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Is it because I'm using it incorrectly?
my code:
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)`
error:
/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.
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