Question 2: Consider a vanilla Recurrent Neural Network (RNN) and an …

Consider a vanilla Recurrent Neural Network (RNN) and an LSTM network with the same input dimension, hidden dimension, and output dimension.
Statement 1: The number of trainable parameters in a vanilla RNN is higher than that in an LSTM network. Statement 2: An LSTM has a higher number of parameters because it contains multiple gates (input gate, forget gate, output gate, and candidate state), each having separate weight matrices and biases.
Choose the correct option from the following.