想了解两者之间的区别，
from tensorflow.keras.preprocessing.text import Tokenizer
sentences = [
'i love my dog',
'I, love my cat',
'You love my dog!'
]
tokenizer = Tokenizer(num_words = 1)
tokenizer.fit_on_texts(sentences)
word_index = tokenizer.word_index
print(word_index)
订单/订单 - {'love': 1, 'my': 2, 'i': 3, 'dog': 4, 'cat': 5, 'you': 6}
对比
from tensorflow.keras.preprocessing.text import Tokenizer
sentences = [
'i love my dog',
'I, love my cat',
'You love my dog!'
]
tokenizer = Tokenizer(num_words = 100)
tokenizer.fit_on_texts(sentences)
word_index = tokenizer.word_index
print(word_index)
订单/订单 - {'love': 1, …