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Suppress hypothesis health check for dask client. (#6589)

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Jiaming Yuan 2021-01-11 14:11:57 +08:00 committed by GitHub
parent 80065d571e
commit 78f2cd83d7
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 27 additions and 15 deletions
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26
tests/python-gpu/test_gpu_with_dask.py
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@ -6,7 +6,7 @@ import numpy as np
import asyncio
import xgboost
import subprocess
from hypothesis import given, strategies, settings, note
from hypothesis import given, strategies, settings, note, HealthCheck
from hypothesis._settings import duration
from test_gpu_updaters import parameter_strategy
@ -18,6 +18,7 @@ from test_with_dask import run_empty_dmatrix_reg # noqa
from test_with_dask import run_empty_dmatrix_cls # noqa
from test_with_dask import _get_client_workers # noqa
from test_with_dask import generate_array # noqa
from test_with_dask import suppress
import testing as tm # noqa
@ -171,25 +172,30 @@ class TestDistributedGPU:
run_with_dask_dataframe(dxgb.DaskDMatrix, client)
run_with_dask_dataframe(dxgb.DaskDeviceQuantileDMatrix, client)
@given(params=parameter_strategy, num_rounds=strategies.integers(1, 20),
dataset=tm.dataset_strategy)
@settings(deadline=duration(seconds=120))
@given(
params=parameter_strategy,
num_rounds=strategies.integers(1, 20),
dataset=tm.dataset_strategy,
)
@settings(deadline=duration(seconds=120), suppress_health_check=suppress)
@pytest.mark.skipif(**tm.no_dask())
@pytest.mark.skipif(**tm.no_dask_cuda())
@pytest.mark.parametrize('local_cuda_cluster', [{'n_workers': 2}], indirect=['local_cuda_cluster'])
@pytest.mark.parametrize(
"local_cuda_cluster", [{"n_workers": 2}], indirect=["local_cuda_cluster"]
)
@pytest.mark.mgpu
def test_gpu_hist(
self,
params: Dict,
num_rounds: int,
dataset: tm.TestDataset,
local_cuda_cluster: LocalCUDACluster
local_cuda_cluster: LocalCUDACluster,
) -> None:
with Client(local_cuda_cluster) as client:
run_gpu_hist(params, num_rounds, dataset, dxgb.DaskDMatrix,
client)
run_gpu_hist(params, num_rounds, dataset,
dxgb.DaskDeviceQuantileDMatrix, client)
run_gpu_hist(params, num_rounds, dataset, dxgb.DaskDMatrix, client)
run_gpu_hist(
params, num_rounds, dataset, dxgb.DaskDeviceQuantileDMatrix, client
)
@pytest.mark.skipif(**tm.no_cupy())
@pytest.mark.skipif(**tm.no_dask())

16
tests/python/test_with_dask.py
View File

@ -14,7 +14,8 @@ from sklearn.datasets import make_classification
import sklearn
import os
import subprocess
from hypothesis import given, settings, note
import hypothesis
from hypothesis import given, settings, note, HealthCheck
from test_updaters import hist_parameter_strategy, exact_parameter_strategy
from test_with_sklearn import run_feature_weights
@ -23,14 +24,19 @@ if sys.platform.startswith("win"):
if tm.no_dask()['condition']:
pytest.skip(msg=tm.no_dask()['reason'], allow_module_level=True)
from distributed import LocalCluster, Client, get_client
from distributed import LocalCluster, Client
from distributed.utils_test import client, loop, cluster_fixture
import dask.dataframe as dd
import dask.array as da
from xgboost.dask import DaskDMatrix
if hasattr(HealthCheck, 'function_scoped_fixture'):
suppress = [HealthCheck.function_scoped_fixture]
else:
suppress = hypothesis.utils.conventions.not_set
kRows = 1000
kCols = 10
kWorkers = 5
@ -803,7 +809,7 @@ class TestWithDask:
@given(params=hist_parameter_strategy,
dataset=tm.dataset_strategy)
@settings(deadline=None)
@settings(deadline=None, suppress_health_check=suppress)
def test_hist(
self, params: Dict, dataset: tm.TestDataset, client: "Client"
) -> None:
@ -812,7 +818,7 @@ class TestWithDask:
@given(params=exact_parameter_strategy,
dataset=tm.dataset_strategy)
@settings(deadline=None)
@settings(deadline=None, suppress_health_check=suppress)
def test_approx(
self, client: "Client", params: Dict, dataset: tm.TestDataset
) -> None: