Function process_failures

test/test_proxy_tensor.py:49–80

Takes file containing failures like FAILED test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive___getitem___cpu_float32 - RuntimeError: aten.size.default - couldn't find symbolic meta function/decomposition # noqa: B950 and processes them into a list

()

def process_failures():
    """
    Takes file containing failures like

    FAILED test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive___getitem___cpu_float32 - RuntimeError: aten.size.default - couldn't find symbolic meta function/decomposition  # noqa: B950

    and processes them into a list of opinfo xfails
    """
    f = open('pytest_failures')
    failures = f.readlines()
    failures = [i.strip() for i in failures]

    def process_failure_string(s, matcher):
        out = re.search(matcher, s)
        return out.groups()

    SYMBOLIC_TRACE_MATCH = r'exhaustive_(.*)_cpu.*: (.*)'
    failures = [process_failure_string(s, SYMBOLIC_TRACE_MATCH) for s in failures]

    def create_normalized_name(op):
        if op.variant_test_name == '':
            s = op.name
        else:
            s = f"{op.name}.{op.variant_test_name}"
        return s.replace('.', '_')

    remap_opinfo = {create_normalized_name(op): (op.name, op.variant_test_name) for op in op_db}

    print("symbolic_tensor_failures = {")
    for failure, reason in failures:
        print(f"    xfail{remap_opinfo[failure]},  # {reason}")
    print("}")


USE_TORCHVISION = False