Method __init__

openrec/modeling/decoders/cppd_decoder.py:174–262

(self,
                 in_channels,
                 out_channels,
                 num_layer=2,
                 drop_path_rate=0.1,
                 max_len=25,
                 vis_seq=50,
                 iters=1,
                 pos_len=False,
                 ch=False,
                 rec_layer=1,
                 num_heads=None,
                 ds=False,
                 **kwargs)

class CPPDDecoder(nn.Module):

    def __init__(self,
                 in_channels,
                 out_channels,
                 num_layer=2,
                 drop_path_rate=0.1,
                 max_len=25,
                 vis_seq=50,
                 iters=1,
                 pos_len=False,
                 ch=False,
                 rec_layer=1,
                 num_heads=None,
                 ds=False,
                 **kwargs):
        super(CPPDDecoder, self).__init__()

        self.out_channels = out_channels  # none + 26 + 10
        dim = in_channels
        self.dim = dim
        self.iters = iters
        self.max_len = max_len + 1  # max_len + eos
        self.pos_len = pos_len
        self.ch = ch
        self.char_node_embed = Embeddings(d_model=dim,
                                          vocab=self.out_channels,
                                          scale_embedding=True)
        self.pos_node_embed = Embeddings(d_model=dim,
                                         vocab=self.max_len,
                                         scale_embedding=True)
        dpr = np.linspace(0, drop_path_rate, num_layer + rec_layer)

        self.char_node_decoder = nn.ModuleList([
            DecoderLayer(
                dim=dim,
                num_heads=dim // 32 if num_heads is None else num_heads,
                mlp_ratio=4.0,
                qkv_bias=True,
                drop_path=dpr[i],
            ) for i in range(num_layer)
        ])
        self.pos_node_decoder = nn.ModuleList([
            DecoderLayer(
                dim=dim,
                num_heads=dim // 32 if num_heads is None else num_heads,
                mlp_ratio=4.0,
                qkv_bias=True,
                drop_path=dpr[i],
            ) for i in range(num_layer)
        ])

        self.edge_decoder = nn.ModuleList([
            DecoderLayer(
                dim=dim,
                num_heads=dim // 32 if num_heads is None else num_heads,
                mlp_ratio=4.0,
                qkv_bias=True,
                qk_scale=1.0 if (rec_layer + i) % 2 != 0 else None,
                drop_path=dpr[num_layer + i],