7e72a12871
* Don't set_params at the end of set_state. * Also fix another issue found in dask prediction. * Add note about prediction. Don't support other prediction modes at the moment.
46 lines
1.2 KiB
Python
46 lines
1.2 KiB
Python
import sys
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import pytest
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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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try:
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from distributed.utils_test import client, loop, cluster_fixture
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import dask.dataframe as dd
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from xgboost import dask as dxgb
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import cudf
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except ImportError:
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client = None
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loop = None
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cluster_fixture = None
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pass
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sys.path.append("tests/python")
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from test_with_dask import generate_array
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import testing as tm
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@pytest.mark.skipif(**tm.no_dask())
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@pytest.mark.skipif(**tm.no_cudf())
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@pytest.mark.skipif(**tm.no_dask_cudf())
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def test_dask_dataframe(client):
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X, y = generate_array()
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X = dd.from_dask_array(X)
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y = dd.from_dask_array(y)
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X = X.map_partitions(cudf.from_pandas)
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y = y.map_partitions(cudf.from_pandas)
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dtrain = dxgb.DaskDMatrix(client, X, y)
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out = dxgb.train(client, {'tree_method': 'gpu_hist'},
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dtrain=dtrain,
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evals=[(dtrain, 'X')],
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num_boost_round=2)
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assert isinstance(out['booster'], dxgb.Booster)
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assert len(out['history']['X']['rmse']) == 2
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predictions = dxgb.predict(out, dtrain)
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predictions = predictions.compute()
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