How to implement a CNN-LSTM model using Keras?
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Sara Jones
Mar 9, 2021, 7:05:14 AM3/9/21
to Keras-users
I am attempting to implement a CNN-LSTM that classifies mel-spectrogram images representing the speech of people with Parkinson's Disease/Healthy Controls. I am trying to implement a pre-existing model (DenseNet-169) with an LSTM model, however I am running into the following error:
ValueError: Input 0 of layer zero_padding2d is incompatible with the layer: expected ndim=4, found ndim=3. Full shape received: [None, 216, 1].
Can anyone advise where I'm going wrong? (Please see following link for the code: https://github.com/saraajones05/ParkinsonsCNNLSTM).
Lance Norskog
Mar 9, 2021, 1:23:36 PM3/9/21
to Sara Jones, Keras-users
The man page for TimeDistributed shows a different input spec for the wrapper layer than the applied layer.
You need two input_spec values, the 4d spec for the TD layer and the 3d spec for the DenseNet.
Cheers,
Lance Norskog
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