#pip install tensorflow

import tensorflow as tf
from tensorflow.keras.datasets import reuters
from tensorflow.keras.preprocessing.sequence import pad_sequences
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Embedding, SimpleRNN, Dense
(x_train, y_train), (x_test, y_test) = reuters.load_data(num_words=10000)
x_train = pad_sequences(x_train, maxlen=100)
x_test = pad_sequences(x_test, maxlen=100)
model = Sequential([
    Embedding(10000, 64),
    SimpleRNN(64),
    Dense(46, activation='softmax')  # 46 classes for Reuters dataset
])
model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

model.fit(x_train, y_train, epochs=5, validation_data=(x_test, y_test))
test_loss, test_acc = model.evaluate(x_test, y_test)
print(f"Test accuracy: {test_acc}")