
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xgb.dask._get_rabit_args,
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len(workers),
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None,
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client,
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)
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futures = client.map(local_test, range(len(workers)), workers=workers)
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client.gather(futures)
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