Allows to manipulate the network architecture of a Keras deep learning model by choosing a new set of output tensors of the model. Of the original layers of the model, only those that are relevant to produce the selected outputs are retained. The new outputs must be selected in the node configuration.
Options
Output Selection
Popular Predecessors
- Keras Dropout Layer15 %
- Keras Network Reader15 %
- Keras Dense Layer8 %
- Keras Network Learner8 %
- Keras CuDNN LSTM Layer8 %
- Keras Flatten Layer5 %
- Keras LSTM Layer5 %
- Keras Reshape Layer3 %
- Keras Add Layer3 %
- Keras Concatenate Layer3 %
- DL Python Network Editor3 %
- Keras Activity Regularization Layer3 %
- Keras Softmax Layer2 %
- Keras Thresholded ReLU Layer2 %
- Keras Activation Layer2 %
- Keras Input Layer2 %
- Keras Freeze Layers2 %
- Keras Batch Normalization Layer2 %
- Keras Average Pooling 2D Layer2 %
- Keras Global Max Pooling 2D Layer2 %
- Keras CuDNN GRU Layer2 %
- Keras Simple RNN Layer2 %
- DL Python Network Creator2 %
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