Hi Fred,
What command would I use to uninstall theano. I also installed the
latest development version. Does it need a different command to uninstall?
Thanks.
Chi
From: [email protected] [mailto:[email protected]] On
Behalf Of Frédéric Bastien
Sent: Tuesday, November 15, 2016 3:11 PM
To: theano-users
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...
To be safer, uninstall Theano a few time before and make sure you can't import
it before reinstalling.
Le 15 nov. 2016 16:20, "Pascal Lamblin"
<[email protected]<mailto:[email protected]>> a écrit :
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]>
> [mailto:[email protected]<mailto:[email protected]>]
> On Behalf Of Pascal Lamblin
> Sent: Monday, November 14, 2016 12:37 PM
> To: [email protected]<mailto:[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]<mailto:[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]<mailto:theano-users%[email protected]>.
> > For more options, visit https://groups.google.com/d/optout.
>
>
>
> --
> Pascal
>
> --
>
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Pascal
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