TFX Transform component operates with Tensors that cannot be executed eagerly within its preprocessing_fn. Therefore the values for each feature cannot be passed to a python function that generates new features based on those values.
I tried creating a custom component but failed to modify the input data as tf.Example objects can't be modified.
What is the recommended way to construct complex/custom features from within the pipeline?
