Hi, I guess your model will be like:
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable

class YourModel(nn.Module):
    def __init__(self):
        super(YourModel, self).__init__()
        self.lin1 = nn.Linear(5, 5)
        self.lin2 = nn.Linear(5, 5)

    def forward(self, m_i, v_a):
        y1 = self.lin1(m_i)
        y2 = self.lin2(v_a)
        y = F.tanh(y1+y2)
        y = F.softmax(y)
        return y

Then,
model = YourModel()
m_i = Variable(torch.Tensor([1,2,3,4,5]))
v_a = Variable(torch.Tensor([6,7,8,9,10]))
output = model.forward(m_i, v_a)

you can get output as follows:
Variable containing:
 0.0563
 0.4156
 0.4156
 0.0563
 0.0563
[torch.FloatTensor of size 5]