def check_memory_layout(name, dtype):
    # Check that it works no matter the memory layout

    est = FOREST_ESTIMATORS[name](random_state=0, bootstrap=False)

    # Nothing
    X = np.asarray(iris.data, dtype=dtype)
    y = iris.target
    assert_array_equal(est.fit(X, y).predict(X), y)

    # C-order
    X = np.asarray(iris.data, order="C", dtype=dtype)
    y = iris.target
    assert_array_equal(est.fit(X, y).predict(X), y)

    # F-order
    X = np.asarray(iris.data, order="F", dtype=dtype)
    y = iris.target
    assert_array_equal(est.fit(X, y).predict(X), y)

    # Contiguous
    X = np.ascontiguousarray(iris.data, dtype=dtype)
    y = iris.target
    assert_array_equal(est.fit(X, y).predict(X), y)

    if est.base_estimator.splitter in SPARSE_SPLITTERS:
        # csr matrix
        X = csr_matrix(iris.data, dtype=dtype)
        y = iris.target
        assert_array_equal(est.fit(X, y).predict(X), y)

        # csc_matrix
        X = csc_matrix(iris.data, dtype=dtype)
        y = iris.target
        assert_array_equal(est.fit(X, y).predict(X), y)

        # coo_matrix
        X = coo_matrix(iris.data, dtype=dtype)
        y = iris.target
        assert_array_equal(est.fit(X, y).predict(X), y)

    # Strided
    X = np.asarray(iris.data[::3], dtype=dtype)
    y = iris.target[::3]
    assert_array_equal(est.fit(X, y).predict(X), y)
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/ensemble/tests/test_forest.py/check_memory_layout/original