Im am using a tflite model on an edge device with not a lot of RAM. My program reads continuous sensor data and the input layer takes in 150 datapoints. I want to invoke the model in intervals of 50 datapoints so that there is overlap with the data in each invoke. Currently I save the data to a buffer and copy it to the input when I want to invoke the model but this requires too much RAM.
Is there a way to keep the data in the input kayer after invoking, so that I don’t have to hold the data in 2 seperate places?