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Fix empty DMatrix with categorical features. (#8739)

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This commit is contained in:
Jiaming Yuan
2023-02-07 00:40:11 +08:00
committed by GitHub
parent 7214a45e83
commit a2e433a089
5 changed files with 93 additions and 11 deletions
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21
tests/test_distributed/test_gpu_with_dask/test_gpu_with_dask.py
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@@ -265,6 +265,27 @@ class TestDistributedGPU:
) -> None:
run_gpu_hist(params, num_rounds, dataset, dmatrix_type, local_cuda_client)
def test_empty_quantile_dmatrix(self, local_cuda_client: Client) -> None:
client = local_cuda_client
X, y = make_categorical(client, 1, 30, 13)
X_valid, y_valid = make_categorical(client, 10000, 30, 13)
Xy = xgb.dask.DaskQuantileDMatrix(client, X, y, enable_categorical=True)
Xy_valid = xgb.dask.DaskQuantileDMatrix(
client, X_valid, y_valid, ref=Xy, enable_categorical=True
)
result = xgb.dask.train(
client,
{"tree_method": "gpu_hist"},
Xy,
num_boost_round=10,
evals=[(Xy_valid, "Valid")],
)
predt = xgb.dask.inplace_predict(client, result["booster"], X).compute()
np.testing.assert_allclose(y.compute(), predt)
rmse = result["history"]["Valid"]["rmse"][-1]
assert rmse < 32.0
@pytest.mark.skipif(**tm.no_cupy())
def test_dask_array(self, local_cuda_client: Client) -> None:
run_with_dask_array(dxgb.DaskDMatrix, local_cuda_client)