token.texts_to_sequences

`token.texts_to_sequences` is a method in the Keras Tokenizer class that converts a list of texts into a list of sequences (i.e., lists of integers). Each integer represents a word in the text, and the list of integers represents the sequence of words in the text. The method takes in a list of texts as its argument and returns a list of sequences.

For example, suppose we have a list of text documents:

texts = [
    "the cat in the hat",
    "the dog chased the cat",
    "the cat ran away from the dog"
]

We can use the Tokenizer class to tokenize these texts and convert them into sequences:

from keras.preprocessing.text import Tokenizer

# create tokenizer object
token = Tokenizer()

# fit tokenizer on the texts
token.fit_on_texts(texts)

# convert texts to sequences
sequences = token.texts_to_sequences(texts)

print(sequences)

This will output:

[
  [1, 2, 3, 4],
  [1, 5, 6, 1, 2],
  [1, 2, 7, 8, 9, 1, 5]
]

In this example, the word "the" is assigned the integer value 1, "cat" is assigned 2, "in" is assigned 3, and so on. The first sequence ([1, 2, 3, 4]) corresponds to the first text ("the cat in the hat"), where "the" is the first word, "cat" is the second word, and so on.