src/model.py

import torch
import torch.nn as nn


class Tox21SNN(nn.Module):

    def __init__(self, in_features, hidden_dim=768, n_layers=8, dropout=0.05):
        super().__init__()
        self.in_features = in_features
        self.hidden_dim = hidden_dim
        self.n_layers = n_layers

        activation = nn.SELU()
        drop = nn.AlphaDropout(p=dropout)

        dims = [hidden_dim] * (n_layers + 1)
        dims[0] = in_features
        dims[-1] = 12

        layers = []
        for i in range(n_layers + 1):
            in_dim = dims[i]
            out_dim = dims[-1] if i == n_layers else dims[i + 1]
            fc = nn.Linear(in_dim, out_dim)
            if i < n_layers:
                layers.extend([fc, activation, drop])
            else:
                layers.append(fc)

        self.model = nn.Sequential(*layers)

    def forward(self, x):
        return self.model(x)