Ridurre-Network-Filter-Pruning-Keras
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the size of model become larger
As we know resnet50 is 94M, but when I load the model and retrain it for several epochs, it become 280M, I don't know why because I model.summary() the .h5 and see the parameters are same. Thank you very much.
What is the version of Tensorflow and Keras?
tensorflow 1.8 and keras 2.24
Then I would advice to change to the newest version of Tensorflow and try out with that. It is defined in the requirements: https://github.com/gaborvecsei/Ridurre-Network-Filter-Pruning-Keras/blob/master/requirements.txt#L1
With this version it can happen that the keras.backend.clear_session()
or the tf.reset_default_graph()
does not work reliably: https://github.com/gaborvecsei/Ridurre-Network-Filter-Pruning-Keras/blob/master/ridurre/base_filter_pruning.py#L160
@zhengmiao1996 at last it works? now i also want to have a try to prune the resnet network
Has this problem solved? I got the same situation, I have trained the FER plus datasets by your example(model_pruning_example) but use the origin resnet not yours, then I got a 280M model