Difference between over sampling and upsampling and between SMOTE and over_sampling.SMOTE?

Question

This question is a bit of paranoia, as in google the search results gets mixed by the audio and Fourier transform etc.

1. Specifically for python, when it comes to numeric data, is there a difference between oversampling and upsampling of the minority class?

2. I am using imblearn to oversample/upsample a minority class. I am currently using

   from imblearn.over_sampling import SMOTE
   
   sm = SMOTE(random_state=12, ratio = 1.0)
   x_train_res, y_train_res = sm.fit_sample(X_train, y_train)
   

   but more recently, I came across

   sm = over_sampling.SMOTE(random_state=12, ratio = 1.0)
   x_train_res, y_train_res = sm.fit_sample(X_train, y_train)
   

   What is the difference?

Answer 1

from imblearn.over_sampling import SMOTE

sm = SMOTE(random_state=12, ratio = 1.0)

and

import imblearn.over_sampling 

sm = over_sampling.SMOTE(random_state=12, ratio = 1.0)

Is identical. The only difference is how you access the SMOTE function in your code.