Getting this error: operands could not be broadcast together with shapes (50,) (2,) (50,)
I am initializing like this: avg = np.zeros(shape=50)
Hi @Hraday
Which assignment ?
C5 W2 A2 Emojify : Exercise 1 - sentence_to_avg
words = [i.lower() for i in sentence.split()]
# Initialize the average word vector, should have the same shape as your word vectors.
avg = np.zeros(shape=50)
# Initialize count to 0
count = 0
# Step 2: average the word vectors. You can loop over the words in the list "words".
for w in ((words)):
# Check that word exists in word_to_vec_map
if w in word_to_vec_map:
avg += word_to_vec_map[w]
# Increment count
count +=1
if count > 0:
# Get the average. But only if count > 0
avg = avg/len(words)
return avg
Can you tell me what am I doing wrong ?
ValueError: operands could not be broadcast together with shapes (50,) (2,) (50,)
I am curious why you feel that a hard-coded value of 50 is the correct shape?
Please review the instructions:
The notebook provides some code that selects a word “any_word” from the dictionary. That’s the correct key to use to get the desired shape.
I’m really lost here, can I get some help? I looked at this after I read the key error love thread, and surmised my issue is in initializing the avg array before I had:
word_to_vec_map[words[0]].s
Now I have something along the lines of:
any_word[].shape
but I’m stuck and not sure what goes in the brackets, I know not to hard code the answer but a random number doesn’t work either.
Hi @olarson117
any_word should be used as an index to word_to_vec_map. So to get the shape of the word vector:
word_to_vec_map[any_word].shape
1 Like
thanks so much! figured it out thank you.
Can anyone tell what we should take the size of the avg array as?
Honestly I still don’t understand why hard coding 50 in np.zeros(50) as the initialization doesn’t work whereas word_to_vec_map[list(word_to_vec_map.keys())[0]].shape which also returns (50,) works ? What am I missing here ?
We can not assume that the shape of a vector map is always 50. It can be 60, 100, whatever…
If a vector map is enhanced and now includes additional features like total 100, do you want to re-write your code ? This is quite inefficient. Once you get the shape dynamically and use it for initialization, then, you do not need to touch any even if a vector map is enhanced.
Think about modern system which consists of millions of code. You can not check one by one.
Dear Hitoro & mentors;
initiation avg=np.zeros(word_to_vec_map[list(word_to_vec_map.keys())[0]].shape)
gives test error as love.
_________________any idea?