class_docstr: Generate next token from the representation. This part is separated from the decoder, mostly for the convenience of sharing weight between embedding and generator.
  log(softmax(Wx + b))
code: def __init__(self, dim_model, vocab_size):
      super(Generator, self).__init__()
      self.proj = nn.Linear(dim_model, vocab_size)
  
imports: import torch
  import torch.nn
  from torch.nn import LayerNorm
  import copy
label_desc: Use image node_id 1 to create a new Generator object from inherited base classes: nn with example: obj = Generator(dim_model, vocab_size)