I converted a TF model to be used with TFLite micro. This model uses a custom layer where there
are some tf.Variable (instead of numpy arrays for partial computations)
and for loops statements (implemented with tf.range, not tf.while_loop statements). I'm using
weights chosen randomly for now. The custom layer is written in custom_layer.py.
From Netron (Netron.png image) I see the TFLite model uses FlexVarHandleOp and FlexAssignVariableOp: these ops are supported through AddVarHandle() and AddAssignVariable() which are in micro_mutable_op_resolver, right? Regarding While op, is it supported in TFLite micro? If not, is there a workaround to use it?