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
