padded.py 文件源码

def get_equivalent_input_padding(layer, layers_args=[]):
    """Compute the equivalent padding in the input layer

    A function to compute the equivalent padding of a sequence of
    convolutional and pooling layers. It memorizes the padding
    of all the Layers up to the first InputLayer.
    It then computes what would be the equivalent padding in the Layer
    immediately before the chain of Layers that is being taken into account.
    """
    # Initialize the DynamicPadding layers
    lasagne.layers.get_output(layer)
    # Loop through conv and pool to collect data
    all_layers = get_all_layers(layer)
    # while(not isinstance(layer, (InputLayer))):
    for layer in all_layers:
        # Note: stride is numerical, but pad *could* be symbolic
        try:
            pad, stride = (layer.pad, layer.stride)
            if isinstance(pad, int):
                pad = pad, pad
            if isinstance(stride, int):
                stride = stride, stride
            layers_args.append((pad, stride))
        except(AttributeError):
            pass

    # Loop backward to compute the equivalent padding in the input
    # layer
    tot_pad = T.zeros(2)
    pad_factor = T.ones(2)
    while(layers_args):
        pad, stride = layers_args.pop()
        tot_pad += pad * pad_factor
        pad_factor *= stride

    return tot_pad