Error.txt

ValueError                                Traceback (most recent call last)
<ipython-input-7-5cf5b03019f2> in <module>()
     24 model.compile(loss='mean_squared_error', optimizer=optimizer)
     25 
---> 26 model.fit(X_train, y_train, epochs=100, verbose=2)

/home/q/anaconda3/envs/p3/lib/python3.6/site-packages/keras/models.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, **kwargs)
    868                               class_weight=class_weight,
    869                               sample_weight=sample_weight,
--> 870                               initial_epoch=initial_epoch)
    871 
    872     def evaluate(self, x, y, batch_size=32, verbose=1,

/home/q/anaconda3/envs/p3/lib/python3.6/site-packages/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, **kwargs)
   1505                               val_f=val_f, val_ins=val_ins, shuffle=shuffle,
   1506                               callback_metrics=callback_metrics,
-> 1507                               initial_epoch=initial_epoch)
   1508 
   1509     def evaluate(self, x, y, batch_size=32, verbose=1, sample_weight=None):

/home/q/anaconda3/envs/p3/lib/python3.6/site-packages/keras/engine/training.py in _fit_loop(self, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch)
   1154                 batch_logs['size'] = len(batch_ids)
   1155                 callbacks.on_batch_begin(batch_index, batch_logs)
-> 1156                 outs = f(ins_batch)
   1157                 if not isinstance(outs, list):
   1158                     outs = [outs]

/home/q/anaconda3/envs/p3/lib/python3.6/site-packages/keras/backend/theano_backend.py in __call__(self, inputs)
   1194     def __call__(self, inputs):
   1195         assert isinstance(inputs, (list, tuple))
-> 1196         return self.function(*inputs)
   1197 
   1198 

/home/q/anaconda3/envs/p3/lib/python3.6/site-packages/theano/compile/function_module.py in __call__(self, *args, **kwargs)
    793                         s.storage[0] = s.type.filter(
    794                             arg, strict=s.strict,
--> 795                             allow_downcast=s.allow_downcast)
    796 
    797                     except Exception as e:

/home/q/anaconda3/envs/p3/lib/python3.6/site-packages/theano/tensor/type.py in filter(self, data, strict, allow_downcast)
    115             if allow_downcast:
    116                 # Convert to self.dtype, regardless of the type of data
--> 117                 data = theano._asarray(data, dtype=self.dtype)
    118                 # TODO: consider to pad shape with ones to make it consistent
    119                 # with self.broadcastable... like vector->row type thing

/home/q/anaconda3/envs/p3/lib/python3.6/site-packages/theano/misc/safe_asarray.py in _asarray(a, dtype, order)
     32         dtype = theano.config.floatX
     33     dtype = np.dtype(dtype)  # Convert into dtype object.
---> 34     rval = np.asarray(a, dtype=dtype, order=order)
     35     # Note that dtype comparison must be done by comparing their `num`
     36     # attribute. One cannot assume that two identical data types are pointers

/home/q/anaconda3/envs/p3/lib/python3.6/site-packages/numpy/core/numeric.py in asarray(a, dtype, order)
    529 
    530     """
--> 531     return array(a, dtype, copy=False, order=order)
    532 
    533 

ValueError: Bad input argument to theano function with name "train_function" at index 1 (0-based).  
Backtrace when that variable is created: