TransformerDecoder¶
- class torch.nn.TransformerDecoder(decoder_layer, num_layers, norm=None)[source][source]¶
TransformerDecoder is a stack of N decoder layers.
- Parameters
decoder_layer (TransformerDecoderLayer) – an instance of the TransformerDecoderLayer() class (required).
num_layers (int) – the number of sub-decoder-layers in the decoder (required).
norm (Optional[Module]) – 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, tgt_is_causal=None, memory_is_causal=False)[source][source]¶
Pass the inputs (and mask) through the decoder layer in turn.
- Parameters
tgt (Tensor) – the sequence to the decoder (required).
memory (Tensor) – the sequence from the last layer of the encoder (required).
tgt_mask (Optional[Tensor]) – the mask for the tgt sequence (optional).
memory_mask (Optional[Tensor]) – the mask for the memory sequence (optional).
tgt_key_padding_mask (Optional[Tensor]) – the mask for the tgt keys per batch (optional).
memory_key_padding_mask (Optional[Tensor]) – the mask for the memory keys per batch (optional).
tgt_is_causal (Optional[bool]) – If specified, applies a causal mask as
tgt mask
. Default:None
; try to detect a causal mask. Warning:tgt_is_causal
provides a hint thattgt_mask
is the causal mask. Providing incorrect hints can result in incorrect execution, including forward and backward compatibility.memory_is_causal (bool) – If specified, applies a causal mask as
memory mask
. Default:False
. Warning:memory_is_causal
provides a hint thatmemory_mask
is the causal mask. Providing incorrect hints can result in incorrect execution, including forward and backward compatibility.
- Return type
- Shape:
see the docs in
Transformer
.