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