(pretrained=False, progress=True, **kwargs)
return model
Constructs a MobileNetV2 architecture from
    `"MobileNetV2: Inverted Residuals and Linear Bottlenecks" <https://arxiv.org/abs/1801.04381>`_.

    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
Constructs a MobileNetV2 architecture from
    `"MobileNetV2: Inverted Residuals and Linear Bottlenecks" <https://arxiv.org/abs/1801.04381>`_.
Constructs a MobileNetV2 architecture from MobileNetV2 : Inverted Residuals and Linear Bottlenecks <https : // arxiv . org / abs / 1801 . 04381 > _ .
def mobilenet_v2(pretrained=False, progress=True, **kwargs):
    """
    Constructs a MobileNetV2 architecture from
    `"MobileNetV2: Inverted Residuals and Linear Bottlenecks" <https://arxiv.org/abs/1801.04381>`_.

    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
    """
    model = MobileNetV2(**kwargs)
    if pretrained:
        state_dict = load_state_dict_from_url(model_urls['mobilenet_v2'],
                                              progress=progress)
        model.load_state_dict(state_dict)
    return model
def mobilenet_v2 ( pretrained = False , progress = True , * * kwargs ) : model = MobileNetV2 ( * * kwargs ) if pretrained : state_dict = load_state_dict_from_url ( model_urls [ 'mobilenet_v2' ] , progress = progress ) model . load_state_dict ( state_dict ) return model