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How to use einlabels method in hypothesis

Best Python code snippet using hypothesis

test_gufunc.py

Source:test_gufunc.py

...148    )149    assert expected_input_1 == smallest_shapes[1]150def gufunc_sig_to_einsum_sig(gufunc_sig):151    """E.g. (i,j),(j,k)->(i,k) becomes ...ij,...jk->...ik"""152    def einlabels(labels):153        assert "x" not in labels, "we reserve x for fixed-dimensions"154        return "..." + "".join(i if not i.isdigit() else "x" for i in labels)155    gufunc_sig = nps._hypothesis_parse_gufunc_signature(gufunc_sig)156    input_sig = ",".join(map(einlabels, gufunc_sig.input_shapes))157    return input_sig + "->" + einlabels(gufunc_sig.result_shape)158@pytest.mark.parametrize(159    ("gufunc_sig"),160    [161        param("()->()", id="unary sum"),162        param("(),()->()", id="binary sum"),163        param("(),(),()->()", id="trinary sum"),164        param("(i)->()", id="sum1d"),165        param("(i,j)->(j)", id="sum rows"),166        param("(i),(i)->()", id="inner1d"),167        param("(i),(i),(i)->()", id="trinary inner1d"),168        param("(m,n),(n,p)->(m,p)", id="matmat"),169        param("(n),(n,p)->(p)", id="vecmat"),170        param("(i,t),(j,t)->(i,j)", id="outer-inner"),171        param("(3),(3)->(3)", id="cross1d"),...

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