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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _load_version(cls, state, version):
 """ A function to load a previously saved SoundClassifier instance. """

        from ._audio_feature_extractor import _get_feature_extractor
        from .._mxnet import _mxnet_utils

        state['_feature_extractor'] = _get_feature_extractor(state['feature_extractor_name'])

        # Load the custom nerual network
        num_classes = state['num_classes']
        num_inputs = state['_feature_extractor'].output_length
        if 'custom_layer_sizes' in state:
            # These are deserialized as floats
            custom_layer_sizes = list(map(int, state['custom_layer_sizes']))
        else:
            # Default value, was not part of state for only Turi Create 5.4
            custom_layer_sizes = [100, 100]
        state['custom_layer_sizes'] = custom_layer_sizes
        net = SoundClassifier._build_custom_neural_network(num_inputs, num_classes, custom_layer_sizes)
        net_params = net.collect_params()
        ctx = _mxnet_utils.get_mxnet_context()
        _mxnet_utils.load_net_params_from_state(net_params, state['_custom_classifier'], ctx=ctx)
        state['_custom_classifier'] = net

        return SoundClassifier(state)