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



class FFN(nn.Module):

	def __init__(self,input_size,hidden_size_1, hidden_size_2, num_classes):
		super().__init__()
		self.h1 = nn.Linear(input_size,hidden_size_1)
		self.h2 = nn.Linear(hidden_size_1, hidden_size_2)
		self.h3 = nn.Linear(hidden_size_2,num_classes)

	def forward(self, x):
		x = self.h1(x)
		x = F.leaky_relu(x)
		x = self.h2(x)
		x = F.leaky_relu(x)
		x = self.h3(x)
		x = F.sigmoid(x)
		return x