为什么fit_transform和transform结果不一样？

请教一下为什么用catboost编码使用fit_transform和transform结果不一样？
我参考的原文链接：https://moonapi.com/news/581.html

# import libraries
import category_encoders as ce
import pandas as pd

# Make dataset
train = pd.DataFrame({
    'color': ["red", "blue", "blue", "green", "red",
              "red", "black", "black", "blue", "green"],

     'interests': ["sketching", "painting", "instruments",
                   "sketching", "painting", "video games",
                   "painting", "instruments", "sketching",
                   "sketching"],

    'height': [68, 64, 87, 45, 54, 64, 67, 98, 90, 87],

    'grade': [1, 2, 3, 2, 3, 1, 4, 4, 2, 3], })

# Define train and target
target = train[['grade']]
train = train.drop('grade', axis = 1)

# Define catboost encoder
cbe_encoder = ce.cat_boost.CatBoostEncoder()

# Fit encoder and transform the features
cbe_encoder.fit(train, target)
train_cbe = cbe_encoder.transform(train)

# We can use fit_transform() instead of fit() and transform() separately as follows:
cbe_encoder1 = ce.cat_boost.CatBoostEncoder()
train_cbe1 = cbe_encoder1.fit_transform(train,target)