Keras LSTM-RNN layer

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System information

• TensorFlow version (you are using): 2.3.1
• Are you willing to contribute it (Yes/No): Yes, when able and available

Describe the feature and the current behavior/state.
There is a high-level API on Keras to LSTM layers on top of RNN that allows getting LSTM output as simple as this:

lstm_module = LSTMModule(5)   
lstm_input = tf.constant([[0.1, 0.2], [0.3, 0.4]], shape=[1, 2, 2])
lstm_output = lstm_module(lstm_input)

A definition of the LSTM Layer with Model Subclassing API from Tensorflow:

class LSTMModule(tf.keras.layers.Layer):

    def __init__(self, lstm_dims):
        super().__init__()
        self.lstm_dims = lstm_dims
        self.lstm = LSTM(lstm_dims, return_sequences=True, return_state=True)

    def call(self, inputs):
        # Forward pass
        ini_hidden_state = tf.zeros(shape=[1, self.lstm_dims]), tf.zeros(shape=[1, self.lstm_dims])
        return self.get_lstm_output(self.lstm, inputs, ini_hidden_state)

    @staticmethod
    def get_lstm_output(lstm_model, input_sequence, initial_state):
        output = lstm_model(input_sequence, initial_state=initial_state)
        hidden_states, hidden_state, cell_state = output[0], output[1], output[2]
        return hidden_states, hidden_state, cell_state

Will this change the current api? How?
This will add a new feature to tensorflow-framework module.

Who will benefit with this feature?
Anyone that requires deep learning to solve sequence classification and prediction problems and everyone who is already familiar with Keras.

Any Other info.
This feature comes from #270

Không có tệp hoặc bài kiểm thử nào được nêu tên. Hãy bắt đầu bằng cách xem xét issue #270 và các API tensorflow-framework hiện có liên quan đến yêu cầu về một layer LSTM/RNN theo kiểu Keras. Công việc được xem là hoàn tất khi xác định được API LSTM cấp cao được yêu cầu có thuộc repository này hay không và xác định được phạm vi triển khai của nó.