Prediction_Head/MTGGenre_head.py

import torch
from torch import nn
import torch.nn.functional as F

class MLPProberBase(nn.Module):
    def __init__(self, d=768, num_outputs=87):
        super().__init__()
        self.hidden_layer_sizes = [512, ] # eval(self.cfg.hidden_layer_sizes)
        self.num_layers = len(self.hidden_layer_sizes)
        for i, ld in enumerate(self.hidden_layer_sizes):
            setattr(self, f"hidden_{i}", nn.Linear(d, ld))
            d = ld
        self.output = nn.Linear(d, num_outputs)
    
    def forward(self, x):
        for i in range(self.num_layers):
            x = getattr(self, f"hidden_{i}")(x)
            # x = self.dropout(x)
            x = F.relu(x)
        output = self.output(x)
        return output