for loop over list KeyError: 664 - python-3.x

Question

I am trying to iterate this list with words as
CTCCTC TCCTCT CCTCTC CTCTCC TCTCCC CTCCCA TCCCAA CCCAAA CCAAAC CAAACT
CTGGGC TGGGCC GGGCCA GGCCAA GCCAAT CCAATG CAATGC AATGCC ATGCCT TGCCTG GCCTGC
TGCCAG GCCAGG CCAGGA CAGGAG AGGAGG GGAGGG GAGGGG AGGGGC GGGGCT GGGCTG GGCTGG GCTGGT CTGGTC
TGGTCT GGTCTG GTCTGG TCTGGA CTGGAC TGGACA GGACAC GACACT ACACTA CACTAT
ATTCAG TTCAGC TCAGCC CAGCCA AGCCAG GCCAGT CCAGTC CAGTCA AGTCAA GTCAAC TCAACA CAACAC AACACA
ACACAA CACAAG ACAAGG AGGTGG GGTGGC GTGGCC TGGCCT GGCCTG GCCTGC CCTGCA CTGCAC
TGCACT GCACTC CACTCG ACTCGA CTCGAG TCGAGG CGAGGT GAGGTT AGGTTC GGTTCC
TATATA ATATAC TATACC ATACCT TACCTG ACCTGG CCTGGT CTGGTA TGGTAA GGTAAT GTAATG TAATGG AATGGA
I am trying for loop to read each item in the list and parse it through mk_model.vector
the code used is as follows
for x in all_seq_sentences[:]:
mk_model.vector(x)
print(x)
Usually, mk_model.vector("AGT") will give an array corresponding to defines dna2vec model, But here rather than actually performing the model run it throws error as
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-144-77c47b13e98a> in <module>
1 for x in all_seq_sentences[:]:
----> 2 mk_model.vector(x)
3 print(x)
4
~/Desktop/DNA2vec/dna2vec/dna2vec/multi_k_model.py in vector(self, vocab)
35
36 def vector(self, vocab):
---> 37 return self.data[len(vocab)].model[vocab]
38
39 def unitvec(self, vec):
KeyError: 664
Looking forward to some help here

Answer 1

The above problem was having issues because the for loop took all items in first line as one item, which is why .split() was best solution of it. To read follow https://python-reference.readthedocs.io/en/latest/docs/str/split.html
working code:
for i in all_seq_sentences:
word = i.split()
print(word[0])
and then later implement another loop to access the model.vector function
vec_of_all_seq = []
for sentence in all_seq_sentences:
sentence = sentence.split()
for word in sentence:
vec_of_all_seq.append(mk_model.vector(word))
vector representation derived from model.vector will be saved in numpy array named vec_of_all_seq.