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[doc] Update dask demo. (#9201)

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Jiaming Yuan 2023-05-31 05:01:02 +08:00 committed by GitHub
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demo/dask/gpu_training.py
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@ -38,19 +38,18 @@ def using_dask_matrix(client: Client, X, y):
def using_quantile_device_dmatrix(client: Client, X, y): def using_quantile_device_dmatrix(client: Client, X, y):
"""`DaskQuantileDMatrix` is a data type specialized for `gpu_hist`, tree """`DaskQuantileDMatrix` is a data type specialized for `gpu_hist` and `hist` tree
method that reduces memory overhead. When training on GPU pipeline, it's methods for reducing memory usage.
preferred over `DaskDMatrix`.
.. versionadded:: 1.2.0 .. versionadded:: 1.2.0
""" """
# Input must be on GPU for `DaskQuantileDMatrix`.
X = dask_cudf.from_dask_dataframe(dd.from_dask_array(X)) X = dask_cudf.from_dask_dataframe(dd.from_dask_array(X))
y = dask_cudf.from_dask_dataframe(dd.from_dask_array(y)) y = dask_cudf.from_dask_dataframe(dd.from_dask_array(y))
# `DaskQuantileDMatrix` is used instead of `DaskDMatrix`, be careful # `DaskQuantileDMatrix` is used instead of `DaskDMatrix`, be careful that it can not
# that it can not be used for anything else other than training. # be used for anything else other than training unless a reference is specified. See
# the `ref` argument of `DaskQuantileDMatrix`.
dtrain = dxgb.DaskQuantileDMatrix(client, X, y) dtrain = dxgb.DaskQuantileDMatrix(client, X, y)
output = xgb.dask.train( output = xgb.dask.train(
client, {"verbosity": 2, "tree_method": "gpu_hist"}, dtrain, num_boost_round=4 client, {"verbosity": 2, "tree_method": "gpu_hist"}, dtrain, num_boost_round=4