thanks @Retired_mod 

three clarification questions:

1.  wouldn't this cause issues when I load the model for inference? because in this case the model signature is different from the input?

2. I also need to log the signature of prediction output. should I just do

df_predictions = lr_model.transform(df_validation_sampled)
signature = ModelSignature(inputs=Schema(input_columns), output=Schema(df_predictions[["prediction]]))

3. to pass the input_sample, should I also just pass the rows of my dataset before transformation?