.SMArtIInt.Blocks.EvaluateRecurrentNeuralNet

Information

Use this block if you want to include a recurrent neural network in Modelica.

Please place this block in your model and

• give the path to the TFLite model
• specify the number of inputs
• specify the sampling interval and how many elements from previous times should be fed into the net
• provide the values for the input of the block and use the outputs in the same manner as it was done during training

In continuous mode the historic values are generated by a delay. You could choose between the computational improved Clara-Delay and the delay in the Modelica-Standard-Library. If continuous is deactivated the model will create an event when reaching the sampling time - this should be avoided for performance reasons.

As tensorflow lite uses a flattened input array, you have to specify the flattening method. In the standard tensorflow setting you have to use the predefined option OldFirstInputSequential.

The example TF_PI_RNN uses this block.