Clarification for the forward function of the SequenceSummary class from modeling_utils.py
Hello,I have a question about the documentation strings provided for the forward function of the SequenceSummary class from modeling_utils.py:github.comhuggingface/transformers/blob/dc552b9b7025ea9c38717f30ad3d69c2a972049d/src/transformers/modeling_utils.py#L1484self.activation: Callable = get_activation(activation_string) if activation_string else Identity()self.first_dropout = Identity()if hasattr(config, "summary_first_dropout") and config.summary_first_dropout > 0:self.first_dropout = nn.Dropout(config.summary_first_dropout)self.last_dropout = Identity()if hasattr(config, "summary_last_dropout") and config.summary_last_dropout > 0:self.last_dropout = nn.Dropout(config.summary_last_dropout)def forward(self, hidden_states: torch.FloatTensor, cls_index: Optional[torch.LongTensor] = None) -> torch.FloatTensor:"""Compute a single vector summary of a sequence hidden states.Args:hidden_states (:obj:`torch.FloatTensor` of shape :obj:`[batch_size, seq_len, hidden_size]`):The hidden states of the last layer.cls_index (:obj:`torch.LongTensor` of shape :obj:`[batch_size]` or :obj:`[batch_size, ...]` where ... are optional leading dimensions of :obj:`hidden_states`, `optional`):Used if :obj:`summary_type == "cls_index"` and takes the last token of the sequence as classificationSo whencls_indexis not specified as the argument in SequenceSummary() statement, is the last token of the sequence used for the classification task? The entire sentence for the description is somewhat awkward…Thanks,