Configuration factory for various networks

    Parameters
    ----------
    network : str
        base network name, such as vgg_reduced, inceptionv3, resnet...
    data_shape : int
        input data dimension
    kwargs : dict
        extra arguments

def get_config(network, data_shape, **kwargs):
    """Configuration factory for various networks

    Parameters
    ----------
    network : str
        base network name, such as vgg_reduced, inceptionv3, resnet...
    data_shape : int
        input data dimension
    kwargs : dict
        extra arguments
    """
    if network == 'vgg16_reduced':
        if data_shape >= 448:
            from_layers = ['relu4_3', 'relu7', '', '', '', '', '']
            num_filters = [512, -1, 512, 256, 256, 256, 256]
            strides = [-1, -1, 2, 2, 2, 2, 1]
            pads = [-1, -1, 1, 1, 1, 1, 1]
            sizes = [[.07, .1025], [.15,.2121], [.3, .3674], [.45, .5196], [.6, .6708], \
                [.75, .8216], [.9, .9721]]
            ratios = [[1,2,.5], [1,2,.5,3,1./3], [1,2,.5,3,1./3], [1,2,.5,3,1./3], \
                [1,2,.5,3,1./3], [1,2,.5], [1,2,.5]]
            normalizations = [20, -1, -1, -1, -1, -1, -1]
            steps = [] if data_shape != 512 else [x / 512.0 for x in
                [8, 16, 32, 64, 128, 256, 512]]
        else:
            from_layers = ['relu4_3', 'relu7', '', '', '', '']
            num_filters = [512, -1, 512, 256, 256, 256]
            strides = [-1, -1, 2, 2, 1, 1]
            pads = [-1, -1, 1, 1, 0, 0]
            sizes = [[.1, .141], [.2,.272], [.37, .447], [.54, .619], [.71, .79], [.88, .961]]
            ratios = [[1,2,.5], [1,2,.5,3,1./3], [1,2,.5,3,1./3], [1,2,.5,3,1./3], \
                [1,2,.5], [1,2,.5]]
            normalizations = [20, -1, -1, -1, -1, -1]
            steps = [] if data_shape != 300 else [x / 300.0 for x in [8, 16, 32, 64, 100, 300]]
        if not (data_shape == 300 or data_shape == 512):
            logging.warn('data_shape %d was not tested, use with caucious.' % data_shape)
        return locals()
    elif network == 'inceptionv3':
        from_layers = ['ch_concat_mixed_7_chconcat', 'ch_concat_mixed_10_chconcat', '', '', '', '']
        num_filters = [-1, -1, 512, 256, 256, 128]
        strides = [-1, -1, 2, 2, 2, 2]
        pads = [-1, -1, 1, 1, 1, 1]
        sizes = [[.1, .141], [.2,.272], [.37, .447], [.54, .619], [.71, .79], [.88, .961]]
        ratios = [[1,2,.5], [1,2,.5,3,1./3], [1,2,.5,3,1./3], [1,2,.5,3,1./3], \
            [1,2,.5], [1,2,.5]]
        normalizations = -1
        steps = []
        return locals()
    elif network == 'resnet50':
        num_layers = 50
        image_shape = '3,224,224'  # resnet require it as shape check
        network = 'resnet'
        from_layers = ['_plus12', '_plus15', '', '', '', '']
        num_filters = [-1, -1, 512, 256, 256, 128]
        strides = [-1, -1, 2, 2, 2, 2]
        pads = [-1, -1, 1, 1, 1, 1]
        sizes = [[.1, .141], [.2,.272], [.37, .447], [.54, .619], [.71, .79], [.88, .961]]
        ratios = [[1,2,.5], [1,2,.5,3,1./3], [1,2,.5,3,1./3], [1,2,.5,3,1./3], \
            [1,2,.5], [1,2,.5]]
        normalizations = -1
        steps = []
        return locals()
    elif network == 'resnet101':
        num_layers = 101
        image_shape = '3,224,224'
        network = 'resnet'
        from_layers = ['_plus29', '_plus32', '', '', '', '']
        num_filters = [-1, -1, 512, 256, 256, 128]
        strides = [-1, -1, 2, 2, 2, 2]
        pads = [-1, -1, 1, 1, 1, 1]
        sizes = [[.1, .141], [.2,.272], [.37, .447], [.54, .619], [.71, .79], [.88, .961]]
        ratios = [[1,2,.5], [1,2,.5,3,1./3], [1,2,.5,3,1./3], [1,2,.5,3,1./3], \
            [1,2,.5], [1,2,.5]]
        normalizations = -1
        steps = []
        return locals()
    else:
        msg = 'No configuration found for %s with data_shape %d' % (network, data_shape)
        raise NotImplementedError(msg)