from keras.preprocessing.text import text_to_word_sequence
import pandas as pd
from keras.preprocessing.text import Tokenizer
import numpy as np
# from __future__ import print_function
from keras.preprocessing import sequence
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation
from keras.layers import Embedding
from keras.layers import Conv1D, GlobalMaxPooling1D
x = df_f.iloc[:, 1].values
y = df_f.iloc[:, 0].values
tk = Tokenizer(num_words= 200, filters = '!"#$%&()*+,-./:;<=>?@[\\]^_`{|}~\t\n',lower=True,
split=" ")
tk.fit_on_texts(x)
x = tk.texts_to_sequences(x)
x = sequence.pad_sequences(x, maxlen=200)
from keras import utils as np_utils
y =np_utils.to_categorical(y, num_classes= 24)
I am using keras version 2.5 and tenser flow version 2.5 I import utils from keras
Newer versions of keras==2.4.0 and tensorflow==2.3.0 would work as follows so use:
from keras.utils import np_utils
and then replace keras.utils.to_categorical with
keras.utils.np_utils.to_categorical
U can also use from tensorflow.keras.utils import to_categorical this error pops up for a lot of attributes.
Sometimes, clearly importing the attribute also helps, but in this case; you have to specify tensorflow.keras