my code:
inputEle = [ak.ImageInput(name='n1'),ak.ImageInput(name='n2'),
ak.ImageInput(name='n3'),ak.ImageInput(name='n4')]
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 is:
/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.
it looks like i use same layer,but i use different name to each Input.
Is it that auto-keras doesn't support using multiple ImageInput, or is there something wrong with my usage?
The official documentation doesn't provide an explanation. Wanted to know if it is good practice to do that and what would be the best way to do that?
