Can you explain me why this implementation for multiclass text classification doesn’t use sigmoid  since expects logits?

  
      github.com
  
  
    keishinkickback/Pytorch-RNN-text-classification/blob/master/model.py 53
import torch
import torch.nn as nn
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence


class RNN(nn.Module):

    def __init__(self, vocab_size, embed_size, num_output, rnn_model='LSTM', use_last=True, embedding_tensor=None,
                 padding_index=0, hidden_size=64, num_layers=1, batch_first=True):
        """

        Args:
            vocab_size: vocab size
            embed_size: embedding size
            num_output: number of output (classes)
            rnn_model:  LSTM or GRU
            use_last:  bool
            embedding_tensor:
            padding_index:
            hidden_size: hidden size of rnn module


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