Hi I am training a custom LSTM model on theano with LSTM layers as in (https://github.com/asheshjain399/NeuralModels/tree/master/neuralmodels/layers/LSTM.py) and (https://github.com/asheshjain399/NeuralModels/blob/master/neuralmodels/layers/multilayerLSTM.py). Now the model that I have created makes a valid theano graph but at the step the find the updates (RMSprop) of the model with a cost (mean square) function via the theano.grad function, I keep getting the following error. The source of the error is that a theano op (Elemwise{minimum,no_inplace}.0) is being sent for slicing to the subtensor.py file instead of a theano constant. The issue is that I am not sure how it ends up there. The model works if I remove the LSTM layer, but this LSTM layer works with some other model perfectly.
I'll be extremely thankful if someone can help me through this error which is bugging me for days now. Best Siddhartha ------------------------------------------------------------- File "trainGCNN_NoGraph.py", line 251, in trainGCNN gcnn = GCNNmodelRegression(preGraphNets,nodeList,nodeFeatureLength,temporalNodeFeatureLength,new_idx,featureRange) File "trainGCNN_NoGraph.py", line 202, in GCNNmodelRegression gcnn = GCNN(graphLayers,finalLayer,preGraphNets,nodeNames,temporalNodeRNN,nodeRNNs,topLayer,euclidean_loss,nodeLabels,learning_rate,adjacency,new_idx,featureRange,clipnorm=args.clipnorm,update_type=gradient_method,weight_decay=args.weight_decay) File "/home/siddhartha/Graph_CNNs/neuralmodels/models/GCNN.py", line 169, in __init__ [self.updates,self.grads] = self.update_type.get_updates(self.params_all,self.cost) File "/home/siddhartha/Graph_CNNs/neuralmodels/updates.py", line 108, in get_updates grads_unclipped = T.grad(cost, params) File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 555, in grad grad_dict, wrt, cost_name) File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 1317, in _populate_grad_dict rval = [access_grad_cache(elem) for elem in wrt] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 1272, in access_grad_cache term = access_term_cache(node)[idx] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 967, in access_term_cache output_grads = [access_grad_cache(var) for var in node.outputs] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 1272, in access_grad_cache term = access_term_cache(node)[idx] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 967, in access_term_cache output_grads = [access_grad_cache(var) for var in node.outputs] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 1272, in access_grad_cache term = access_term_cache(node)[idx] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 967, in access_term_cache output_grads = [access_grad_cache(var) for var in node.outputs] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 1272, in access_grad_cache term = access_term_cache(node)[idx] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 967, in access_term_cache output_grads = [access_grad_cache(var) for var in node.outputs] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 1272, in access_grad_cache term = access_term_cache(node)[idx] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 967, in access_term_cache output_grads = [access_grad_cache(var) for var in node.outputs] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 1272, in access_grad_cache term = access_term_cache(node)[idx] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 967, in access_term_cache output_grads = [access_grad_cache(var) for var in node.outputs] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 1272, in access_grad_cache term = access_term_cache(node)[idx] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 967, in access_term_cache output_grads = [access_grad_cache(var) for var in node.outputs] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 1272, in access_grad_cache term = access_term_cache(node)[idx] File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line 1108, in access_term_cache new_output_grads) File "/usr/local/lib/python2.7/dist-packages/theano/scan_module/scan_op.py", line 2250, in L_op outer_inp_seqs = [s_[:grad_steps] for s_ in outer_inp_seqs] File "/usr/local/lib/python2.7/dist-packages/theano/tensor/var.py", line 519, in __getitem__ theano.tensor.subtensor.Subtensor.convert(arg) File "/usr/local/lib/python2.7/dist-packages/theano/tensor/subtensor.py", line 378, in convert slice_b = Subtensor.convert(b, False) File "/usr/local/lib/python2.7/dist-packages/theano/tensor/subtensor.py", line 348, in convert raise TypeError("Expected an integer") TypeError: Expected an integer -- --- 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 theano-users+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.