I have a error when trying to call calculate_similarity2 function which in in DocSim.py file from my notebook.
The error message is : 'DocSim' object has no attribute 'calculate_similarity2'
Here the content of my docsim File :
import numpy as np
class DocSim(object):
def __init__(self, w2v_model , stopwords=[]):
self.w2v_model = w2v_model
self.stopwords = stopwords
def vectorize(self, doc):
"""Identify the vector values for each word in the given document"""
doc = doc.lower()
words = [w for w in doc.split(" ") if w not in self.stopwords]
word_vecs = []
for word in words:
try:
vec = self.w2v_model[word]
word_vecs.append(vec)
except KeyError:
# Ignore, if the word doesn't exist in the vocabulary
pass
# Assuming that document vector is the mean of all the word vectors
# PS: There are other & better ways to do it.
vector = np.mean(word_vecs, axis=0)
return vector
def _cosine_sim(self, vecA, vecB):
"""Find the cosine similarity distance between two vectors."""
csim = np.dot(vecA, vecB) / (np.linalg.norm(vecA) * np.linalg.norm(vecB))
if np.isnan(np.sum(csim)):
return 0
return csim
def calculate_similarity(self, source_doc, target_docs=[], threshold=0):
"""Calculates & returns similarity scores between given source document & all
the target documents."""
if isinstance(target_docs, str):
target_docs = [target_docs]
source_vec = self.vectorize(source_doc)
results = []
for doc in target_docs:
target_vec = self.vectorize(doc)
sim_score = self._cosine_sim(source_vec, target_vec)
if sim_score > threshold:
results.append({
'score' : sim_score,
'sentence' : doc
})
# Sort results by score in desc order
results.sort(key=lambda k : k['score'] , reverse=True)
return results
def calculate_similarity2(self, source_doc=[], target_docs=[], threshold=0):
"""Calculates & returns similarity scores between given source document & all the target documents."""
if isinstance(source_doc, str):
target_docs = [source_doc]
if isinstance(target_docs, str):
target_docs = [target_docs]
#source_vec = self.vectorize(source_doc)
results = []
for doc in source_doc:
source_vec = self.vectorize(doc)
for doc1 in target_docs:
target_vec = self.vectorize(doc)
sim_score = self._cosine_sim(source_vec, target_vec)
if sim_score > threshold:
results.append({
'score' : sim_score,
'source sentence' : doc,
'target sentence' : doc1
})
# Sort results by score in desc order
results.sort(key=lambda k : k['score'] , reverse=True)
return results
here in instruction code when i try to call the fucntion :
To create DocSim Object
ds = DocSim(word2vec_model,stopwords=stopwords)
sim_scores = ds.calculate_similarity2(source_doc, target_docs)
the error message is :
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-54-bb0bd1e0e0ad> in <module>()
----> 1 sim_scores = ds.calculate_similarity2(source_doc, target_docs)
AttributeError: 'DocSim' object has no attribute 'calculate_similarity2'
i don't undersantand how to resolve this problem.
I can access to all function except calculate_similarity2
Can you help me please?
thanks
calculate_similarity2as an inner function in the initializer, so it indeed doesn't become a method of your class. Move the function definition outside the initializer and you'll be fine.stopwordsargument to your initializer), cf docs.python-guide.org/writing/gotchas/…