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Layer names duplicated with multiple image inputs

See original GitHub issue

Bug Description

When multiple ImageBlocks are used in the same model, the layer names they generate are not unique, so the model does not build.

Bug Reproduction

input_node1 = ak.ImageInput()
input_node2 = ak.ImageInput()
output_node1 = ak.ImageBlock(augment=False)(input_node1)
output_node2 = ak.ImageBlock(augment=False)(input_node2)
merged = ak.Merge()([output_node1, output_node2])
output_node = ak.ClassificationHead()(merged)
clf = ak.AutoModel(
    inputs=[input_node1, input_node2],
    outputs=output_node,
    overwrite=True,
    max_trials=5)

Expected Behavior

The model should build. Instead:

ValueError: The name "conv1_pad" is used 2 times in the model. All layer names should be unique.

Setup Details

Include the details about the versions of:

OS type and version: Colab
Python: 3.6
autokeras: 1.0.3
keras-tuner: 1.0.2rc0
scikit-learn: 0.22.2.post1
numpy: 1.18.5
pandas: 1.0.5
tensorflow: 2.2.0

Issue Analytics

State:
Created 3 years ago
Reactions:8
Comments:5

Top GitHub Comments

2reactions

rakshith291commented, Jan 7, 2021

Renaming the layers in the following way solved the problem for me.

for layer in model_con_1.layers : layer._name = layer.name + str(‘_1’) for layer in model_con_2.layers : layer._name = layer.name + str(‘_2’)

0reactions

abe-martincommented, Mar 7, 2022

Bump on this one. Is it possible to use multiple image inputs with AutoModel? I see that rakshith291 posted some code to rename layers, but where does that go, somewhere in the source of the fit function?