It depends how you would like to process this input.
nn.Linear uses a fully-connected weight matrix, such that each input feature will be used to create an output value.
Since you are using a temporal signal, you could create a tensor in the shape [batch_size, sequence_length * features] or alternatively you could also let the linear layer process each “time stamp” separately by passing an input of [batch_size, sequence_length, features].
For temporal singals you should also have a look at e.g. nn.Conv1d etc. as they might be beneficial for your use case.



 superjunnis:

Also, what is nb_features in this case?


in_features defined the number of input features for the linear layer.