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[dask] Honor nthreads from dask worker. (#5414)

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This commit is contained in:
Jiaming Yuan
2020-03-16 04:51:24 +08:00
committed by GitHub
parent 21b671aa06
commit 761a5dbdfc
5 changed files with 59 additions and 16 deletions
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3
demo/dask/cpu_training.py
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@@ -22,7 +22,6 @@ def main(client):
# evaluation metrics.
output = xgb.dask.train(client,
{'verbosity': 1,
'nthread': 1,
'tree_method': 'hist'},
dtrain,
num_boost_round=4, evals=[(dtrain, 'train')])
@@ -37,6 +36,6 @@ def main(client):
if __name__ == '__main__':
# or use other clusters for scaling
with LocalCluster(n_workers=7, threads_per_worker=1) as cluster:
with LocalCluster(n_workers=7, threads_per_worker=4) as cluster:
with Client(cluster) as client:
main(client)

3
demo/dask/gpu_training.py
View File

@@ -22,7 +22,6 @@ def main(client):
# evaluation metrics.
output = xgb.dask.train(client,
{'verbosity': 2,
'nthread': 1,
# Golden line for GPU training
'tree_method': 'gpu_hist'},
dtrain,
@@ -41,6 +40,6 @@ if __name__ == '__main__':
# `LocalCUDACluster` is used for assigning GPU to XGBoost processes. Here
# `n_workers` represents the number of GPUs since we use one GPU per worker
# process.
with LocalCUDACluster(n_workers=2, threads_per_worker=1) as cluster:
with LocalCUDACluster(n_workers=2, threads_per_worker=4) as cluster:
with Client(cluster) as client:
main(client)