ericmcmc
commented
5 years ago Hello ,
I think it could be caused by theano config. Seeing the error you are getting, the problem could be the parameter floatX in theano's config is set as float64 when it should be float32.
To check theano's config you can do:
import theano
print(theano.config)
To set a new config for an execution you can do it like this:
THEANO_FLAGS='floatX=float32' python training.py
More information here: http://deeplearning.net/software/theano/library/config.html
If the problem remains the same, could you send a more detailed info about theano's config and the sentences you are passing to the net?
Regards
mrcabellom
TomReidNZ
gsegares
On a new clone of your repo, I can't get the model to train. There's a type mismatch in the updates when building the optimizer.
Running on conda on macOS (using CPU). I didn't mess with any files, just added in the .txt file. I tried updating the n_words, changing various things in the config file but no luck.
Any help would be much appreciated. Thanks, Tom
Error message:
Building optimizers... Traceback (most recent call last): File "/anaconda3/envs/storytelling/lib/python3.5/site-packages/theano/compile/pfunc.py", line 193, in rebuild_collect_shared allow_convert=False) File "/anaconda3/envs/storytelling/lib/python3.5/site-packages/theano/tensor/type.py", line 234, in filter_variable self=self)) TypeError: Cannot convert Type TensorType(float64, matrix) (of Variable Elemwise{add,no_inplace}.0) into Type TensorType(float32, matrix). You can try to manually convert Elemwise{add,no_inplace}.0 into a TensorType(float32, matrix).
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "training.py", line 6, in
EncTrainer.train()
File "/Users/tom/Documents/development/ailab/Pix2Story/source/training/train_encoder.py", line 40, in train
trainer(self.text, self.training_options)
File "/Users/tom/Documents/development/ailab/Pix2Story/source/skipthoughts_vectors/training/train.py", line 128, in trainer
f_grad_shared, f_update = eval(optimizer)(lr, tparams, grads, inps, cost)
File "/Users/tom/Documents/development/ailab/Pix2Story/source/skipthoughts_vectors/encdec_functs/optim.py", line 40, in adam
f_update = theano.function([lr], [], updates=updates, on_unused_input='ignore', profile=False)
File "/anaconda3/envs/storytelling/lib/python3.5/site-packages/theano/compile/function.py", line 317, in function
output_keys=output_keys)
File "/anaconda3/envs/storytelling/lib/python3.5/site-packages/theano/compile/pfunc.py", line 449, in pfunc
no_default_updates=no_default_updates)
File "/anaconda3/envs/storytelling/lib/python3.5/site-packages/theano/compile/pfunc.py", line 208, in rebuild_collect_shared
raise TypeError(err_msg, err_sug)
TypeError: ('An update must have the same type as the original shared variable (shared_var=<TensorType(float32, matrix)>, shared_var.type=TensorType(float32, matrix), update_val=Elemwise{add,no_inplace}.0, update_val.type=TensorType(float64, matrix)).', 'If the difference is related to the broadcast pattern, you can call the tensor.unbroadcast(var, axis_to_unbroadcast[, ...]) function to remove broadcastable dimensions.')