TransformerDecoder
class torch.nn.TransformerDecoder(decoder_layer, num_layers, norm=None)
TransformerDecoder is a stack of N decoder layers
Parameters:
      * decoder_layer -- an instance of the
        TransformerDecoderLayer() class (required).
  * **num_layers** -- the number of sub-decoder-layers in the
    decoder (required).

  * **norm** -- the layer normalization component (optional).

Examples::
      >>> decoder_layer = nn.TransformerDecoderLayer(d_model=512, nhead=8)
      >>> transformer_decoder = nn.TransformerDecoder(decoder_layer, num_layers=6)
      >>> memory = torch.rand(10, 32, 512)
      >>> tgt = torch.rand(20, 32, 512)
      >>> out = transformer_decoder(tgt, memory)
forward(tgt, memory, tgt_mask=None, memory_mask=None, tgt_key_padding_mask=None, memory_key_padding_mask=None)
  Pass the inputs (and mask) through the decoder layer in turn.

  Parameters:
     * **tgt** (*Tensor*) -- the sequence to the decoder
