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


class DistributionRegressor(nn.Module):

    def __init__(self, n_classes, hidden_dim=256):
        super(DistributionRegressor, self).__init__()
        self.fc1 = nn.Linear(n_classes, hidden_dim)
        self.fc2 = nn.Linear(hidden_dim, n_classes)

    def forward(self, x):
        x = F.relu(self.fc1(x))
        x = self.fc2(x)
        x = F.softmax(x, dim=-1)
        return x