nets/model.py

import torch
import torch.nn as nn
from nets.decoder import Decoder
from nets.projections import Projections
from nets.encoder import Encoder


class Model(nn.Module):
    def __init__(self, input_size, embedding_size,
                 decoder_input_size,
                 num_heads=8, num_layers=4, ff_hidden=250, *args, **kwargs):
        super().__init__()

        self.embedding_size = embedding_size

        # ----------- Encoder -----------
        self.encoder = Encoder(
            n_heads=num_heads,
            embed_dim=embedding_size,
            n_layers=num_layers,
            feed_forward_hidden=ff_hidden,
            node_dim=input_size
        )

        # ----------- Decoder -----------
        self.decoder = Decoder(
            decoder_input_size=decoder_input_size,
            embedding_size=embedding_size,
            num_heads=num_heads
        )

        # ----------- Attention Projections -----------
        self.projections = Projections(
            n_heads=num_heads,
            embed_dim=embedding_size
        )

        # ----------- Fleet Attention Encoder (Optional) -----------
        self.fleet_attention = Encoder(
            n_heads=num_heads,
            embed_dim=embedding_size,
            n_layers=1,
            feed_forward_hidden=ff_hidden,
            node_dim=embedding_size + 1
        )