def _get_net(n_inputs: int, n_units_1: int, n_units_2: int) -> Any:
""" Create a Network with theano """
l_in = lasagne.layers.InputLayer(shape=(None, n_inputs))
fc_layer_1 = lasagne.layers.DenseLayer(
l_in,
num_units=n_units_1,
W=lasagne.init.HeNormal(),
b=lasagne.init.Constant(val=0.0),
nonlinearity=lasagne.nonlinearities.tanh)
fc_layer_2 = lasagne.layers.DenseLayer(
fc_layer_1,
num_units=n_units_2,
W=lasagne.init.HeNormal(),
b=lasagne.init.Constant(val=0.0),
nonlinearity=lasagne.nonlinearities.tanh)
l_out = lasagne.layers.DenseLayer(
fc_layer_2,
num_units=1,
W=lasagne.init.HeNormal(),
b=lasagne.init.Constant(val=0.0),
nonlinearity=lasagne.nonlinearities.linear)
network = AppendLayer(l_out,
num_units=1,
b=lasagne.init.Constant(np.log(1e-3)))
return network
def get_default_net(n_inputs):
l_in = lasagne.layers.InputLayer(shape=(None, n_inputs))
fc_layer_1 = lasagne.layers.DenseLayer(
l_in,
num_units=50,
W=lasagne.init.HeNormal(),
b=lasagne.init.Constant(val=0.0),
nonlinearity=lasagne.nonlinearities.tanh)
fc_layer_2 = lasagne.layers.DenseLayer(
fc_layer_1,
num_units=50,
W=lasagne.init.HeNormal(),
b=lasagne.init.Constant(val=0.0),
nonlinearity=lasagne.nonlinearities.tanh)
fc_layer_3 = lasagne.layers.DenseLayer(
fc_layer_2,
num_units=50,
W=lasagne.init.HeNormal(),
b=lasagne.init.Constant(val=0.0),
nonlinearity=lasagne.nonlinearities.tanh)
l_out = lasagne.layers.DenseLayer(
fc_layer_3,
num_units=1,
W=lasagne.init.HeNormal(),
b=lasagne.init.Constant(val=0.0),
nonlinearity=lasagne.nonlinearities.linear)
network = AppendLayer(l_out,
num_units=1,
b=lasagne.init.Constant(np.log(1e-3)))
return network
def get_net():
l_in = InputLayer(shape=(None, 1))
l_hid1 = DenseLayer(l_in,
num_units=50,
W=lasagne.init.HeNormal(),
b=lasagne.init.Constant(0.),
nonlinearity=lasagne.nonlinearities.tanh)
l_hid2 = DenseLayer(l_hid1,
num_units=50,
W=lasagne.init.HeNormal(),
b=lasagne.init.Constant(0.),
nonlinearity=lasagne.nonlinearities.tanh)
l_out = DenseLayer(l_hid2,
num_units=1,
W=lasagne.init.HeNormal(),
b=lasagne.init.Constant(0.),
nonlinearity=None)
l_out = AppendLayer(l_out,
num_units=1,
b=lasagne.init.Constant(np.log(1e-3)))
return l_out