| import torch | |
| import torch.nn as nn | |
| import pandas as pd | |
| import numpy as np | |
| DROPOUTX = 0.05 | |
| class SimplePlusNN2(nn.Module): | |
| def __init__(self, input_size, num_classes): | |
| super(SimplePlusNN2, self).__init__() | |
| self.fc1 = nn.Linear(input_size, 64) | |
| self.relu = nn.ReLU() | |
| self.fc2 = nn.Linear(64, 8) | |
| self.relu = nn.ReLU() | |
| self.fc3 = nn.Linear(8, 1) | |
| self.dropout = nn.Dropout(DROPOUTX) | |
| self.sigmoid = nn.Sigmoid() | |
| def forward(self, x): | |
| x = self.relu(self.fc1(x)) | |
| x = self.relu(self.fc2(x)) | |
| x = self.dropout(x) | |
| x = self.sigmoid(self.fc3(x)) | |
| return x |