CODEWITHSUNDEEP
kerasgenerator
simba buffalo
simba buffalo

Reputation: 31

How to use a NN in a keras generator?

I am setting up a fit_generator to train a DNN by keras. But don't know how to use a CNN inside this generator.

Basically, I have a pre-trained image generator using fully-connected convolutional networks (we can named it as GEN-NET). Now I want to used this Fully-CNN in my fit_generator to generate unlimited number of images to train another classifier (called CLASS-NET) in keras. But it always crashed my training and the error message is:

ValueError: Tensor Tensor("decoder/transform_output/mul:0", shape=(?, 128, 128, 1), dtype=float32) is not an element of this graph.

This "decoder/transform_output/mul:0" is the output of my CNN GEN-NET.

So my question is that can I use CNN based GEN-NET in my fit_generator to train GLASS-NET or it is not permitted in keras?

Upvotes: 0

Views: 64

Answers (2)

gerwin
gerwin

Reputation: 909

Keras does not really like running two separate models in a single session. You could use K.clear_session() after using the model but this would produce a lot of overhead!

Best way to do this, IMHO, is by pre-generating these images and then loading them using a generator. Basically splitting your program into two separate programs.

Otherwise, if you are using tensorflow as back-end there might be a way to do it by switching the default graph on the tf.Session, you could Google that but I would not recommend it! :)

Upvotes: 1

TheLoneDeranger
TheLoneDeranger

Reputation: 1199

Seems like you might have things a bit mixed up! The CNN (convolutional neural network) needs to be trained to your data, unless you're using a pretrained network for predictions. If you're going to train the CNN, you can do that with either the fit() or the fit_generator() function. Use fit() if you're feeding data directly, and use fit_generator() if your data is handled by Image Data Generators. If you've loaded a pre-trained model/weights only to make predictions, you don't need to use any fit function, since no training needs to be done.

Upvotes: 0

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