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Complete cudf support. (#4850)

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* Handles missing value.
* Accept all floating point and integer types.
* Move to cudf 9.0 API.
* Remove requirement on `null_count`.
* Arbitrary column types support.
This commit is contained in:
Jiaming Yuan
2019-09-16 23:52:00 -04:00
committed by GitHub
parent 125bcec62e
commit 5374f52531
17 changed files with 702 additions and 339 deletions
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11
tests/python/test_basic.py
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@@ -67,17 +67,17 @@ class TestBasic(unittest.TestCase):
def test_np_view(self):
# Sliced Float32 array
y = np.array([12, 34, 56], np.float32)[::2]
from_view = xgb.DMatrix([], label=y).get_label()
from_array = xgb.DMatrix([], label=y + 0).get_label()
from_view = xgb.DMatrix(np.array([[]]), label=y).get_label()
from_array = xgb.DMatrix(np.array([[]]), label=y + 0).get_label()
assert (from_view.shape == from_array.shape)
assert (from_view == from_array).all()
# Sliced UInt array
z = np.array([12, 34, 56], np.uint32)[::2]
dmat = xgb.DMatrix([])
dmat = xgb.DMatrix(np.array([[]]))
dmat.set_uint_info('root_index', z)
from_view = dmat.get_uint_info('root_index')
dmat = xgb.DMatrix([])
dmat = xgb.DMatrix(np.array([[]]))
dmat.set_uint_info('root_index', z + 0)
from_array = dmat.get_uint_info('root_index')
assert (from_view.shape == from_array.shape)
@@ -256,7 +256,7 @@ class TestBasic(unittest.TestCase):
assert dm.num_row() == 5
assert dm.num_col() == 5
data = np.matrix([[1, 2], [3, 4]])
data = np.array([[1, 2], [3, 4]])
dm = xgb.DMatrix(data)
assert dm.num_row() == 2
assert dm.num_col() == 2
@@ -430,4 +430,3 @@ class TestBasicPathLike(unittest.TestCase):
# invalid values raise Type error
self.assertRaises(TypeError, xgb.compat.os_fspath, 123)