How to import Keras layers for regression?
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Hi all. I am playing around with importing Keras layers for an LSTM problem but can't seem to get even a basic fully connected single layer network to work. Even though my Keras model just has a basic input layer, Matlab reads it as an "ImageInputLayer". This is for a simple sequence-to-sequence regression problem. I just want to feed in a 2D matrix with multiple features and a series of timesteps but it expects a 3D image tensor. Is there something wrong with the Keras model or do I need to preprocess my data differently? Thanks in advance!
2 件のコメント
Friedrich Seiffarth
2020 年 8 月 24 日
Did you find a solution for your problem ? Because I am running into the same problem.
回答 (1 件)
Sivylla Paraskevopoulou
2022 年 5 月 9 日
Since R2020b, Deep Learning Toolbox provides the featureInputLayer layer, and since R2021a you can import the TensorFlow-Keras layer Input as a featureInputLayer. For a complete list, see TensorFlow-Keras Layers Supported for Conversion into Built-In MATLAB Layers.
The importTensorFlowNetwork function tries to append an output layer to the imported network by interpreting the loss function of the TensorFlow model. If your model doesn't specify a loss function, specify the OutputLayerType name-value argument of importTensorFlowNetwork as "regression".
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