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The underside layers that happen to be closer for the inputs (the ParallelConv1D blocks in the diagram) are frozen as well as the parameters will keep unchanged at additional tuning the design. The layers which aren't frozen (the upper levels that are nearer on the output, long short-time period memory (LSTM) layer, plus the classifier made up of t
When transferring the pre-properly trained design, Section of the model is frozen. The frozen layers are generally The underside from the neural network, as They're deemed to extract common options. The parameters of your frozen levels will never update for the duration of education. The rest of the layers are not frozen and so are tuned with new f