Source code for networks.linear_net

import math
import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F


[docs]class Linear_net_sig(nn.Module): """ Linear binary classifier """ def __init__(self, input_dim, out_dim=1): super(Linear_net_sig, self).__init__() # an affine operation: y = Wx + b self.fc1 = nn.Linear(input_dim, 1) self.sigmoid = nn.Sigmoid()
[docs] def forward(self, x): x = self.fc1(x) x = self.sigmoid(x) return x
[docs]class LinearNetDefer(nn.Module): """ Linear Classifier with out+1 units and no softmax """ def __init__(self, input_dim, out_dim): super(LinearNetDefer, self).__init__() # an affine operation: y = Wx + b self.fc = nn.Linear(input_dim, out_dim + 1)
[docs] def forward(self, x): out = self.fc(x) return out
[docs]class LinearNet(nn.Module): """ Linear Classifier with out units and no softmax """ def __init__(self, input_dim, out_dim): super(LinearNet, self).__init__() # an affine operation: y = Wx + b self.fc = nn.Linear(input_dim, out_dim)
[docs] def forward(self, x): out = self.fc(x) return out