title: Silence when loading lightgbm model in python from pickle
body: <p>I have a question concerning the loading of lightgbm model previously saved as pickle.</p>
  
  <p>If I train, save and load a model as pickle in the same script, when loading the pickle nothing will be printed.
  With this script, nothing is printed when loading the model.</p>
  
  <pre><code>import pandas as pd                                                                                                                                                                                                                                                                      
  import numpy as np                                                                                                                                                                                                                                                                                        
  import pickle                                                                                                                                                                                                                                                                              
  import lightgbm as lgb                                                                                                                                                                                                                                                   
  
  params = {                                                                                                                                                                                                                                                                                      
  'objective': 'regression',                                                                                                                                                                                                                                                                 
  'verbose': -1,                                                                                                                                                                                                                                                                             
  'num_leaves': 3                                                                                                                                                                                                                                                                       
  }  
  
  X = np.random.rand(100,2)                                                                                                                                                                                                                                                              
  Y = np.ravel(np.random.rand(100,1))                                                                                                                                                                                                                                                        
  lgbm = lgb.train(params, lgb.Dataset(X,label=Y),num_boost_round=1)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                
  
  f = open('test_pickle.pkl','wb')                                                                                                                                                                                                                                                           
  pickle.dump(lgbm,f)                                                                                                                                                                                                                                                                        
  f.close()                                                                                                                                                                                                                                                                                  
  
  f = open('test_pickle.pkl','r')                                                                                                                                                                                                                                                            
  pickle.load(f)                                                                                                                                                                                                                                                                             
  f.close()`      
  </code></pre>
  
  <p>If after that I open a new script and load the model like this :</p>
  
  <pre><code>import pickle
  f = open('test_pickle.pkl','r')
  pickle.load(f)
  f.close()
  </code></pre>
  
  <p>there will be a print like this :</p>
  
  <p><code>[LightGBM] [Info] Finished loading 2 models</code></p>
  
  <p>My question is : how can I do to not have the printing when the model is loaded not in the script where it was saved ?</p>
  
  <p>Thanks in advance</p>
  
  <p>Ben</p>