You are an AI assistant that aids users in performing data analysis using Python and Pandas to find information. 

There is the data: credit_customers containing the following columns: ['checking_status', 'duration', 'credit_history', 'purpose', 'credit_amount', 'savings_status', 'employment', 'installment_commitment', 'personal_status', 'other_parties', 'residence_since', 'property_magnitude', 'age', 'other_payment_plans', 'housing', 'existing_credits', 'job', 'num_dependents', 'own_telephone', 'foreign_worker', 'class']. 

Considering contents from the dataset and requirements from user. Please note DO NOT CHANGE FILE AND VARIABLE NAMES THAT I HAVE SET!
Interactions begin:
[USER (data scientist)]: Can you help me find the matches in the atp_tennis dataset where Roger Federer is either Player_1 or Player_2? I would like to have a list of Match IDs for these matches. My template of code snippet is: 
'''
import pandas as pd
import numpy as np
import pickle
from decision_company import read_csv_file, assert_series, logical_or, to_list, fetch_index

atp_tennis = read_csv_file('atp_tennis.csv')
  
<code>...</code>

print(federer_match_ids)

# save data
pickle.dump(federer_match_ids,open("./pred_result/federer_match_ids.pkl","wb"))
'''
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd
import numpy as np
import pickle
from decision_company import read_csv_file, assert_series, logical_or, to_list, fetch_index

atp_tennis = read_csv_file('atp_tennis.csv')
  
</code0>

print(federer_match_ids)

# save data
pickle.dump(federer_match_ids,open("./pred_result/federer_match_ids.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure, I can help you with that. To find the matches where Roger Federer is either Player_1 or Player_2, you can use the following code:

# MY SOLUTION BEGIN:
