def __init__(self, nfeats, noutputs, nlayers=4):
super().__init__()
encoder_layer = transformer.TransformerEncoderLayer(
nfeats + 16, 2, nfeats)
decoder_layer = transformer.TransformerDecoderLayer(
nfeats + 16, 2, nfeats)
self.encoder = transformer.TransformerEncoder(encoder_layer, nlayers)
self.decoder = transformer.TransformerDecoder(decoder_layer, nlayers)
self.predict_outputs = nn.Linear(nfeats + 16, noutputs)
def __init__(self, dim_model, num_heads, dim_feedforward, num_layers):
super().__init__()
assert num_layers >= 1
self.layers = nn.ModuleList([
transformer.TransformerDecoderLayer(
d_model=dim_model,
nhead=num_heads,
dim_feedforward=dim_feedforward,
dropout=0.0,
) for _ in range(num_layers - 1)
] + [
DecoderLastLayerPytorch(
d_model=dim_model,
nhead=num_heads,
dim_feedforward=dim_feedforward,
dropout=0.0,
)
])
self.num_layers = num_layers