Error while unpickle custom pipeline Ml model in python

Question

I create a custom Pipeline in python. I have used the sklearn pipeline and it seems running successfully. But When I save the model as a pickle file and want to load that saved pickle file in a different notebook it shows an error.

import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.preprocessing import LabelEncoder
from sklearn import metrics
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
import eli5
from eli5.sklearn import PermutationImportance
from sklearn.pipeline import Pipeline, make_pipeline, FeatureUnion
from sklearn.preprocessing import FunctionTransformer
from sklearn.compose import ColumnTransformer

path = 'C:/Users/Desktop/'
df = pd.read_excel (path + "df.xlsx", sheet_name='df')

###################################################################################

# import the BaseEstimator

from sklearn.base import BaseEstimator

# define the class OutletTypeEncoder
# custom transformer must have methods fit and transform
class OutletTypeEncoder(BaseEstimator):

def __init__(self):
    pass
    #self.name = name

def fit(self, df, y=None):
    return self

def transform(self, df):
    
    # replace NaN
    df[['pdf_tbl_pn_identifier', 'pdf_tbl_qty_identifier', 'pdf_header_present']] = df[['pdf_tbl_pn_identifier', 'pdf_tbl_qty_identifier', 'pdf_header_present']].fillna(value=-999)
    df[['pdf_tbl_cnt']] = df[['pdf_tbl_cnt']].fillna(value=0)

    # Replace gt 1 count as 0
    df['pdf_tbl_cnt'] = np.where((df['pdf_tbl_cnt'] == '1'), 1, 0)
    df['part_cnt'] = np.where((df['part_cnt'] == '1'),  1, 0)

    # create numeric and categorica coulmns
    obj_df= df[['pdf_tbl_pn_identifier','pdf_tbl_qty_identifier','pdf_header_present',
                'pdf_body_pn_identifier','pdf_body_qty_identifier','pdf_model_rel_returned','pdf_model_ent_returned']]
    num_df= df[['pdf_tbl_cnt', 'pdf_model_avg_relationship_score','pdf_model_avg_entity_score','part_cnt']]

    # Labelencoding for categorica columns and then 
    obj_df=obj_df.apply(LabelEncoder().fit_transform)
    df = pd.concat([obj_df, num_df], axis=1)
    #df.reset_index(inplace=True, drop=True)

    df.pdf_tbl_pn_identifier = df.pdf_tbl_pn_identifier.astype(str)
    df.pdf_tbl_qty_identifier = df.pdf_tbl_qty_identifier.astype(str)
    df.pdf_body_pn_identifier = df.pdf_body_pn_identifier.astype(str)
    df.pdf_body_qty_identifier = df.pdf_body_qty_identifier.astype(str)
    df.pdf_model_rel_returned = df.pdf_model_rel_returned.astype(str)
    df.pdf_model_ent_returned = df.pdf_model_ent_returned.astype(str)
    df.pdf_header_present = df.pdf_header_present.astype(str)
    #df.matching = df.matching.astype(str)
    #df['pdf_tbl_cnt'] = df['pdf_tbl_cnt'].apply(np.int64) 
    df.pdf_tbl_cnt = df.pdf_tbl_cnt.apply(np.int64) 

    return df

#################################################################################

feature_cols = df.drop(['matching'], axis=1)
X = feature_cols # Features
y = df.matching # Target variable

# split into train test sets
X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.25,random_state=0)

# Create Pipeline
logreg = LogisticRegression()
model_pipeline = Pipeline(steps=[('preprocess', OutletTypeEncoder()), 
                                 ('logreg', LogisticRegression())
                                 ])    
                                 
                                 
# fit the pipeline with the training data
model_pipeline.fit(X_train,y_train)

# Predict
y_pred=model_pipeline.predict(X_test)

Now I save the model as a pickle file and want to use that pickle file in another notebook. But got an error that: AttributeError: Can't get attribute 'OutletTypeEncoder' on <module 'main'>

# Save the Modle to file in the current working directory

Pkl_Filename = "C:\\Users\\SafayetKarim\\Desktop\\confidence_score\\results_updated\\pdf\\logisic_Model_pipeline.pkl"  

with open(Pkl_Filename, 'wb') as file:  
    pickle.dump(model_pipeline, file)
    
    
    
# Load the Model back from file
with open('C:\\Users\\SafayetKarim\\Desktop\\confidence_score\\results_updated\\pdf\\logisic_Model_pipeline.pkl', 'rb') as file:  
    logisic_Model_pipeline = pickle.load(file)

logisic_Model_pipeline

Please help me out how to resolve the issue.

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-4-28376e81d621> in <module>
      1 # Load the Model back from file
      2 with open('C:\\Users\\SafayetKarim\\Desktop\\confidence_score\\results_updated\\pdf\\OutletTypeEncoder.pkl', 'rb') as file:
----> 3     OutletTypeEncoder = pickle.load(file)
      4 
      5 OutletTypeEncoder

AttributeError: Can't get attribute 'OutletTypeEncoder' on <module '__main__'>

Error while unpickle custom pipeline Ml model in python

0 Answers0