Remove as_gpu_matrix from tests and fix some uncovered bugs.

python/cudf/cudf/core/column/column.py

@@ -130,6 +130,12 @@ def values_host(self) -> "np.ndarray":
         """
         Return a numpy representation of the Column.
         """
+        if len(self) == 0:
+            return np.array([], dtype=self.dtype)
+
+        if self.has_nulls:
+            raise ValueError("Column must have no nulls.")
+
         return self.data_array_view.copy_to_host()
 
     @property
@@ -138,7 +144,7 @@ def values(self) -> "cupy.ndarray":
         Return a CuPy representation of the Column.
         """
         if len(self) == 0:
-            return cupy.asarray([], dtype=self.dtype)
+            return cupy.array([], dtype=self.dtype)
 
         if self.has_nulls:
             raise ValueError("Column must have no nulls.")

python/cudf/cudf/tests/test_dataframe.py

@@ -941,12 +941,13 @@ def test_dataframe_dir_and_getattr():
         df.not_a_column
 
 
-@pytest.mark.parametrize("order", ["C", "F"])
-def test_empty_dataframe_as_gpu_matrix(order):
+def test_empty_dataframe_to_array():
     df = cudf.DataFrame()
 
     # Check fully empty dataframe.
-    mat = df.as_gpu_matrix(order=order).copy_to_host()
+    mat = df.to_cupy()
+    assert mat.shape == (0, 0)
+    mat = df.to_numpy()
     assert mat.shape == (0, 0)
 
     df = cudf.DataFrame()
@@ -955,33 +956,32 @@ def test_empty_dataframe_as_gpu_matrix(order):
         df[k] = np.random.random(nelem)
 
     # Check all columns in empty dataframe.
-    mat = df.head(0).as_gpu_matrix(order=order).copy_to_host()
+    mat = df.head(0).to_cupy()
     assert mat.shape == (0, 3)
 
 
-@pytest.mark.parametrize("order", ["C", "F"])
-def test_dataframe_as_gpu_matrix(order):
+def test_dataframe_to_cupy():
     df = cudf.DataFrame()
 
     nelem = 123
     for k in "abcd":
         df[k] = np.random.random(nelem)
 
     # Check all columns
-    mat = df.as_gpu_matrix(order=order).copy_to_host()
+    mat = df.to_numpy()
     assert mat.shape == (nelem, 4)
     for i, k in enumerate(df.columns):
         np.testing.assert_array_equal(df[k].to_array(), mat[:, i])
 
     # Check column subset
-    mat = df.as_gpu_matrix(order=order, columns=["a", "c"]).copy_to_host()
+    mat = df[["a", "c"]].to_cupy().get()
     assert mat.shape == (nelem, 2)
 
     for i, k in enumerate("ac"):
         np.testing.assert_array_equal(df[k].to_array(), mat[:, i])
 
 
-def test_dataframe_as_gpu_matrix_null_values():
+def test_dataframe_to_cupy_null_values():
     df = cudf.DataFrame()
 
     nelem = 123
@@ -999,14 +999,15 @@ def test_dataframe_as_gpu_matrix_null_values():
         refvalues[k] = data
 
     # Check null value causes error
-    with pytest.raises(ValueError) as raises:
-        df.as_gpu_matrix()
-    raises.match("column 'a' has null values")
+    with pytest.raises(ValueError):
+        df.to_cupy()
+    with pytest.raises(ValueError):
+        df.to_numpy()
 
     for k in df.columns:
         df[k] = df[k].fillna(na)
 
-    mat = df.as_gpu_matrix().copy_to_host()
+    mat = df.to_numpy()
     for i, k in enumerate(df.columns):
         np.testing.assert_array_equal(refvalues[k], mat[:, i])