def googlenet(pretrained=True, progress=True, **kwargs):
    r"""GoogLeNet (Inception v1) model architecture from
    `"Going Deeper with Convolutions" <http://arxiv.org/abs/1409.4842>`_.

    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
        progress (bool): If True, displays a progress bar of the download to stderr
        aux_logits (bool): If True, adds two auxiliary branches that can improve training.
            Default: *False* when pretrained is True otherwise *True*
        transform_input (bool): If True, preprocesses the input according to the method with which it
            was trained on ImageNet. Default: *False*
    """
    if pretrained:
        if "transform_input" not in kwargs:
            kwargs["transform_input"] = True
        if "aux_logits" not in kwargs:
            kwargs["aux_logits"] = False
        if kwargs["aux_logits"]:
            warnings.warn(
                "auxiliary heads in the pretrained googlenet model are NOT pretrained, "
                "so make sure to train them"
            )
        original_aux_logits = kwargs["aux_logits"]
        kwargs["aux_logits"] = True
        kwargs["init_weights"] = False
        model = GoogLeNet(**kwargs)
        state_dict = load_state_dict_from_url(
            model_urls["googlenet"], progress=progress
        )
        model.load_state_dict(state_dict)
        if not original_aux_logits:
            model.aux_logits = False
            del model.aux1, model.aux2

        model.fc = nn.Linear(1024, 7)
        return model

    return GoogLeNet(**kwargs)
GoogLeNet (Inception v1) model architecture from
    `"Going Deeper with Convolutions" <http://arxiv.org/abs/1409.4842>`_.

    Args:
        pretrained (bool): If True, returns a model pre-trained on ImageNet
        progress (bool): If True, displays a progress bar of the download to stderr
        aux_logits (bool): If True, adds two auxiliary branches that can improve training.
            Default: *False* when pretrained is True otherwise *True*
        transform_input (bool): If True, preprocesses the input according to the method with which it
            was trained on ImageNet. Default: *False*
    
rmn/models/googlenet.py