def _conv1d_act() -> _List[_BackendPatternConfig]:
    """
    float: Conv1d -> Act
    qat: FakeQuant -> qat.ConvAct1d -> FakeQuant
    """
    configs = _weighted_relu_configs(
        mod=_nn.Conv1d,
        func_mod=_F.conv1d,
        fused_mod=_nni.ConvReLU1d,
        qat_mod=_nniq.ConvReLU1d,
        ref_quant_mod=_nnr.Conv1d,
    )
    for act in _mod_activations:
        configs.extend(
            _weighted_act_configs(
                mod=_nn.Conv1d,
                func_mod=_F.conv1d,
                act=act,
                fused_mod=_fused.ConvAct1d,
                qat_mod=_qat.ConvAct1d,
                ref_quant_mod=_quantized.QuantizedConvAct1d,
            )
        )
    return configs

    float: Conv1d -> Act
    qat: FakeQuant -> qat.ConvAct1d -> FakeQuant
    
coremltools/optimize/torch/quantization/_backend_config.py