Traceback (most recent call last):


 "fastcell.py", line 43, in <module>

model.add(RNN(cell2,return_sequences=True))


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\training\checkpointable\base.py", line 474, in _method_wrapper

method(self, *args, **kwargs)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\sequential.py", line 175, in add

output_tensor = layer(self.outputs[0])


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\keras\layers\recurrent.py", line 619, in __call__

return super(RNN, self).__call__(inputs, **kwargs)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py", line 757, in __call__

outputs = self.call(inputs, *args, **kwargs)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\keras\layers\recurrent.py", line 750, in call

input_length=timesteps)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\keras\backend.py", line 3201, in rnn

outputs, _ = step_function(inputs[0], initial_states + constants)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\keras\layers\recurrent.py", line 737, in step

output, new_states = self.cell.call(inputs, states, **kwargs)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\contrib\rnn\python\ops\rnn_cell.py", line 1683, in call

self._linear = _Linear(cell_inputs, 2 * self._num_units, True)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\contrib\rnn\python\ops\core_rnn_cell.py", line 99, in __init__

initializer=kernel_initializer)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 1487, in get_variable

aggregation=aggregation)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 1237, in get_variable

aggregation=aggregation)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 540, in get_variable

aggregation=aggregation)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 492, in _true_getter

aggregation=aggregation)


 "d:\Users\prane\Anaconda3\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 861, in _get_single_variable

name, "".join(traceback.format_list(tb))))
ValueError: Variable kernel already exists, disallowed. Did you mean to set reuse=True or reuse=tf.AUTO_REUSE in VarScope? Originally defined at:

Traceback (most recent call last):

line 641, in train

self.trained_final_model = self.train_ml_estimator(self.model_names, self._scorer, X_df, y)

line 1237, in train_ml_estimator

gscv_results = self.fit_grid_search(X_df, y, grid_search_params, feature_learning=feature_learning)

line 1162, in fit_grid_search

gs.fit(X_df, y)


 "/usr/local/lib/python2.7/dist-packages/evolutionary_search/cv.py", line 355, in fit

self._fit(X, y, possible_params)


 "/usr/local/lib/python2.7/dist-packages/evolutionary_search/cv.py", line 426, in _fit

halloffame=hof, verbose=self.verbose)


 "/usr/local/lib/python2.7/dist-packages/deap/algorithms.py", line 150, in eaSimple

fitnesses = toolbox.map(toolbox.evaluate, invalid_ind)


 "/usr/lib/python2.7/multiprocessing/pool.py", line 251, in map

return self.map_async(func, iterable, chunksize).get()


 "/usr/lib/python2.7/multiprocessing/pool.py", line 567, in get

raise self._value
cPickle.PicklingError: Can't pickle <type 'instancemethod'>: attribute lookup __builtin__.instancemethod failed
