Avoid warning in np primitive type tests. (#7833)
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@ -569,7 +569,7 @@ class TestModels:
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y = rng.randn(rows)
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y = rng.randn(rows)
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feature_names = ["test_feature_" + str(i) for i in range(cols)]
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feature_names = ["test_feature_" + str(i) for i in range(cols)]
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X_pd = pd.DataFrame(X, columns=feature_names)
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X_pd = pd.DataFrame(X, columns=feature_names)
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X_pd.iloc[:, 3] = X_pd.iloc[:, 3].astype(np.int)
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X_pd.iloc[:, 3] = X_pd.iloc[:, 3].astype(np.int32)
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Xy = xgb.DMatrix(X_pd, y)
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Xy = xgb.DMatrix(X_pd, y)
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assert Xy.feature_types[3] == "int"
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assert Xy.feature_types[3] == "int"
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@ -245,19 +245,23 @@ class TestInplacePredict:
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predt_orig = self.booster.inplace_predict(orig)
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predt_orig = self.booster.inplace_predict(orig)
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# all primitive types in numpy
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# all primitive types in numpy
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for dtype in [
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for dtype in [
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np.signedinteger,
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np.int32,
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np.int64,
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np.byte,
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np.byte,
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np.short,
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np.short,
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np.intc,
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np.intc,
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np.int_,
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np.int_,
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np.longlong,
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np.longlong,
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np.unsignedinteger,
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np.uint32,
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np.uint64,
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np.ubyte,
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np.ubyte,
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np.ushort,
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np.ushort,
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np.uintc,
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np.uintc,
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np.uint,
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np.uint,
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np.ulonglong,
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np.ulonglong,
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np.floating,
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np.float16,
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np.float32,
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np.float64,
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np.half,
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np.half,
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np.single,
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np.single,
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np.double,
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np.double,
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@ -328,5 +328,5 @@ class TestPandas:
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return to_bytes(Xy)
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return to_bytes(Xy)
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b0 = test_bool(pd.BooleanDtype())
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b0 = test_bool(pd.BooleanDtype())
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b1 = test_bool(np.bool)
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b1 = test_bool(bool)
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assert b0 != b1 # None is converted to False with np.bool
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assert b0 != b1 # None is converted to False with np.bool
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