I think you'll want to ask this question on the Lasagne forum https://groups.google.com/forum/#!forum/lasagne-users I don't think it is a problem with how you are using Theano.
On Saturday, April 29, 2017 at 10:46:46 AM UTC-7, Madhavun Candadai wrote: > > Hello, > > I am trying to set up a recurrent neural network with multiple layers as > follows - > > inputs = T.tensor3(name='inputs') > targets = T.dvector(name='targets') > > # Input layer > l_in = lasagne.layers.InputLayer(([1,1,NUM_SENSORS]),inputs) > > # recurrent layer > initRec1Weights = > lasagne.utils.create_param(np.eye(NUM_HIDDEN_UNITS)*4.+np.random.rand(NUM_HIDDEN_UN$ > > [NUM_HIDDEN_UNITS,NUM_HIDDEN_UNITS]) > initRec2Weights = > lasagne.utils.create_param(np.eye(NUM_HIDDEN_UNITS)*4.+np.random.rand(NUM_HIDDEN_UN$ > > [NUM_HIDDEN_UNITS,NUM_HIDDEN_UNITS]) > initRec3Weights = > lasagne.utils.create_param(np.eye(NUM_HIDDEN_UNITS)*4.+np.random.rand(NUM_HIDDEN_UN$ > > [NUM_HIDDEN_UNITS,NUM_HIDDEN_UNITS]) > > l_r1 = lasagne.layers.RecurrentLayer(l_in, NUM_HIDDEN_UNITS, > W_in_to_hid=lasagne.init.Uniform(range=2,std=None,mean=0.), > W_hid_to_hid=initRec1Weights,#lasagne.init.Constant(4.), > b=lasagne.init.Constant(0.), > nonlinearity=lasagne.nonlinearities.sigmoid, > gradient_steps=20) # number of steps for BPTT to unroll network > > l_r2 = lasagne.layers.RecurrentLayer(l_r1, NUM_HIDDEN_UNITS, > W_in_to_hid=lasagne.init.Uniform(range=2,std=None,mean=0.), > W_hid_to_hid=initRec2Weights,#lasagne.init.Constant(4.), > b=lasagne.init.Constant(0.), > nonlinearity=lasagne.nonlinearities.sigmoid, > gradient_steps=BPTT_STEPS) # number of steps for BPTT to unroll network > > l_r3 = lasagne.layers.RecurrentLayer(l_r2, NUM_HIDDEN_UNITS, > W_in_to_hid=lasagne.init.Uniform(range=2,std=None,mean=0.), > W_hid_to_hid=initRec3Weights,#lasagne.init.Constant(4.), > b=lasagne.init.Constant(0.), > nonlinearity=lasagne.nonlinearities.sigmoid, > gradient_steps=BPTT_STEPS) # number of steps for BPTT to unroll network > > # output layer > l_out = lasagne.layers.DenseLayer(l_r3, NUM_OUTPUTS, > W=lasagne.init.Uniform(range=2,std=None,mean=0.), > nonlinearity=lasagne.nonlinearities.sigmoid) > > but I am getting the following error - > > Traceback (most recent call last): > File "categAgent.py", line 203, in <module> > gradient_steps=20) # number of steps for BPTT to unroll network > File > "/home/madvn/anaconda2/lib/python2.7/site-packages/lasagne/layers/recurrent.py", > > line 552, in __init__ > in_to_hid = DenseLayer(InputLayer((None,) + input_shape[2:]), > TypeError: can only concatenate tuple (not "list") to tuple > > Please help. Thanks > > - Madhavun > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
