def get_output(self, layer, X):
        if isinstance(layer, basestring):
            layer = self.layers_[layer]

        fn_cache = getattr(self, '_get_output_fn_cache', None)
        if fn_cache is None:
            fn_cache = {}
            self._get_output_fn_cache = fn_cache

        if fn_cache not in layer:
            xs = self.layers_[0].input_var.type()
            get_activity = theano.function([xs], get_output(layer, xs))
            fn_cache[layer] = get_activity
        else:
            get_activity = fn_cache[layer]

        outputs = []
        for Xb, yb in self.batch_iterator_test(X):
            outputs.append(get_activity(Xb))
        return np.vstack(outputs)
dataset/ETHPy150Open dnouri/nolearn/nolearn/lasagne/base.py/NeuralNet.get_output/swapped operands of `not in`