我到底如何将不同长度的序列传递给keras上的LSTM？

from keras.models import Sequential
from keras.layers import LSTM, Embedding, Dense
from keras.preprocessing.sequence import pad_sequences
from sklearn.model_selection import train_test_split

# 假设有一个序列数据集X和对应的标签y
X = [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
y = [0, 1, 0]

# 对序列数据进行填充，使其具有相同的长度
X_padded = pad_sequences(X)

# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X_padded, y, test_size=0.2)

# 创建LSTM模型
model = Sequential()
model.add(Embedding(input_dim=10, output_dim=32, input_length=X_padded.shape[1]))
model.add(LSTM(units=64))
model.add(Dense(units=1, activation='sigmoid'))

# 配置模型
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])

# 训练模型
model.fit(X_train, y_train, epochs=10, batch_size=32)

# 在测试集上评估模型
loss, accuracy = model.evaluate(X_test, y_test)