Hi Pascal, I did have 0.8.2.
I installed the latest development version. But, I got the same error. I tried changing my program in various way to work around this without any success. Could you recommend a work around? Thanks. Chi -----Original Message----- From: [email protected] [mailto:[email protected]] On Behalf Of Pascal Lamblin Sent: Tuesday, November 15, 2016 1:21 PM To: [email protected] Subject: Re: [theano-users] TypeError: Cannot convert Type TensorType(float64, 3D) (of Variable Subtensor{:int64:}.0) into Type TensorType(float64, (False, True, False)). You can try to manually convert Subtensor{:int64:}.0 into a TensorType(float64, (False, Tr... On Tue, Nov 15, 2016, Chi Ku wrote: > Hi Pascal, > > How would I find out which version of Theano I have? You can try to print theano.version.version, that should be generated when you call "pip install" > Can I use the following command to install the latest development version? > > <sudo> pip install <--user> <--no-deps> > git+https://github.com/Theano/Theano I think so. > > Thanks. > > Chi > > > > > > > -----Original Message----- > From: [email protected] [mailto:[email protected]] On > Behalf Of Pascal Lamblin > Sent: Monday, November 14, 2016 12:37 PM > To: [email protected] > Subject: Re: [theano-users] TypeError: Cannot convert Type > TensorType(float64, 3D) (of Variable Subtensor{:int64:}.0) into Type > TensorType(float64, (False, True, False)). You can try to manually convert > Subtensor{:int64:}.0 into a TensorType(float64, (False, Tr... > > Which version of Theano are you using? > If you are using the 0.8.2 release, can you try the latest development > version? > > On Sat, Nov 12, 2016, [email protected] wrote: > > > > I got the following errors when calling tensor.grad() to compute the > > symbolic gradient of the finetune_cost of a hybrid DBN-RNN model. > > I tried changing the way this expression is formed in several ways without > > any success. I need help from experts. A tar file of the source code > > and data is attached here. > > > > The pretraining code for file hybrid_array.py ran for 0.48m > > ... getting the finetuning functions > > Traceback (most recent call last): > > File "/usr/lib/python2.7/pdb.py", line 1314, in main > > pdb._runscript(mainpyfile) > > File "/usr/lib/python2.7/pdb.py", line 1233, in _runscript > > self.run(statement) > > File "/usr/lib/python2.7/bdb.py", line 400, in run > > exec cmd in globals, locals > > File "<string>", line 1, in <module> > > File "hybrid_array.py", line 494, in <module> > > test_DBN() > > File "hybrid_array.py", line 412, in test_DBN > > learning_rate=finetune_lr > > File "hybrid_array.py", line 253, in build_finetune_functions > > gparams = T.grad(self.finetune_cost, self.params) > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 561, in grad > > grad_dict, wrt, cost_name) > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 1324, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, in access_term_cache > > output_grads = [access_grad_cache(var) for var in node.outputs] > > output_grads = [access_grad_cache(var) for var in node.outputs] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, in access_term_cache > > output_gra term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 973, 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 > > 1279, in access_grad_cache > > term = access_term_cache(node)[idx] > > File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line > > 1113, in access_term_cache > > input_grads = node.op.grad(inputs, new_output_grads) > > File > > "/usr/local/lib/python2.7/dist-packages/theano/scan_module/scan_op.py", > > line 2523, in grad > > outputs = local_op(*outer_inputs) > > File "/usr/local/lib/python2.7/dist-packages/theano/gof/op.py", line 611, > > in __call__ > > node = self.make_node(*inputs, **kwargs) > > File > > "/usr/local/lib/python2.7/dist-packages/theano/scan_module/scan_op.py", > > line 430, in make_node > > new_inputs.append(format(outer_seq, as_var=inner_seq)) > > File > > "/usr/local/lib/python2.7/dist-packages/theano/scan_module/scan_op.py", > > line 422, in format > > rval = tmp.filter_variable(rval) > > File "/usr/local/lib/python2.7/dist-packages/theano/tensor/type.py", line > > 233, in filter_variable > > self=self)) > > TypeError: Cannot convert Type TensorType(float64, 3D) (of Variable > > Subtensor{:int64:}.0) into Type TensorType(float64, (False, True, False)). > > You can try to manually convert Subtensor{:int64:}.0 into a > > TensorType(float64, (False, True, False)). > > Uncaught exception. Entering post mortem debugging > > Running 'cont' or 'step' will restart the program > > > > > /usr/local/lib/python2.7/dist-packages/theano/tensor/type.py(233)filter_variable() > > -> self=self)) > > > > > > > > -- > > > > --- > > 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. > > > > -- > Pascal > > -- > > --- > You received this message because you are subscribed to a topic in the Google > Groups "theano-users" group. > To unsubscribe from this topic, visit > https://groups.google.com/d/topic/theano-users/8uSF6ub-drA/unsubscribe. > To unsubscribe from this group and all its topics, send an email to > [email protected]. > For more options, visit https://groups.google.com/d/optout. > > -- > > --- > 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. -- Pascal -- --- You received this message because you are subscribed to a topic in the Google Groups "theano-users" group. 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