def METHOD_NAME():
    # tensor3 . tensor3
    a = tensor3("a")
    a.tag.test_value = (
        np.linspace(-1, 1, 10 * 5 * 3).astype(config.floatX).reshape((10, 5, 3))
    )
    b = tensor3("b")
    b.tag.test_value = (
        np.linspace(1, -1, 10 * 3 * 2).astype(config.floatX).reshape((10, 3, 2))
    )
    out = at_blas.BatchedDot()(a, b)
    fgraph = FunctionGraph([a, b], [out])
    compare_jax_and_py(fgraph, [get_test_value(i) for i in fgraph.inputs])
    # A dimension mismatch should raise a TypeError for compatibility
    inputs = [get_test_value(a)[:-1], get_test_value(b)]
    opts = RewriteDatabaseQuery(include=[None], exclude=["cxx_only", "BlasOpt"])
    jax_mode = Mode(JAXLinker(), opts)
    aesara_jax_fn = function(fgraph.inputs, fgraph.outputs, mode=jax_mode)
    with pytest.raises(TypeError):
        aesara_jax_fn(*inputs)
    # matrix . matrix
    a = matrix("a")
    a.tag.test_value = np.linspace(-1, 1, 5 * 3).astype(config.floatX).reshape((5, 3))
    b = matrix("b")
    b.tag.test_value = np.linspace(1, -1, 5 * 3).astype(config.floatX).reshape((5, 3))
    out = at_blas.BatchedDot()(a, b)
    fgraph = FunctionGraph([a, b], [out])
    compare_jax_and_py(fgraph, [get_test_value(i) for i in fgraph.inputs])