LSTM Keras API: Handling two cases; y<t> = x<t+1> and y<t> = x<t>

Keras
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I’m learning how to implement LSTM using Keras API, and got a question regard how I can handle two different cases; y = x and y = x

For example, the following code builds a simple LSTM in Keras:

inputs = tf.random.normal([32, 10, 8])
lstm = tf.keras.layers.LSTM(4, return_sequences=True, return_state=True)
whole_seq_output, final_memory_state, final_carry_state = lstm(inputs)

When doing training for name entity task y equals to x, but when doing inferencing then y = x. But it seems like there is no argument/parameter specifying these cases when initializing LSTM in Keras.

Is it that these things are being handled internally all by Keras API by itself or is there something I’m missing?

Thanks.

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