The length of word index in the Keras Tokenizer
Consider the following code applied to the IMDB dataset. The printed length of word_index is always 88582 regardless of the value of max_words. I think it should be min(max_words,88582). What is wrong?
from keras.preprocessing.text import Tokenizer
max_words = 100
tokenizer = Tokenizer(num_words=max_words)
tokenizer.fit_on_texts(texts)
print(len(tokenizer.word_index))
python keras
asked May 11 '18 at 4:17
HosseinHossein
981615
add a comment |
Consider the following code applied to the IMDB dataset. The printed length of word_index is always 88582 regardless of the value of max_words. I think it should be min(max_words,88582). What is wrong?
from keras.preprocessing.text import Tokenizer
max_words = 100
tokenizer = Tokenizer(num_words=max_words)
tokenizer.fit_on_texts(texts)
print(len(tokenizer.word_index))
python keras
asked May 11 '18 at 4:17
HosseinHossein
981615
1
I think you will find your answer here: github.com/keras-team/keras/issues/7551
– Ghanem
May 11 '18 at 4:30
Thanks, @Minion. It helped.
– Hossein
May 11 '18 at 4:59
add a comment |
Consider the following code applied to the IMDB dataset. The printed length of word_index is always 88582 regardless of the value of max_words. I think it should be min(max_words,88582). What is wrong?
from keras.preprocessing.text import Tokenizer
max_words = 100
tokenizer = Tokenizer(num_words=max_words)
tokenizer.fit_on_texts(texts)
print(len(tokenizer.word_index))
python keras
asked May 11 '18 at 4:17
HosseinHossein
981615
Consider the following code applied to the IMDB dataset. The printed length of word_index is always 88582 regardless of the value of max_words. I think it should be min(max_words,88582). What is wrong?
from keras.preprocessing.text import Tokenizer
max_words = 100
tokenizer = Tokenizer(num_words=max_words)
tokenizer.fit_on_texts(texts)
print(len(tokenizer.word_index))
python keras
python keras
asked May 11 '18 at 4:17
HosseinHossein
981615
asked May 11 '18 at 4:17
HosseinHossein
981615
asked May 11 '18 at 4:17
HosseinHossein
981615
asked May 11 '18 at 4:17
HosseinHossein
981615
asked May 11 '18 at 4:17
HosseinHossein
981615
981615
1
I think you will find your answer here: github.com/keras-team/keras/issues/7551
– Ghanem
May 11 '18 at 4:30
Thanks, @Minion. It helped.
– Hossein
May 11 '18 at 4:59
add a comment |
1
I think you will find your answer here: github.com/keras-team/keras/issues/7551
– Ghanem
May 11 '18 at 4:30
Thanks, @Minion. It helped.
– Hossein
May 11 '18 at 4:59
1
1
I think you will find your answer here: github.com/keras-team/keras/issues/7551
– Ghanem
May 11 '18 at 4:30
I think you will find your answer here: github.com/keras-team/keras/issues/7551
– Ghanem
May 11 '18 at 4:30
Thanks, @Minion. It helped.
– Hossein
May 11 '18 at 4:59
Thanks, @Minion. It helped.
– Hossein
May 11 '18 at 4:59
add a comment |
1 Answer
1
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max_words is the vocabulary size. So the result shape is (88582,100)
answered Dec 31 '18 at 16:20
johannjohann
11
add a comment |
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max_words is the vocabulary size. So the result shape is (88582,100)
answered Dec 31 '18 at 16:20
johannjohann
11
add a comment |
max_words is the vocabulary size. So the result shape is (88582,100)
answered Dec 31 '18 at 16:20
johannjohann
11
add a comment |
max_words is the vocabulary size. So the result shape is (88582,100)
answered Dec 31 '18 at 16:20
johannjohann
11
max_words is the vocabulary size. So the result shape is (88582,100)
answered Dec 31 '18 at 16:20
johannjohann
11
answered Dec 31 '18 at 16:20
johannjohann
11
answered Dec 31 '18 at 16:20
johannjohann
11
answered Dec 31 '18 at 16:20
johannjohann
11
11
add a comment |
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I think you will find your answer here: github.com/keras-team/keras/issues/7551
– Ghanem
May 11 '18 at 4:30
Thanks, @Minion. It helped.
– Hossein
May 11 '18 at 4:59