All operation names should be unique.

	inputEle = [ak.ImageInput(name='n1'),ak.ImageInput(name='n2'),
                    ak.ImageInput(name='n3'),ak.ImageInput(name='n4'),ak.ImageInput(name='n5')]
        outputEle = [ak.ClassificationHead(name='n7')]
	am = ak.AutoModel(
        inputs=inputEle,
        outputs=outputEle,
        objective='val_accuracy',
        overwrite=True
    )
    history = am.fit(x=self.inputs, y=self.outputs, validation_split=0.2, verbose=1)`

/usr/local/lib/python3.11/dist-packages/autokeras/auto_model.py in fit(self, x, y, batch_size, epochs, callbacks, validation_split, validation_data, verbose, **kwargs)
    301             )
    302 
--> 303         history = self.tuner.search(
    304             x=dataset,
    305             epochs=epochs,

/usr/local/lib/python3.11/dist-packages/autokeras/engine/tuner.py in search(self, epochs, callbacks, validation_split, verbose, **fit_kwargs)
    198         hp = self.oracle.get_space()
    199         self._prepare_model_build(hp, **fit_kwargs)
--> 200         self._try_build(hp)
    201         self.oracle.update_space(hp)
    202         super().search(

/usr/local/lib/python3.11/dist-packages/keras_tuner/src/engine/tuner.py in _try_build(self, hp)
    162         gc.collect()
    163 
--> 164         model = self._build_hypermodel(hp)
    165         # Stop if `build()` does not return a valid model.
    166         if not isinstance(model, keras.models.Model):

/usr/local/lib/python3.11/dist-packages/keras_tuner/src/engine/tuner.py in _build_hypermodel(self, hp)
    153     def _build_hypermodel(self, hp):
    154         with maybe_distribute(self.distribution_strategy):
--> 155             model = self.hypermodel.build(hp)
    156             self._override_compile_args(model)
    157             return model

/usr/local/lib/python3.11/dist-packages/keras_tuner/src/engine/hypermodel.py in _build_wrapper(self, hp, *args, **kwargs)
    118             # to the search space.
    119             hp = hp.copy()
--> 120         return self._build(hp, *args, **kwargs)
    121 
    122     def declare_hyperparameters(self, hp):

/usr/local/lib/python3.11/dist-packages/autokeras/graph.py in build(self, hp)
    231             for output_node, real_output_node in zip(block.outputs, outputs):
    232                 keras_nodes[self._node_to_id[output_node]] = real_output_node
--> 233         model = keras.Model(
    234             keras_input_nodes,
    235             [

/usr/local/lib/python3.11/dist-packages/keras/src/utils/tracking.py in wrapper(*args, **kwargs)
     24     def wrapper(*args, **kwargs):
     25         with DotNotTrackScope():
---> 26             return fn(*args, **kwargs)
     27 
     28     return wrapper

/usr/local/lib/python3.11/dist-packages/keras/src/models/functional.py in __init__(self, inputs, outputs, name, **kwargs)
    133             inputs, outputs = clone_graph_nodes(inputs, outputs)
    134 
--> 135         Function.__init__(self, inputs, outputs, name=name, **kwargs)
    136 
    137         if trainable is not None:

/usr/local/lib/python3.11/dist-packages/keras/src/ops/function.py in __init__(self, inputs, outputs, name)
     75             self._self_setattr_tracking = _self_setattr_tracking
     76 
---> 77         (nodes, nodes_by_depth, operations, operations_by_depth) = map_graph(
     78             self._inputs, self._outputs
     79         )

/usr/local/lib/python3.11/dist-packages/keras/src/ops/function.py in map_graph(inputs, outputs)
    329     for name in all_names:
    330         if all_names.count(name) != 1:
--> 331             raise ValueError(
    332                 f'The name "{name}" is used {all_names.count(name)} '
    333                 "times in the model. All operation names should be unique."

ValueError: The name "resnet50" is used 4 times in the model. All operation names should be unique.