transformer tgt?

[a1wj1]

Hello, I don't understand the following code

` if self.end2end:
tgt = self.query_pos_embed.repeat(bs, 1, 1)
else:
tgt = self.position_encoding(
torch.ones((bs, 1, 20, 20), device=x["rgb"].device)
)
tgt = tgt.flatten(2)
tgt = torch.cat([tgt, self.query_pos_embed.repeat(bs, 1, 1)], 2)
tgt = tgt.permute(2, 0, 1)

    memory = self.encoder(features, mask=self.attn_mask)
    hs = self.decoder(self.query_embed.repeat(1, bs, 1), memory, query_pos=tgt)[0]

`

From the flowchart of the paper, the input decoder is either waypoints or the current image, but why is the target sequence here a learnable parameter torch.ones((bs, 1, 20, 20)?

[deepcs233]

Hi!
The (bs, 1, 20, 20) is used as the queries fot the traffic map.