Use the nn.RNN module and work with an input sequence. I also show you how easily we can switch to a gated recurrent unit (GRU) or long short-term memory (LSTM) RNN.
The pytorch-rnn-lstm-gru is a module within PyTorch that utilizes the nn.RNN functionality, allowing manipulation of input sequences within neural networks. This module showcases the flexibility to seamlessly transition between different recurrent neural network architectures such as the gated recurrent unit (GRU) or long short-term memory (LSTM) RNNs. This adaptability enables users to experiment and compare the performance of different RNN variants while working with sequential data, providing a convenient and straightforward way to implement these models within PyTorch.