Let’s say your  batch_size=5 and seq_len=3. So each batch looks like
batch = [
        [x1_1, x1_2, x1_3],
        [x2_1, x2_2, x2_3],
        ...
        [x5_1, x5_2, x5_3]
       ] # shape (batch_size, seq_len, input_size) 

where x{seq_id}_{timestep}

For a given timestep t, the RNN reads the t-th observations from all the sequences in the batch. So at timestep t, it will read and process input_t
input_1 = [x1_1, x2_1..., x5_1] # shape (batch_size, input_size)
input_2 = [x1_2, x2_2..., x5_2]
input_3 = [x1_3, x2_3..., x5_3]

However, you don’t actually need to split your data into time-stepped inputs like this, the RNN just needs
rnn_input = [input_1, input_2, input_3] # (seq_len, batch_size, input_size)

from you.
Hope this helps!