在运行LSTM模型时，我被这段代码卡住了-

# Create cell state and hidden state variables to maintain the state of the LSTM
c, h = [], []
initial_state = []

for li in range(n_layers):
    c.append(tf.Variable(tf.zeros([batch_size, num_nodes[li]]), trainable=False))
    h.append(tf.Variable(tf.zeros([batch_size, num_nodes[li]]), trainable=False))
    initial_state.append(tf.keras.layers.LSTMStateTuple(c[li], h[li]))

# Do several tensor transformations, because the function dynamic_rnn requires the output to be of
# a specific format. Read more at: https://www.tensorflow.org/api_docs/python/tf/nn/dynamic_rnn

all_inputs = tf.concat([tf.expand_dims(t, 0) for t in train_inputs], axis=0)

# Create LSTM layer
lstm_layer = tf.keras.layers.LSTM(num_nodes[-1], return_sequences=True, return_state=True, dropout=dropout)

# Pass inputs and initial state to the LSTM layer
all_lstm_outputs, final_state, _ = lstm_layer(all_inputs, initial_state=initial_state)

all_outputs = tf.keras.layers.Dense(1)(all_lstm_outputs)

split_outputs = tf.split(all_outputs, num_unrollings, axis=0)```

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我得到了这个错误：

AttributeError: module 'keras.api._v2.keras.layers' has no attribute 'LSTMStateTuple'

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