Thank you!
Yes, I’m using nn.LSTM with 2 hidden layers (unidirectional). So, I also want to ask about the shape of h_n specifically in this case. For example, I get the shape of h_n as torch.Size([2, 1, 1500])
If I understand it correctly, I can get the hidden states of the hidden layers by indexing into them in the order:
first_hidden_layer_hidden_state = h_n[0]    # torch.Size([1, 1500])
second_hidden_layer_hidden_state = h_n[-1]    # torch.Size([1, 1500])

Is this a correct way of indexing and getting the hidden states?
P.S.: I’m just interested only in these hidden states because I want to pass them to a downstream network for further processing.