TypeError

[sourabhdeoghare]

Loading data
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Building f_cost...
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Computing gradient...
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Building optimizers...
Traceback (most recent call last):
File "/home/sourabh/anaconda3/lib/python3.6/site-packages/Theano-1.0.4-py3.6.egg/theano/compile/pfunc.py", line 193, in rebuild_collect_shared
allow_convert=False)
File "/home/sourabh/anaconda3/lib/python3.6/site-packages/Theano-1.0.4-py3.6.egg/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 "train_nmt.py", line 44, in
'reload': [False]})
File "train_nmt.py", line 31, in main
overwrite=False)
File "/home/sourabh/codes/dl4mt-tutorial-master/session1/nmt.py", line 975, in train
f_grad_shared, f_update = eval(optimizer)(lr, tparams, grads, inps, cost)
File "/home/sourabh/codes/dl4mt-tutorial-master/session1/nmt.py", line 773, in adam
on_unused_input='ignore', profile=profile)
File "/home/sourabh/anaconda3/lib/python3.6/site-packages/Theano-1.0.4-py3.6.egg/theano/compile/function.py", line 317, in function
output_keys=output_keys)
File "/home/sourabh/anaconda3/lib/python3.6/site-packages/Theano-1.0.4-py3.6.egg/theano/compile/pfunc.py", line 449, in pfunc
no_default_updates=no_default_updates)
File "/home/sourabh/anaconda3/lib/python3.6/site-packages/Theano-1.0.4-py3.6.egg/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=Wemb_mean, 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.')