from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Embedding, LSTM, Dense, GRU
from tensorflow.keras.datasets import imdb
from tensorflow.keras.preprocessing.sequence import pad_sequences

# Загружаем данные
max_features = 10000
maxlen = 200
(X_train, y_train), (X_test, y_test) = imdb.load_data(num_words=max_features)
X_train = pad_sequences(X_train, maxlen=maxlen)
X_test = pad_sequences(X_test, maxlen=maxlen)

# Создаем модель с LSTM
model = Sequential([
    Embedding(max_features, 128, input_length=maxlen),
    LSTM(64, dropout=0.2, recurrent_dropout=0.2),
    Dense(1, activation='sigmoid')
])

# Компилируем модель
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])

# Обучаем модель
model.fit(X_train, y_train, epochs=5, batch_size=32, validation_split=0.2)

# Оцениваем модель
loss, accuracy = model.evaluate(X_test, y_test)
print(f"Точность LSTM: {accuracy:.2f}")