[Python] Save and reuse TfidfVectorizer in scikit learn

I am using TfidfVectorizer in scikit learn to create a matrix from text data. Now I need to save this object to reuse it later. I tried to use pickle, but it gave the following error.

loc=open('vectorizer.obj','w')
pickle.dump(self.vectorizer,loc)
*** TypeError: can't pickle instancemethod objects


I tried using joblib in sklearn.externals, which again gave similar error. Is there any way to save this object so that I can reuse it later?

Here is my full object:

class changeToMatrix(object):
def __init__(self,ngram_range=(1,1),tokenizer=StemTokenizer()):
from sklearn.feature_extraction.text import TfidfVectorizer
self.vectorizer = TfidfVectorizer(ngram_range=ngram_range,analyzer='word',lowercase=True,
token_pattern='[a-zA-Z0-9]+',strip_accents='unicode',
tokenizer=tokenizer)

def load_ref_text(self,text_file):
textfile = open(text_file,'r')
lines = textfile.readlines()
textfile.close()
sent_tokenizer = nltk.data.load('tokenizers/punkt/english.pickle')
sentences = [item.strip().strip('.') for item in sent_tokenizer.tokenize(' '.join(lines).strip())]
#vectorizer is transformed in this step
chk2 = pd.DataFrame(self.vectorizer.fit_transform(sentences1).toarray())
return sentences, [chk2]

def get_processed_data(self,data_loc):
ref_sentences,ref_dataframes=self.load_ref_text(data_loc)
loc = open("indexedData/vectorizer.obj","w")
pickle.dump(self.vectorizer,loc) #getting error here
loc.close()
return ref_sentences, ref_dataframes

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