trinet_embed.py 文件源码

def build_simple_block(incoming_layer, names,
                       num_filters, filter_size, stride, pad,
                       use_bias=False, nonlin=rectify):
    """Creates stacked Lasagne layers ConvLayer -> BN -> (ReLu)

    Parameters:
    ----------
    incoming_layer : instance of Lasagne layer
        Parent layer

    names : list of string
        Names of the layers in block

    num_filters : int
        Number of filters in convolution layer

    filter_size : int
        Size of filters in convolution layer

    stride : int
        Stride of convolution layer

    pad : int
        Padding of convolution layer

    use_bias : bool
        Whether to use bias in conlovution layer

    nonlin : function
        Nonlinearity type of Nonlinearity layer

    Returns
    -------
    tuple: (net, last_layer_name)
        net : dict
            Dictionary with stacked layers
        last_layer_name : string
            Last layer name
    """
    net = []
    net.append((
            names[0],
            ConvLayer(incoming_layer, num_filters, filter_size, stride, pad,
                      flip_filters=False, nonlinearity=None) if use_bias
            else ConvLayer(incoming_layer, num_filters, filter_size, stride, pad, b=None,
                           flip_filters=False, nonlinearity=None)
        ))

    net.append((
            names[1],
            BatchNormLayer(net[-1][1])
        ))
    if nonlin is not None:
        net.append((
            names[2],
            NonlinearityLayer(net[-1][1], nonlinearity=nonlin)
        ))

    return dict(net), net[-1][0]