def __init__(self, net, print_architecture=True):
"""
Constructor
"""
self.net = net
self.compute_output = None
self.compute_output_dict = dict()
self.saliency_function = None
self.iter_funcs = None
# get input shape of network
l_in = lasagne.layers.helper.get_all_layers(self.net)[0]
self.input_shape = l_in.output_shape
if print_architecture:
print_net_architecture(net, detailed=True)
W=init_conv(gain="relu"),
nonlinearity=nonlin)
net = batch_norm(net, alpha=0.1)
net = DropoutLayer(net, p=0.5)
net = Conv2DLayer(net,
num_filters=8 * nf,
filter_size=1,
pad=0,
W=init_conv(gain="relu"),
nonlinearity=nonlin)
net = batch_norm(net, alpha=0.1)
net = DropoutLayer(net, p=0.5)
# --- feed forward part ---
net = Conv2DLayer(net,
num_filters=41,
filter_size=1,
W=init_conv(gain="relu"),
nonlinearity=None)
net = batch_norm(net, alpha=0.1)
net = GlobalPoolLayer(net)
net = FlattenLayer(net)
net = NonlinearityLayer(net, nonlinearity=lasagne.nonlinearities.softmax)
return net
if __name__ == "__main__":
from dcase_task2.lasagne_wrapper.utils import print_net_architecture
print_net_architecture(build_model(None), detailed=True)